Advances in Psychology Volume 98 Imagery, Creativity, and Discovery: A Cognitive Perspective

ADVANCES IN PSYCHOLOGY 98 Editors: G. E. STELMACH P. A. VROON NORTH-HOLLAND AMSTERDAM LONDON NEW YORK TOKYO IMAGERY...

Author: Beverly Roskos-Ewoldsen

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ADVANCES IN PSYCHOLOGY 98 Editors:

G. E. STELMACH

P. A. VROON

NORTH-HOLLAND AMSTERDAM LONDON NEW YORK TOKYO

IMAGERY, CREATIVITY, AND DISCOVERY A Cognitive Perspective

ADVANCES IN PSYCHOLOGY

98 Editoi-s:

G. E. STELMACH P. A. VROON

NORTH-HOLLAND AMSTERDAM * LONDON * NEW YORK TOKYO

IMAGERY, CREATIVITY, AND DISCOVERY A Cognitive Perspective

Edited by

Beverly ROSKOS-EWOLDSEN Depai.tnient of Psychology University of Alabama Tuscnloosa, AL, U.S.A.

Margaret Jean INTONS-PETERSON Depurtnient of Psychology lndianu Uiii\vrsity Bloomingtnn, I N , U.S.A.

Rita E. ANDERSON Department oj'Psychology Memorial University St. John's, Neu;foundland, Canuda

1993

-

NORTH-HOLLAND AMSTERDAM LONDON * NEW YORK 'TOKYO

NORTH-HOLL AND ELSEVIER SCIENCE PUBLISHERS B.V. Sara Burgerhartstraat 25 P.O. BOX21 I , 1000 AE Amsterdam, The Netherlands

Library of Congress Cataloging-in-Publication Data

Imagery, creativity, and discovery: a cognitive prspectivdedited by Beverly Roskos-Ewoldsen. Msrgarer Jean Intons-Peterson Rita E. Anderson p. cm. - (Advances in psychology; 98) Based on papers presented Bf a conference held at Vandabilt University in May, 1991 Includes bibliographical references and indexes. ISBN 0-444-89591-4 (alk. paper) 1. Creative ability-congresses. 2 Imagery (Psychology)s. I. Roskos-Ewoldsen, Bevaly. II. Intons-Peterson,Margaret Jean. In. Anderson. Rita E. IV. Series: Advances in psychology (Amsterdam. Netherlands) ; 98. BF411152 1993 153.34~20

93-17150

CIP

ISBN: 0 444 89591 4 0

1993 ELSEVIER SCIENCE PUBLISHERS B.V. All rights reserved.

No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical. photocopying, recording or otherwise, without the prior written permission of' the publisher, Elsevier Science Publishers B.V.. Copyright & Permissions Department, P.O. Box 521, 1000 AM Amsterdam. The Netherlands. Special regulations for readers in the U.S.A. - This publication has been registered with the Copyright Clearance Center Inc. (CCC). Salem, Massachusetts. Information can be obtained from the CCC about conditions under which photocopies of parts of this publication may be made in the U.S.A. All other copyright questions, including photocopying outside of the U.S.A., should be referred to the copyright owner, Elsevier Science Publishers B.V., unless otherwise specified. No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods. products. instructions or ideas contained in the material herein. Thih booh is printed on acid-free paper. Printed in The Netherlands

V

TABLEOF CONTENTS Preface..

.....................................

vii

..............................

xi

List of Contributors

Imagery’s Role in Creativity and Discovery Margaret Jean Intons-Peterson

............

1

The Ins and Outs of Working Memory: . . . . . . . . . . . . . . 39 Overcoming the Limits on Learning from Imagery Daniel Reisberg and Robert Logie Images Are Both Depictive and Descriptive Deborah Chambers

...........

77

.......

99

Imagery, Reconstructive Memory, and Discovery Ira E. Hyman, Jr.

Mental Imagery: Fixed or Multiple Meanings? . . . . . . . . 123 Nature and Function of Imagery in Creative Thinking Geir Kaufmann and Tore Helstrup 6

The Ambiguity of Mental Images: . . . . . . . . . . . . . . . . . . 151 Insights Regarding the Structure of Shape Memory and its Function in Creativity Mary A. Peterson Discovering Emergent Properties of Images Beverly Roskos-Ewoldsen

. . . . . . . . . . . 187

Multiple Perspectives on Discovery . . . . . . . . . . . . . . . . . 223 and Creativity in Mind and on Paper Rita E. Anderson and Tore Helstrup

Table of Contents

vi 9

Mental Imagery and Creative Discovery Ronald A. Finke

10

Imagery and Discovery Stephen K. Reed

. . . . . . . . . . . . . . 255

..........................

11 Imagery, Creativity, and Discovery: Conclusions and Implications Beverly Roskos-Ewoldsen, Margaret Jean Intons-Peterson, and Rita E. Anderson

.287

. . . . . . . . . . . . . . . . .313

12

Author Index

..................................

329

13

Subject Index

..................................

337

vii

PREFACE Does creativity depend on imagery? Can discoveries be made in imagery? Einstein and many others (see Shepard, 1978), have claimed that their creations began first as images and only later were transformed into words. If imagery has precedence in creative discoveries, why do people sometimes have difficulty "seeing" information in their visual images that they readily see in perception? Do our expectations affect the way images are generated and maintained; do our expectations affect what can be discovered in or learned from images? How do creativity, discovery, and imagery intersect? These intriguing questions have long tantalized psychologists and others interested in creativity. Despite the extensive history of creativity, discovery, and imagery as phenomena in need of explanation, relatively little progress has been made in answering these queries until fairly recently. Now, however, recent theoretical developments, coupled with a growing data base, suggest that it is desirable to bring together relevant research, to assess theories, and to chart some courses for the future. In part, we were acting and reacting to the developments in the field; we thought it timely to juxtapose various views of imagery, creativity, and discovery. The above goals guided development of the book, but, like most efforts, the book evolved. It began with hallway conversations at the meetings of the Psychonomic Society in November, 1990, while some of us chatted about our research. Frustrated by the short time available at the meetings, we decided to reconvene at a conference to explore common themes emerging from a cognitive approach to imagery, creativity, and discovery. Bev Roskos-Ewoldsen assumed responsibility for organizing the conference. She contacted various people and institutions about sponsoring the conference, invited prospective participants and attenders, made the arrangements, and engineered an intellectually challenging and delightful conference. The conference was held at Vanderbilt University in May, 1991.

viii

Preface

Diverse opinions, paradigms, and results sparked our imagination. The result was an invigorating and vigorous sharing of experiences and views, as well as an agreement to share our experience with the world via a book. A number of themes emerged, and these are developed in the chapters in this book. One theme, of ancient but still current vintage, is that many individuals, universally acclaimed for their creativity, believe that their creative discoveries blossomed from their images. We could not ignore these impressions, often offered with compelling fervor. However, the experimental evidence seemed less persuasive than the anecdotal accounts. For example, college students, unselected for imagery or creative ability, failed to detect a second interpretation of the perceptually ambiguous duck-rabbit figure in their images, although they were able to do so as soon as they drew their images on paper (e.g., Chambers & Reisberg, 1985). Such results suggest that the images might constrain creativity and discovery, rather than expanding it, as the anecdotal reports had intimated. Needless to say, the original duck-rabbit findings drove a number of our contributors to the laboratory to pursue various explanations. The results of these explorations delivered still other themes. One of the additional themes is that expectations affect what c a n be detected in images. If subjects expect a particular orientation, it may be difficult for them to re-orient their images, thereby reducing the probability of making discoveries from their images (see chapters by Chambers, Peterson, and Reisberg-Logie). These expectations may be determined by linguistic or by perceptual (graphic, pictorial) information used to induce imagery. Moreover, the more cohesive, symmetrical, or psychologically "good1'an imaged pattern is, the more difficult it may be to dissemble and reassemble (see chapters by Peterson and Roskos-Ewoldsen),another theme. In brief, expectations may constrain the utility of imagery. Several ways to overcome these constraints are demonstrated. Chambers reports the use of instructions to view the image from a different orientation; Hyman and Peterson use hints designed to serve the same purpose. Kaufmann and Helstrup demonstrate greater facility with mental discovery in images among artists than is typical of college students unselected for imaginal or creative ability.

Preface

ix

Still another theme is that images can be combined mentally to yield composites. These composites may serve as media for the creation and discovery of new patterns (see chapters by Anderson and Helstrup, Finke, Intons-Peterson, Roskos-Ewoldsen). In the mental synthesis of component parts, constraining the kind of product to be discovered may actually increase the numbers of composites identified as creative by independent judges (Finke). Furthermore, patterns judged t o be perceptually good or cohesive are more difficult t o parse imaginally than those judged less good or cohesive, which suggests that imagining the known and predictable may be creatively counterproductive (Roskos-Ewoldsen). Practice with the mental construction of novel image composites may increase the production of creative composites in a second session (IntonsPeterson). Finally, compared to pure mental synthesis, the provision of drawing support increases the numbers of creative patterns by a surprisingly surprisingly small amount (Anderson and Helstrup). The cognitive influence permeated the conference, and it shapes the models presented in the chapters. All of the chapters offer or evaluate models of imagery, creativity, or discovery which have a distinctive cognitive flavor to them, as is demanded by the evidence. Some of the models attempt t o integrate perceptual and other sensory systems with imagery, creativity, or discovery (Reisberg and Logie). Others emphasize working memory (Anderson and Helstrup, Kaufmann and Helstrup, Reisberg and Logie, Roskos-Ewoldsen). As well, the need to examine cognitive models of imagery and creativity and discovery from other perspectives (i.e., evolution, development, neurophysiological, motivation) was raised (Anderson and Helstrup, Intons-Peterson). The book culminates with two chapters. Reed develops the conditions under which we are or are not likely t o find imagery useful. Roskos-Ewoldsen,Intons-Peterson, and Anderson summarize the current status of the field and identifies new directions t o pursue. To say more now would be to give away many of the creative images to be discovered in the chapters. We thank Vanderbilt University and Indiana University for their contributions to and financial support of the conference. Specifically, Randy Blake and Keith Clayton helped Bev Roskos-

X

Preface

Ewoldsen and me to organize the conference by guiding Bev toward knowledgeable contacts at Vanderbilt University. Also assisting were the Office of Research and the University Graduate School (Dean George Walker) and the College of Arts and Sciences (Dean Morton Lowengrub), both of Indiana University. More good luck was in store, for Elsevier Scientific Publishers agreed t o publish the book. In particular, I want t o state our appreciation of the excellent assistance of K. Michielsen and Erik Oosterwijk. Other acknowledgments are in order. Catherine Barnes and Vicki Blackwell are responsible for preparation of the manuscript. They and we often relied on Nathan Engle and Sheryl Mobley for their voluminous knowledge of computers and software as we prepared camera-ready copy. We are most grateful to them. Finally, we thank our families and colleagues for their support and forbearance.

Beverly Roskos-Ewoldsen Margaret Jean Intons-Peterson Rita E. Anderson July 1992

References Chambers, D., & Reisberg, D. (1985). Can mental images be ambiguous? Journal of Experimental Psychology: Human Perception and Performance, 11, 318-328. Shepard, R. N. (1978). Externalization of mental images and the act of creation. In B. S. Randhawa and W. E. Coffman (Eds.). Visual learning, thinking, and communication, (pp. 133-189). New York: Academic Press.

xi

LIST OF CONTRIBUTORS Rita E. Anderson Department of Psychology, Memorial University of Newfoundland, St. John's, Newfoundland Canada A1C 5S7 Deborah Chambers 1903 Gatewood Place, Silver Springs, Maryland 20903, U.S.A. Ronald A. Finke Department of Psychology, Texas A & M University, College Station, Texas 77843-4235,U.S.A. Tore Helstrup Department of Cognitive Psychology, University of Bergen, Sydneshaugen 2,5007 Bergen, Norway Ira E. Hyman, Jr. Department of Psychology, Western Washington University, Bellingham, Washington 98225,U.S.A. Margaret Jean Intons-Peterson Department of Psychology, Indiana University, Bloomington, Indiana 47405,U.S.A. Geir Kaufmann Department of Cognitive Psychology, University of Bergen, Sydneshaugen 2,5007 Bergen, Norway Robert Logie Department of Psychology, King's College, University of Aberdeen, Aberdeen AB9 2UB, United Kingdom

xii

List of Contributors

Mary A. Peterson Department of Psychology, University of Arizona, Tucson, Arizona 85721,U.S.A. Stephen K. Reed Department of Psychology, San Diego State University, San Diego, California 92182,U.S.A. Daniel Reisberg Department of Psychology, Reed College, Portland, Oregon 97202,U.S.A. Beverly Roskos-Ewoldsen Department of Psychology, The University of Alabama, Box 870348,Tuscaloosa, Alabama 35487-0348,U.S.A.

Imagery, Creativity, and Discovcry: A Cognitive Pcrspectivc B. Koskos-Ewoldson, M.J.Intons-Peterson and K.E. Anderson (Editors) 0 1993 Elscvier Science Publishcrs B.V. All rights rescrvcd.

1.

Chapter 1

IMAGERY'S ROLE IN CREATMTY AND DISCOVERY Margaret Jean Intons-Peterson Department of Psychology Indium University Bloomington, IN 47405 USA My central task in this chapter is to give a brief historical survey of what we know about the creative process. In preparation for it, I studied books, articles, manuscripts, and more books. It was an enlightening experience. I learned that, in 1926,Wallas told us that the creative process has four stages: preparation, incubation, illumination, and verification. In 1962, Hilgard's third edition of his famous text, Introduction to Psychdogy, told us the same: The four stages of creative thought are preparation, incubation, i l l h a t i o n , and verification. In 1991,65 years after Wallas's pronouncement, Solso delivers the same message. Psychologists seem to be astonishingly uncreative! Seriously, what do we know about imagery's role in the creative process, defined as the sense of bringing into being or as causing to exist, and in the discovery process, defined as making known or visible or of finding something for the &st time? I'm tempted to say, "Preciouslittle." But that is too pessimistic. We have made progress, progress that will be addressed in the chapters in this book. Although we may not have as extensive, compellingevidence as we would like, the topic has long piqued curiosity, and investigations of the creative process have a substantial history. One strongly held view is that imagery plays a critical role in creativity. For example, in his book,Imagery in Scientific Thought,Miller (1984) says, ' I . . . an ingredient essential to scientific research of the highest creativity is what Poincark described as 'our need of thinking in images"' (p. 222). Miller attributes to Aristotle the claim that "thought is impossible without an image" (1984, p. 263) and to Plato the view that

2

Margaret Jean Intons-Peterson

mental images are like impressions on a wax tablet which may be stored for later use. Much of the evidence for the role of imagery in creativity and discovery has been anecdotal, consisting largely of reports from creative persons about the processes contributing to their creative efforts (e.g., Arieti, 1976; Arnheim, 1969; Ghiselin, 1952; Miller, 1984, Roe, 1951; Shepard, 1978). These anecdotal observations make fascinating reading, and they offer insights into the role of imagery in both creativity and discovery, Nevertheless, the anecdotes do not answer some basic questions about the interplay of imagery, creativity, and discovery. For answers, we must turn to more systematic investigations. These investigations have taken two forms: correlational and experimental. The plan of this chapter is to chronicle some of the insights afforded by anecdotal observations,to identify some central issues, and to examine correlational and experimental evidence pertaining to these issues.

Anecdotal Observations Imagery has long been thought to contribute to creativity. For example, in his provocative chapter about the externalization of mental images, Shepard (1978)recounts instances in which chemists, physicists, biologists, musicians, artists, writers, architects, mnemonists, chess masters, mathematicians, geometers, and surgeons claim that images were central to their creative output. Some of the stories related by Shepard (1978)are well-known, such as Einstein’s realization, while imagining that he was traveling beside a beam of light, that the stationary spatial oscillation he %awl’ did not correspond to Maxwell’s equations for the propagation of electromagnetic waves, Kekule’s dream about a snake swallowingits tail, which led to his formulation of the benzene ring, Watson’s awareness of the structure of DNA from pairs of adenine residues that whirled before his closed eyes while napping, and Mozart’s claim that he could hear an entire musical work before recording any of it. Others are less well-known. While practicing golf swings in a dream, Jack Nicklaus discovered an error in the way he gripped his club. By correctingthis error, his game improved by 10 points almost immediately. The American sculptor James Surls reports imagining his sculptures. He is mentally able t o remove and add to various portions of a sculpture. In

Imagery's Role in Creativity and Discovery

3

a Regents' Lecture given at the University of California at Berkeley in 1976, Joan Didion described how "pictures in her mind" drove her novels. Clearly, these creative individuals believe that images inform, guide, and even illuminate their creative activities, corresponding to Wallas's third stage of illumination. These individuals also are noteworthy for being professionals in their respective areas, for having prepared themselves by virtue of their training and occupation. Most reports mention preoccupation with their topics. Thus, the reports lend credence to Wallas's (1926)fmt and second stages of preparation and incubation,as well. Finally, many talk about going over their creations or discoveries to be sure that they were correct and correctly transcribed, thereby supporting Wallas's fourth stage of verification. Poincar6 summed up the situation, when he said, "It is by logic that we prove, but by intuition that we invent" (Miller, 1984, p. 233). These delightful reports, and many others, are inspiring, but anecdotal, haphazardly or selectively collected. There are no checks to ascertain whether images preceded the creative moment or whether creative realizations unfolded in interaction with imagery. It is not clear how discovery occurs. That is, when does the creator become aware that a discovery has been made? How complete are most initial discoveries? Do they require substantial correction and modification? Most important, are images necessary for creative invention? This last question sparked a bitter debate in physics. Part of the lore of the field, Miller (1984) tells us, is that theoretical physicists should be able to intuit processes and solutions;they should be able to imagine them. Letters from Einstein, Bohr, Faraday, and countless others were cited as evidence. With the advent of the general and special theories of relativity and quantum mechanics, physicists began to experience difficulty in imagining processes with multiple dimensions. They found it hard, for example, to imagine simultaneous changes in time as a fourth (or more) dimension or to imagine something not previously experienced, although some people, including Einstein and Mozart, claimed to be able to do so. One camp of physicists, led by Heisenberg, argued that physicists would have to rely on mathematics because "there can be no directly intuitive geometrical interpretation because the motion of electrons cannot be described in terms of the familiar concepts of space and time" (Miller, 1984, p. 142). Fortunately, the work of Schrodinger,Dirac, Pauli, and Feynman showed otherwise. In effect, they returned visualization to a hallowed status in physics.


4

Nevertheless, it remains difficult to imagine simultaneously depth, movement, and time lapse. The ability to do so may be a characteristic that sets some gifted individuals apart from others. These anecdotal reports leave many questions unanswered, to be sure, but Shepard has extracted some challengingthemesfrom them. One set of themes has to do with characteristicsof creative individuals and the circumstances that may foster their creativity. Another set focuses on the interrelationships between imagery and creativity. Let us begin with the first set. Although these characteristics are not really our bailiwick, they are thought-provoking.

The Creative Person The characteristics that may aid the development of creativity may provide a framework for more systematic exploration of the imagerycreativity connection. Shepard (1978, p. 155) suggests, . that the genetic potential for visual-spatial creativity of a high order seems especiallylikely to be revealed andor fostered in a child (a) who is kept home from school during the early school years and, perhaps, is relatively isolated from age mates, as well, (b) who is, if anything, slower than average in language development, (c)who is furnished with and becomes unusually engrossed in playing with concrete physical objects, mechanical models, geometrical puzzles or, simply, wooden cubes. In addition, the inspiration to press relentlessly and concertedly toward the highest achievements that such a creativity makes possible may require the stimulus or model provided by a previous great thinker of a similar turn of mind. Thus Einstein may require his Maxwell and Maxwell his Faraday . . . At the same time, some of the factors that contribute to this kind of creativity may also carry with them an increased predispositionnot only toward some degree of dyslexia . . , but also toward the sorts of mental breakdowns, aberration, or even hallucinations that at one time or another afflicted several of the scientists we have mentioned, including Newton,

. .


5

Faraday, Cardan, Pascal, and Tesla . . . These are interesting speculations about highly gifted and creative individuals. They may or may not apply to a less select sample, who represent the general focus of this book. In brief, we are concerned with the imagery-creativity-discoveryconnectionsin typical human processing, although Anderson and Helstrup raise questions about some developmental aspects of imagery and both Kaufmann and Helstrup and Reed report research with trained architects, artists, or designers in their chapters in this volume.

Imagery's Role in Creativity More important for our purposes are reasons Shepard (1978) offers for the special effectiveness of mental imagery and spatial visualization in the creative process, his second set of themes. He identifies five reasons. The firstis that imagery and spatial visualization offer rich alternatives to the typical strictures imposed by language and traditional ways of thinking. As Shepard (1978, pp. 156)notes, "it seems reasonable that the most novel ideas and radical departures from traditional ways of thinking are not likely to arise within the very system ofverbal communication that is the primary vehicle for maintaining and perpetuating established ideas and entrenched traditions." The second reason is that the richness of imagery, and its relation to external sources, may suggest interactions and relations not fully preserved by language. Even an image whose structure parallels that of temporally bound verbal communication may permit more or different comparisons than descriptive language. Third, the nature of images makes them amenable for intuition and manipulation in ways that undoubtedly precede language development, both individually and evolutionarily. Our ability to avoid running into moving objects is an example. We must anticipate where the object willbe at some future time and arrange to avoid being there at that time. These abilities are displayed by all moving organisms, including nonhumans and preverbal children,whether they have functional use of a human language or not. Fourth, Shepard hypothesizes that images are more likely to engage affective and motivational systems than verbal productions. He argues that this is "why powerful emotions of fear, anger, and desire tend to be more strongly determined by the vividness with which one concretely

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pictures the relevant object or event (a plane crash or a terminal illness,in the case of fear) than by the probability that one abstractly assigns to that event by verbal reasoning" (p. 157). A possible h a l factor is that the search for structural symmetries and invariances may be aided by the sensitivity of the visual system to symmetry. Drives toward symmetry strongly motivated the work of Einstein, Maxwell, and Watson, for example. Shepard's reasons for the special effectiveness of mental imagery in the creative process are addressed in one way or another in the chapters of this book. Shepard's reasons for the special effectiveness of imagery in creativity provide a usefil structure for systematicexploration of imagery in creativity and discovery. Let us begin this exploration by asking whether imagery contributes to creativity in principled ways.

The Imagery-Language Connection If, as Shepard suggests, one of the advantages of the use of spatial images is that images may escape some the constraints imposed by our customary and circumscribed use of language, we might expect verbal ability and imagery to be dissociable from each other. One test of this possibility is whether the two play similar roles in creativity. Evidence h m paper-and-penciltests offered by G a o r d (1967),Torrance (1966)and others typically yields positive correlations. These correlations are so persistent that Shaw and DeMers (1986, 1986-87) focused on children with intelligence test scores above 115 as more likely to show a relation between imagery ability and creativity than children with lower scores. Shaw and DeMers correlated scoreson imagery and creativity tests among fifih- and sixth-gradechildren. They used three of Torrance's (1966)tests to assess three aspects of creativity (fluency, flexibility, and originality). Each test contains two verbal forms and two figural (spatial) forms; thus, Shaw and DeMers assessed both verbal and imaginal creativity. They measured three aspects of imagery sometimes thought to be important (vividness,control, and memory), using Marks' (1973)Vividness of Visual Imagery Questionnaire (VVIQ),Gordon's (1949) Test of Visual Imagery Control (TVIC), and Shaw's Visual Memory Test (described in Shaw & DeMers, 1986, 1986-871, respectively. These tests were administered to 54 childrenwho scored above 115on a school-administered intelligence test and to 84 children who scored lower than 115.

Imagery’s Role in Creativity and Discovery

7

In general, creativity scores for originality and flexibility correlated more highly with imaginal vividness and control for the high-IQ group than for the comparison group, in concert with previous demonstrations of an association between intelligence and creativity. More interesting for our purposes is that the high-IQ group showed higher correlations for the figural (spatial) test of creativity with imaginal control (-61)than for the verbal creativity test (.49). The comparison group showed similar trends, but with lower correlations (.29and .18,respectively). Thus, some aspects ofvisual imagery seem to be more tightly associated with spatial creativity than with verbal creativity. However, the effects of verbal communication on spatial aspects of creativity cannot be unambiguously assessed from these data, for a number of reasons. The first is that the tests for spatial and verbal creativity correlate with each other, albeit nonsignificantly (.28, Shaw & DeMers, 1986-87). The second is that all of the measures used in the research contained a heavy verbal component. This heavy linguistic weighting militates against pure assessments of visuospatial ability. Indeed, it is perhaps surprising that the imaginal-verbal creativity correlations were not higher. The correlational approach has other hazards, including interpretation of the direction of the effects, cause-and-effectrelations, the psychometric properties of the various scales, and the absence of control over the use of imagery. Unfortunately, the tests also have questionable validity. Although some correlations have been reported between the creativity tests and individuals judged by teachers to be creative, no unassailable evidence has yet been produced. Further, paper-and-pencil tests of imagery have often been rather unimpressive predictors of imaginal performance (Paivio, 1986). For example, Peterson, Kihlstrom, Rose, and Glisky (1992) failed to find that either the VVIQ or the TVIC predicted imaginal performance. Self-report measures of imagery tend to be uncorrelatedwith performance, although they show modest associations with other self-report measures (Ernest, 1977). Occasionally more substantial correlations are observed (Finke & Shepard, 1986). Perhaps the most disturbing aspect of the correlational approach is that it does not examine the linkbetween imagery and creativity directly. That is, the assessments of each are administered successivelyand utilize different measures. Hence, there is no convincing evidence that components contributing to or invoked by the creativity tests also are involved in the imagery tests. In brief, we cannot assess how or if imagery

8


supports creativity from these data. An alternative way to determine the strength of the link between imagery and creativity is to manipulate the use of imaginal strategies by direct instruction. For example,Helstrup and Anderson (1991)encouraged their subjects to use either visual or verbal strategies to construct new objects in a mental discovery task. Subjects who were instructed to use visual strategies performed considerably better than those told to use verbal strategies,just as Shepard might have predicted. (SeeAnderson & Helstrup's chapter, this volume, for further details.) Unfortunately, the productions were not measured for creativity and hence, their results speak only to a link between imagery and discovery. Language might affect images, like percepts, by biasing subjects toward a particular interpretation. This interpretation may then be very difficult to dislodge, as Chambers and Reisberg (1985) showed. In their work, subjects were able to detect one version of an ambiguous figure (e.g., the ducwrabbit), but not the other form in their image, even though they were able to detect both versions from a subsequent drawing of their image. In this case, language may impose modification-resistant expectations on image generalization. Although the above evidence suggests that language may establish expectations for the shape and characteristics of an image, language also may facilitate expectations if it is used to challenge interpretations of images ( H p a n , this volume; Hyman & Neisser, 1991). Indeed, a number of authors of chapters in this volume (e.g., Chambers, Hyman, and Kaufmann & Helstrup, in particular) argue that language and description may influence visual depictions in myriad ways, ways that extend from interference to facilitation. As Chambers maintains, description shapes depiction. Hyman likens imagery construction to story construction. Imaginal gaps may be filled in, just as is true with stories. Kaufmann and Helstrup contendthat images are neither descriptionsnor mental pictures (images, visual depictions). Instead, they are hybrid mental concepts which embody both symbolic and perceptual properties. Furthermore, the opportunity to articulate may suppress imaginal transformations. Brandimonte, Hitch, and Bishop (1992) recently demonstrated that subjects were more adept at identifymgthe remainder of an image aRer a part had been subtracted mentally when they simultaneously engaged in articulatory suppression (saying "la,la")than when they did not. In other words, the suppression of articulation apparently aided the mental manipulation of the visuospatial material.


9

The effect disappeared when the original images were difficult to name, as we might expect. With easily named images, subjects may rely at least partly on linguistic processes, unless discouraged from doing so by articulatory suppression. With difficult-to-name images, subjects presumably rely almost exclusively on imagery. Significant effects of articulatory suppression on imaginal subtraction occurred for images generated from long-termmemory,but not for images constructed in shortterm or working memory. These results suggest that language (naming) of images may reduce the effectiveness of imaginal manipulations. Note that the evidence suggests that although language may establish expectancies which, in turn, guide either the generation or the interpretation of images in inappropriate or overly constrained ways, the data considered above do not indicate that language activelyinterfereswith the generation of creative images. The research by Shaw and DeMers (1986, 1986-87) implies that visual imagery is more closely associated with spatial than with verbal creativity. These different relations could well have prompted the nonverbal-verbal distinctions drawn from his anecdotal reports that led Shepard (1978) to conjecture that the development of creativity may be fostered by some isolation from traditional language strictures and by the opportunities and commitment to absorb oneself in spatial activities (see the previous quotation from Shepard, 1978, p. 155).

Special Characteristics of Imagery In this section, I combine Shepard’s second and third reasons for the special effectiveness of mental imagery in creativity and discovery, the ideas that imagery‘s richness may deliver interrelationships less apparent in language and that the nature of images makes them particularly amenable to integration and manipulation. Anecdotal Reports Anecdotal reports are strongly supportive. One particularly striking example comes from the inventor Tesla, who claimed that, aRer a few weeks, he inspected his image of a physical machine (e.g.,the three-phase electrical distribution system, the self-starting induction motor) for signs of wear (Shepard, 1978). A hallmark of these reports is that the images

10


represented novel combinations or relations not previously experienced.

Assemblage and Interpretations of Images from Verbal Input Experimentalevidenceoffers a similarmessage ofnovelcombinations within images. For example, young adults are mentally able to construct, synthesize,and manipulate the componentsof an image that are described to them verbally (e.g., Anderson & Helstrup, in press, this volume; Denis & Cocude, 1989;Finkey1990, this volume; Finke, Pinker, & Farah, 1989 Finke & Slayton, 1988;Helstrup &Anderson,1991;Intons-Peterson,1981, 1984, this chapter; Klatzky & Thompson, 1975; Roskos-Ewoldsen, 1989, this volume). Finke et al. (1989) asked subjects to mentally combine and manipulate alphanumeric characters and geometric shapes to form an object defined by the experimenters. Their imagers were able to discover the experimenters’ pre-experimentally determined forms. Strictly speaking,these researcherswere documenting the contributionof imagery to the discovery of forms because the tasks were to identi@predetermined recognizable (i.e., nameable) shapes. In this research, subjects usually hear phrases or sentences that describe the components to be included in the image. Mental rotation or other transformations also may be specified by the experimenter. Subjects are able to identi@ the target image correctly from a set of alternatives or to draw the target accurately. Roskos-Ewoldsen moved toward the detection of both predetermined and emergent forms in her dissertation (1989; also see her chapter in this volume). She found that her observers were able to detect some novel combinations when figures had been imaginally constructed. These abilities also can be harnessed to produce useful, nameable objects (Finke, 1990,this volume)or recognizableobjects (Finke & Slayton, 1988). For example, Finke and Slayton’sundergraduates, unselected for intelligencetest performance or other abilities, were told to combine three components, drawn randomly from a set of 15 forms (circle, square, triangle, rectangle, horizontal line, vertical line, and the alphanumeric characters L, T, C, D,J, 8, X, V, and P), to form and name the object. The objects drawn and their names then were judged for correspondence on a scale from 1 to 5. Those judged to have high drawing-name correspondence (scores of 4 or 5) also were classified as creative or not. Finke and Slayton found that about 38% had high drawing-name correspondence and of these objects, 16%were judged as creative. These


11

creative patterns were rarely predicted by a naive experimenter or by another group of 70 undergraduates. This latter group even failed to predict many of the creative responses they themselves gave when tested later on the imagery task. Apparently, syntheses emerge from imaginal processes that are not immediatelyobviousfrom a surveyof the component parts. Note a potential definitional problem with this task, however. Subjects were asked to imaginally construct an object that could be identified by a briefverbal description. This task may bias subjectstoward identifying something already known and labelable, a near contradiction in terms for the novelty often assumed to be essential to creativity. Fortunately, ample evidence now shows that navel images often are reported, thereby reducing objections to this aspect of the procedure. For example, Finke and Slayton’s subjects and the participants in my experiment generated items judged novel and creative by independent judges. In addition,Anderson and Helstrup (in press, this volume), using similar procedures,found that their subjects generated as many novel and creative items (again, as judged by independentjudges) when they relied solely on the mental combination of parts as when they were able to augment their mental efforts by being able to draw the combinations. Nonetheless, it seems reasonable to view this work as imaginal discovery, as Finke (1990) does in his book and in his chapter in this book. In his book, Finke (1990) extends these efforts, asking subjects to generate useful objects from three components and to then describethe use of the object. In some cases, subjects generated two-dimensional objects; in other cases, they generated three-dimensional ones. F’inke’s book (and his chapter, this volume) are replete with interesting and creative objects generated by his subjects. In general, the results were similar to those obtained in the Finke-Slayton (1988)research. All of this work provides compelling demonstrations of the abilities of unselected adults to synthesize and manipulate mentally components of images in experimental tasks that assume the use of imagery. Typically, the likelihood of using imagery has not been manipulated, except by using control groups to whom no mention is made of the use of imagery. That is, the technique does not permit evaluation of the frequency of production of objects judged creative as a function of the likelihood of eliciting imagery. It seems reasonable to assume that imagery was used because the subjects needed to translate the verbal labels (names) of the components into a spatial array (image?) of the

12


mental objeds) depicted in the drawings. UsingFinke's general approach as a springboard,Wendi Russell and I hypothesized that if imagery contributes to creativity, creative productions should increase with increases in the likelihood of using imagery, Our approach was to devise a slightly more difficult task which was undertaken in conditions designed to manipulate the induction of imagery. The task consisted of the presentations of four (rather than three) simple componentswhich the subjectswere to combine into a useful object. Three conditions were devised to manipulate the likely use of imagery: picture, printed word, and verbal. In the picture condition, a task that should be least likely to involve imagery, the subjects saw pictures of the components. They could look at these pictures from various perspectives and thus be able to integrate the componentsvisually without having to imagine them. The task should involve more imagery if subjects read the names of the four components, as in the printed word condition. In this condition, subjects would have to rely on the visual system, with which imagery is supposedly closely linked (e.g., Finke, 1990),to read, interpret, and then retrieve the meanings of the names from long-term memory of the components they had to form into an image to perform the task. Similarly, in the verbal condition, where subjects heard the names of the components, as they had in F'inke's (1990)experiments, the subjects would have to interpret the names, retrieve information from long-term memory and convert this information into an image. The verbal condition also conferred the advantage that potential "input interference" from having to look at the stimuli would be reduced; hence, the visual system might be more free to use imagery. Accordingly, we had three maingroups of 20 subjects each. One saw pictures of the components to be combined into a u s e l l object. Another saw the printed names of the components, and the third heard the names of the components. On each trial, the participants were given two geometric figures, sampled randomly from the set (square, triangle, circle, spring, line, and crescent) and two capital letters, sampled randomly from the set (C, K, L, N, S, and V). The two figures and two letters were seen as pictures, as the printed names of the components, or heard as the names of the components. Of course, the printed letters and their pictures are both pictorial, but the two other components differed in these conditions. The subjects were to construct a novel, but potentially usefid object from the four components. ARer they construcM the object,using as much time as they needed, they drew it on a response sheet and then wrote a


13

brief description of its purpose. No drawingwas permitted until they drew the final object. Our predictions were that, if imagery contributes to creativity, subjects in the picture condition should produce fewer creative objects than subjects in the printed word condition, and subjects in the verbal condition should produce the most creative objects. It is possible, however, that subjects need to learn how to cope with thisnovel task. With the threecomponent task, Helstrup and Anderson (1991)found that performance improved from the first to the second block of trials regardless of whether subjects were able to augment their compositionsby drawing. Finke (19901,however, observed no evidence of practice or familiarity effects with his three-component task. To test the possibility of a practice effect over an extended delay, we brought all subjects back to the laboratory two weeks later. The subjects worked on seven problems during the first session and on fourteen,during the second session. Because seven of the problems presented during the second session duplicated the seven problems from the first session, this design enabled us to test subjects with both the same and Merent problems. This approach should indicate whether subjects who devise creative solutions to some problems continue to do so with other problems and whether subjects do or do not produce the same solutions to problems repeated later (but in a new randomized order). As with Finke and Slayton (1988),we had threejudges independently rate the correspondence between the drawings of the objects and their descriptions, using a 5-point scale that ranged from 1 =very poor correspondence to 5 = excellentcorrespondence. Ifa pattern was rated as having high correspondence (rated as 4 or 5), the judge then rated it for creativity on a 5-point scale. Patterns were considered to have high correspondence and to be creative if they were rated as 4 or 5 on both scales by at least two of the three judges. In Session 1, 130 of 420 (7 problems x 60 subjects) or 31%of the opportunities yielded corresponding drawingdescriptions (rated 4 or 5). Presenting the components as pictures produced about the same numbers of recognizable drawingdescriptions (39 of 140 opportunitiesor 27.9%) as printed words (30 of 98 or 30.6%)or as verbally presented words (48 of 140 or 34.3%). Apparently, when subjects first begin thisnovel task, the mode of presentation of the four components does not substantially &ect the percentages of recognizable objects produced. But were the objectsjudged to be creative? Of the 130drawings that

14


corresponded to the descriptions,43 or 33.1% werejudged as creative. The percentages of drawingdescriptionsjudged as creativewas about the same for pictures (12of 39 = 30.8%) as for printed words (15of 43 or 34.9%) and verbally presented words (16 of 48 or 33.3%). Hence, the mode of presentation, which presumably manipulated the level of imagery, did not yield differential numbers of objects judged as recognizable or as creative during Session 1. These results are depicted in Figures 1and 2. Although our subjects seemed to understand the task and to respond reasonably quickly, their drawings during the first session corresponded to the descriptions on only about one-third of the trials. Of these, slightly more than one-third of the productions were considered creative. These relatively low frequencies also were found by Anderson and Helstrup (in press) and by F'inke and Slayton(1988).For example, F'inke and Slayton's subjects produced 38.1% recognizable patterns, of which approximately 15% were considered creative. Thus, this level of productivity may be typical of people unselected for their imaginal or creative abilities on their initial exposure to the task. Let us consider Session 2 responses, obtainedtwo weeks after Session 1. These responses reflect some experience with the task. The Session 2 data were separated into the old and new sets. Overall, the percentages of descriptions that corresponded to the drawings declined from Session 1for both the old and new sets of Session 2. The decline was from 35% on Session 1 to 21.9% (92/420)for old sets and 24.3% (10W420)for new sets on Session 2. All three groups displayed this decline, as shown in Figure 1,but the drop was significant for only printed words. These results suggest that the presence of printed words may have a suppressingeffect, given enough exposure. I will return to the Session 1-Session 2 differences aRer considering our major focus, the effects of likely recruitment of imagery on the number of corresponding productions that were also judged creative. During Session 2, the proportions of productions judged creative increasedreliably as the assumed likelihood of elicitingimagery increased, and this result appeared for both old and new sets. The percentages of creative responses for the presentation groups, in order of assumed elicitation of imagery (picture,printed word, verbal presentation),were 12, 21,and 26 for the old sets and 6,11,and 31 for the new sets. Thus, in Session 2,but not in Session 1, more items were judged creative in conditions designed to elicit more imagery (the printed words and verbal presentation) than the condition expected to elicit less

Imagery$ Role in Creativity and Discovery

15

imagery (the pictures). Three samples of creative responses appear in Figure 3. Another attribute often ascribed t o creativity is its versatility, That is, different images may be created on separate occasions from the same or highly similar components, a concept similar to Anderson and Helstrup's (1989, in press; this volume) "productivity." Versatility was instantiated in the current paradigm by repeating the sets from Session 1 as part of Session 2. The principle of versatility predicts that, even though seven sets were identical on the two sessions, the drawings and descriptions created would vary. That was true, although subjects were told that some sets might duplicate those from Session 1. The percentages of the 140 drawings from Session 2 that were rated as very similar or identical to those from Session 1 were 5.7, 10.7, and 7.9 for the pictures, printed words, and verbal conditions. The comparable percentages of descriptions rated as very similar or identical were 7.1,8.6, and 5.7. ObviousIy, identical components elicited different drawings and descriptions on most of the trials, supporting the principle of versatility. Our subjects were likely t o construct different objects from the same sets of components, and presentation condition had essentially no effect on versatility of the creative output. The next issue focused on individual differences in creativity. Are some people more creative than others? We explored this issue by tallying the numbers of individuals who gave at least one creative response to the seven old items and t o the seven new items on Session 2 as a function of whether they had given at least one response judged creative in Session 1 (see Table 1). These tallies were conducted separately for the three conditions. The pattern was very clear for the picture and printed words groups. At most two of the subjects giving at least one creative response during Session 1 also made a response judged creative during Session 2, whether the patterns were old or new. Thus, for the subjects in the picture and printed words groups, we found no evidence for a transfer effect or for generality of creativity from one set of patterns to another. In contrast, 50% of the subjects in the verbal presentation group who gave creative responses during Session 1 also gave creative responses t o old patterns during Session 2, and 70% gave


16

Proportions of Correspondlng Drawings and Descrlptlor

?

?

? A

0

w

N

?

P I

'Ictu res

Wnted Words

Jerbal

Pictures

Printed Words

Verbal

Pictures

Printed Words

Verbal I

Figure 1 Proportions of drawings rated as corresponding to the descriptions for the three conditions of presentations of sets in Sessions 1and 2. For Session 2, half of the sets repeated Session 1's sets (old) and half were new.

17

Imagery’s Role i n Creativity and Discovery

Proportions of Corresponding Drawings and Descriptions Rated as Creative 0 ~~

0

0

A

ka

~

0

tc

0

i

I

Pictures Printed Words Verbal

Pictures Printed Words Verbal ~~

Pics. Printed Words Verbal

Figure 2 Proportions of drawing descriptions judged as corresponding as highly creative.


18

DescriDtion of I n t e n d e d

Fisure

‘s(

A letter

bubble-blower.

C

T h i s i s a f u t u r i s t i c microphone s t a n d i n which you speak i n t o t h e S t o amplify your v o i c e t h r o u g h t h e V shaped part of t h e device.

-

t h e V i e an antenna p i c k i n g up a n t s i g n a l s , and when it f i n d s o n e t h e C acts as a c l a w and stores them i n the triangle.

A a n t catcher

Figure 3 Samples of drawings of objects.


19

TABLE 1 Numbers of subjects who made a t least one response judged Creative (c) and Not Creative (N). Pictures (N = 20)

Printed Words (N = 20)

Verbal (N = 20)

Session 2 Old

Creative

C

N

C

N

C

N

0

7

2

8

5

5

4

9

2

8

3

7

Session 1 Not Creative

Session 2 New

Creative

C

N

C

N

C

N

2

5

0

10

7

3

0

13

2

8

2

8

Session 1 Not Creative

creative responses to new patterns. These results suggest that the consistency of giving creative responses may be enhanced by use of a condition that fosters imagery, our verbal presentation of words. All subjects were asked, "How did you go about constructing an object from the figures?" The responses generally divided into two categories. The first (imaginal) one involved mentally manipulating the components. The second (perceptual) one consisted of drawing figures and then trying to interpret the drawing. Answers to this question constitute a type of manipulation check. The imaginal strategy was claimed by fewer subjects in the picture condition (27%) than in the printed words (50%) or verbal (54%) conditions, as we had predicted, even though no subjects were told to imagine the components or the objects. In summary, consistent with the view that the use of imagery

20


aids creativity, our evidence suggests that during the second session with the task, imagery-encouraging conditions fostered creative synthesis more than an imagery-neutral condition. This effect required some exposure to emerge, for it was not apparent during the first session. Imagery-encouragingconditions had little differential effect on the numbers of the production of recognizable objects produced during either session. The most reasonable explanation for the absence of an effect on the production of recognizable objects from manipulations of imagery-inducing conditions is that participants in the printed words and verbal conditions had ample time to activate representations of the figural referents of all components in a manner similar to that perceptually available to participants in the picture condition. Now, consider the effect of sessions. There are two issues: Why did the percentage of descriptions corresponding to the drawings decline over the sessions where the percentage of productionsjudged creative increase? We originally proposed that experience with the task would aid generation of corresponding productions. Clearly, that was not the case. The changes in both measures are at odds with the failure of Finke (1990) to find practice effects. There are two major differences between our approach and his. The first is that we used a more difficult (four-component)task; the second is that our sessions were separated by two weeks, whereas no delay was interposed in the Finke (1990) research. The use of a more difficult task cannot be the sole answer because Helstrup and Anderson (1991) found an increase in creative productions from the first to the second half of a single session, even though they used the same kind of three-component task as Finke. The Helstrup and Anderson (1991) results also suggest that the length of the delay is not a critical factor. Consequently, we considered another possibility: Post-experimental reports of the subjects had suggested a motivational explanation. The participants complained that they became bored with the repetitiousness of the task. The two-week delay also may have contributed to a decline in motivation. Our subjects were using experimental participation as one way to fulfill some course requirements, and they may not have been happy about the requirement. This possibility could explain the decline in the generation of corresponding productions. An alternative to this rather uninteresting possibility is that

ImageryS Role in Creativity and Discovery

21

exposure to (and increasing familiarity with) the task suppresses Note that the decline in the generation of performance. corresponding productions from Session 1to Session 2 emerged for the new sets on Session 2, as well as for the old sets. Hence, exposure to or familiarity with the task may function as a suppressor. This explanation can be extended to address the differential effect of sessions on creative synthesis if we assume that the suppressing effect of familiarity is ameliorated by the use of a condition that strongly encourages the use of imagery, such as verbal presentation of the components. The partial release from suppression occurs, we speculate, because the use of imagery facilitates varying combinations of components even within a now familiar task. Specifically, the imagery-encouraging conditions (printed words and especially verbally presented words) appeared to buffer the substantial decline in recognizable and creative objects seen in all conditions during Session 2. This decline was particularly pronounced for the pictorial condition, which presumably required less imagery than the other conditions. These experimental results offer support for the notion that creativity is fostered by taking novel approaches to tasks. Another striking result was the presence of substantial variability both between and within subjects. No subject gave recognizable and creative responses to all sets. Further, the same subjects rarely produced highly similar objects to the same sets presented two weeks apart. This was true, even when subjects claimed to have used imagery systematically. Finally, our subjects appeared to have little difficulty mentally arranging and rearranging independent components. These components could have been easily dissembled because they were not part of a cohesive reference frame (see chapters by Anderson & Helstrup, Finke, Hyman, Kaufmann & Helstrup, Peterson, and Roskos-Ewoldsen in this volume, and Peterson et al., 1992). These results imply that Finke (1990,this volume) has chosen an effective imagery-inducing procedure, one that is likely to yield creative syntheses.

22


Interpretation of Perceptually Ambiguous Images Collectively, the research described above suggests a reasonably facile manipulation of mental images to create or discover novel For example, combinations; other evidence is contradictory. Chambers and Reisberg (1985,1991) have found that images of ambiguous figures cannot be reinterpreted (reconstrued). Their work and related research ask questions about the relation between imagery and sensation-perception. Doubts about the ability of subjects to discover components in their images motivated Reed (1974)to ask whether subjects are able to discern target parts within their images. He found that subjects were not very good at identifying parts of imaginal wholes. For example, in one experiment, subjects saw a pattern for one second, say a Star of David. This was followed by a blank field, and then a test figure that may or may not have been an embedded part (e.g., a triangle or a hexagon) of the original pattern appeared. Subjects judged whether or not the part was in the original pattern. They had no difficulty identifying the entire pattern, but did have problems with some parts. In this experiment, Reed found that 68% of the subjects reported using imagery to perform the task, 12% said that they used both imagery and verbal descriptions, and 20% claimed to use only verbal descriptions. Reed interpreted these results as indicating that images are "structural descriptions," a form of propositions. Additional work also was conducted (see Reed & Johnsen, 1975,for example), but the primary messages were that (a) there was substantial variability in the detection rates of parts of the images and (b) parts were not necessarily "visible" in images in the same way that they are in pictures. The contention that images may differ from perceptual counterparts may extend to reinterpretation processes, as well. For example, certain ambiguous visual forms tend t o reverse as they are viewed. One example is the ducWrabbit figure. Chambers and Reisberg (1985)argued that, if imagery supports the same kinds of processes as perception, reinterpretability should emerge with imaginal ''reversible" forms. That is, the same kinds of components should be discoverable in images as in percepts. In a series of experiments, they tried to obtain imaginal reversals of the ducW rabbit and other classical ambiguous figures. They failed each time.


23

However, when the subjects drew their images of the ambiguous figures, most immediately saw t8hereversed figure. Investigations of auditory images yielded similar results (Reisberg, Smith, Baxter, & Sonenshine, 1989). Peterson et al. (1992; also see Peterson, this volume), offer a reconciliation of Reed's (1974)and of Chambers and Reisberg's (1985) failure to find reconstrual of images and the previous research demonstrating the ability of students to create and manipulate their images mentally. Peterson et al. distinguish between two types of reversal. The first type, reference-frame reversals, entails a change in reference-frame, such as a top-bottom reassignment, in addition to a reconstrual of image components. The second type, reconstrual, refers only to reorderings of the components to form a new interpretation, or reconstrual. They note that reinterpretation of Chambers and Reisberg's ducWrabbit would involve both referenceframe reversals and reconstruals of the components. If, as Finke et al. (1989) suggested, reconstruals in imagery occur more readily than reference-frame reversals, then we would expect imagers to have more difficulty reinterpreting figures whose reversal depends on alterations of the reference frame (e.g., Chambers & Reisberg's duck/ rabbit) than reinterpreting figures whose reversal rests on reorganization of parts (e.g., Finke et al., 1989; Roskos-Ewoldsen, 1989, this volume). These arguments led Peterson et al., (1992) to substitute a familiarization stimulus whose reversal required both alteration of the reference frame and reconstrual of the components (Tinbergen's, 1948, goosehawk figure) for Chambers and Reisberg's Mach book. This substitution was made because the Mach book reversal depends on reference-frame reversal, but not on reconstrual of the interpretation of the components. This modified procedure yielded reference-frame reversals in images of the duckhabbit figure, although these reversals were rare compared to the frequent reconstruals of images. In addition to seeing, and then imagining, the entire duckhabbit stimulus, they also tested conditions in which the observers imaginally constructed the stimulus from "good" parts that were divided by minima in curvature or from "poorll parts that were divided in ways that did not correspond to minima in curvature. The images constructed from good parts were more likely to reverse than those constructed from poor parts.

24


These results suggest that imagery might be differentially sensitive to different kinds of mental manipulations, with imagery being generally more responsive to reconstruals and reinterpretations of parts than to changes in overall organization. Peterson et al. (1992,this volume) propose that, at an early stage, the structural description of a shape is not yet connected to an interpretation. This connection might not yet have been made in the case of recognition, or a new one might not yet have replaced a previous one, in the case of reversal. Shape memory is searched for a best-fitting representation to serve as the interpretation for the structure. Exhaustive searches of representations with similar reference frames precede searches of representations with other reference frames. Matches found in the same reference frames are reconstruals; matches found in other reference frames, occasioned by failures to find matches in the same reference frame, are reference-frame reversals. These search strategies deliver simple reconstruals more often than reference-frame reversals. Although these processes might explain why reconstruals dominate in imagery, they do not explain why reversals of shapes such as the ducWrabbit dominate perception. Peterson et al. (1992, this volume) argue that this difference might be explained by differences between perception and imagery. From this perspective, the details of a figure present during perception might subvert or eclipse reconstruals and direct the search toward representations with different reference frames. Imaginal searches are less likely to be deflected from same-reference-framesets because images contain fewer diverting details. A second explanation is that naming or other verbal directions about processing of visual images may overcome difficulties in interpretation. Hyman and Neisser (1991;also see Hyman,this volume) used a procedure similar to that of Chambers and Reisberg (1985). They reasoned that subjects would be more likely to reinterpret the image if they were asked questions that encouraged them (a) to refocus on the orientation of the image, (b) to make a categorical classification of the image, or (c) both. These questions would induce reinterpretations of the image, thereby allowing imaginal reconstrual. Their data supported this view. These results, and similar ones by Peterson et al. (1992,this volume) are intriguing because they reveal the role language can play in guiding the search


25

of visual images. Language, both that of the experimenter and selfimposed restrictions, can establish powerful expectations for the shape and components of an image. Language also may facilitate overcoming these linguistic strictures, if used adroitly and appropriately to alter initial expectations. Chambers, Hyman, and Kaufmann and Helstrup all use such findings to argue in their chapters that language and description may influence visual depictions. In brief, there can be no doubt that language constrains visual imagery. A third explanation is that the transitory nature of images requires their regeneration for an extended search. There may be time for a search for reconstruals to occur before the images must be refreshed, but not for searches of different reference-frame sets. If the image is not refreshed, for some reason or other, then the opportunity for a more extended search also is lost. Perception presumably is not as restricted under ordinary circumstances which permit viewing until a match is achieved. Of course, limited glimpses of the items might also produce more reconstruals than reference-frame reversals. A somewhat different, but complementary explanation has been offered by Reisberg and his colleagues (Chambers & Reisberg, 1992; Reisberg & Logie, this volume; Reisberg et al., 1989; Smith, Reisberg, & Wilson, 1992). According to their perspective, perceptions arise from actual stimuli and are subject to interpretation and reinterpretation, whereas . . . mental images in any modality have no existence outside our understanding of them, making the image and its comprehension inseparable. In perception, there is a physical stimulus, existing independent of the perceiver, which needs interpretation. However, in imagery, there is no free-standing icon waiting to be interpreted, and no interpretation is needed to learn what the image depicts" (Reisberg et al., 1989, p. 620). Their view is that "pure" auditory images are unambiguous, and the meanings of the images (the interpretations of the images) are immediately clear. Pure auditory images may be "enacted1'by subvocalizing the image. In this case, the auditory image will support more interpretations and yield results more like those of perception. Tests of this view have used both auditory and visual ambiguous stimuli. In the auditory case, traditional switching between, say, "stress" and ''dress" occurred when "stress" was repeated aloud.

26


When imagery subjects subvocalized, their performance approached that of the perceptual (aloud) group, as expected. In the visual case, Chambers and Reisberg (1992) argued that the initial interpretation of an image affects subsequent analyses of that image. For example, with ambiguous images, the initial interpretation may omit information not relevant to the interpretation. If so, imagers would not be able to detect deviations inconsistent with their interpretation. To evaluate this prediction, they asked subjects to imagine the duckhabbit figure while under directions to imagine a duck or a rabbit. Next, the subjects had to identify one of two pictures that most closely resembled their image. The idea was that if the subjects imagined a duck, they would interpret the original figure in terms of "duchess" and generate an image with a clear left side (the duck side of the ducWrabbit figure), or what they called the "duck face." In contrast, if the subjects imagined a rabbit, they would interpret the original figure in terms of "rabbitness" and generate an image with a clear right side (the rabbit side of the figure), or what they called the "rabbit face." The two pictures presented as a two-alternative forced-choice test showed the original figure paired with a figure with variations in either the duck face or the rabbit face. Subjects who had interpreted the figure as a duck and presumably had a clear image of the duck face should be able to correctly identify the original when it was paired with the figure with a slight modification of the duck face. The images of the ''duck'' subjects would be less distinct on the rabbit side. Hence, these subjects should not be able to distinguish between the original and a slight modification of the rabbit side. The opposite results would hold for subjects told to imagine a rabbit, The results supported these predictions, even when the imagers were told to reinterpret their image as a rabbit after having first imagined it as a duck, and vice versa. Apparently, the cognitive interpretations (construal) suggested to the subjects affected their images and their subsequent abilities to compare the original stimulus with a slightly modified one. Chambers and Reisberg conclude that their work demonstrated "that image construal guides what is and what is not included within the image." I agree with the general notion that image construal guides image generation, but not with their argument that their data tell us about what was not included within an image. Selection on a two-


27

alternative forced-choice task informs us that subjects are or are not able to differentiate between the two stimuli. When subjects are not able to differentiate, the task does not indicate why. Chambers and Reisberg postulate that the "backsides" of the images were deficient or even that the information was missing. These interpretations are not warranted. It may be that the subjects had substantial information about both the original stimulus and their images, but they could not distinguish between the two test stimuli. Or they might have forgotten the original and lost the image. In either case, we would expect chance-level performance. This issue becomes important because Chambers and Reisberg try to explain how subjects were able to "fill inttinformation when told to reconstrue the image. Chambers and Reisberg conclude that, as Kosslyn (1980, 1983)proposed, components may be missing from a pixel-like image in working memory that still is available in long-term memory. Before accepting this conclusion, I would want more evidence that items were, in fact, lost. One possibility is to use more complex figures, ones that allow for the inclusion or exclusion of specific components. Some of the reversible figures in Shepard's (1990)book, Mind Sights, are possibilities. Figures with or without specific features then would be presented for yesho identity judgments. This approach should disclose whether and what kind of featural information is lost from the images. Integrating over various findings provides some evidence for Shepard's second contention that the special richness of imagery may facilitate creativity and discovery. When we generate images from scratch, so to speak, by constructing them from individual components, we seem to build images with reference frames, both in the sense that the images are guided by our linguistic concepts and in the sense that the images have specific orientations, outlines, or configurations. Reference frames - the anchors of our perceptual world - appear to constrain our mental gymnastics and, perhaps, our creative discoveries. These topics emerge in most of the chapters in this volume. Specifically, imagery seems t o support more creative responses when unencumbered by simultaneous instructions to use a verbal strategy (Anderson & Helstrup, this volume; Helstrup & Anderson, 1991). Likewise, imaginal search appears to aid internal reorganization of the images (reconstruals; Hyman, this volume;

28


Roskos-Ewoldsen, this volume), particularly when reconstruals are interpreted literally (Kaufmann & Helstrup; Peterson, this volume). Imagery and its kin, pictures and diagrams, may foster efficient computations (Reed, this volume). Finally, images foster rich creative productions (Anderson & Helstrup, Finke, Intons-Peterson, all this volume) that exceed those sponsored by pictures or printed words, given some experience with the task as I described earlier in this chapter. Evolutionary and Developmental Precedence of Imagery over Language The use of spatial imagery or spatial knowledge to guide purposive, unimpeded locomotion has been noted by Mandler (1983). These investigators note that the ability to use spatial knowledge precedes language development (see Anderson & Helstrup, this volume). Similarly, monkeys respond to mental rotation in ways that resemble those of humans, although they do not speak in the usual sense (Georgopoulos, Lurito, Petrides, Schwartz, & Massey, 1989; also see chapter by Reisberg & Logie, this volume). This limited evidence supports Shepard's claim for imaginal precedence over language. The problem is obvious: These studies are handicapped by an inability to assess language in preverbal children and nonhuman animals. Motivational Aspects of Imagery Shepard argues that images are more likely to engage affective and motivational systems than verbal productions. This may well be true for creations in the arts and related fields, but evidence from psychology appears to be limited to two experiments. One experiment, the work I reported earlier in the chapter, suggested that boredom with spaced practice reduced the number of objects generated from four components, but this suppression was partly alleviated when the mode of presentation of the components encouraged the use of imagery. In other words, exposure to the task may suppress creative integration, unless countered by


29

encouragement to use imagery. Perhaps creativity is cultivated by adopting novel perspectives, such as those afforded by imaginal manipulations. Although these speculations intrigued us, the research itself, was not designed to investigate the motivational aspects of imagery. Neither was research by David Roskos-Ewoldsen and Jeffrey Franks (personal communication). Nevertheless, their work also suggests that imagery may engage affective systems. Their subjects judged 48 items for ease of imagining. Half of these items (24) then were included among 60 items presented for affective judgment, and the other half were included in another set of 60 items presented for animateness judgments. The items were counterbalanced across subjects. The assumption was that affectivejudgments would trigger affective reactions to the words, but animateness judgments would not. Finally, recognition of all 120 items was tested. Items rated as high in both affect and ease of imagining were recognized significantly more often than items rated as high in affect but less easy to imagine or items rated for animateness, regardless of the ease of imagining. These results do not disclose the underlying mechanisms, nor do they indicate that the subjects actively tried to imagine the items before the items were rated for ease of imagery. These caveats notwithstanding, the results implicate a positive connection between imagery and affect. Hence, this area stands as a challenge for the future.

The Search for Structural Symmetries Shepard's last possibility is that searches for structural similarities and invariances may be helped by visualization. Indeed, Roskos-Ewoldsen(1989,this volume) found that "good"constructions, which often were symmetrical, facilitated detection of emergent patterns. Hyman (this volume) reported that canonical (usually symmetrical) objects were easily reproduced both when the subjects drew them from memory and when the objects were visible, compared to simple or complex asymmetrical objects. The reverse was true when the task was to organize the objects into a single, cohesive whole. In the latter case, complex, asymmetrical objects were the easiest to organize, followed by the simple components, with

30


the canonical ones, the hardest. Reed (1974)also found symmetry to be beneficial. The notion may be extended to natural discontinuities, such as Peterson et ale's (1992,this volume) changes in curvature. The situation is expanded further by Roskos-Ewoldsen's finding of better detection of emergent components when the pattern constructed from components was poor (typicallyasymmetrical) than when the pattern was judged as good (typically symmetrical). The cohesiveness of good or symmetrical patterns may function like a reference frame in imagery, thereby retarding the necessary decomposition of the pattern for the detection of emergent elements.

Individual Differences and Training Images thus seem to play a special role in creativity and discovery, as Shepard surmised. This possibility raises the interesting question of whether the use of images in creative discovery can be taught or is the special province of a few gifted individuals. Evidence from Anderson and Helstrup (in press, this volume), Finke (1990,this volume), Intons-Peterson (this volume), Intons-Peterson and Roskos-Ewoldsen (1989),and Roskos-Ewoldsen (this volume) suggests that normal people can do it. Can they be taught to become more creative? Can creativity be modeled by computer simulation as a form of problem solving, as Simon and his colleagues maintained (Langley,Simon, Bradshaw, & Zytkow, 1987)? In their theory of scientific discovery, Langley et al. construe discovery as problem solving, saying, "A hypothesis that will be central to our inquiry is that the mechanisms of scientific discovery are not peculiar to that activity but can be subsumed as special cases of the general mechanisms of problem solving" (1987,p. 5). They devised computer simulation models of problem solving based on the assumptions that the human brain is an information processor "whose memories hold interrelated symbol structures and whose sensory and motor connections receive encoded symbols from the outside via sensory organs and send encoded symbols to motor organs" (1987,p. 8). In brief, problems are defined as problem spaces, and the task, as goal satisfaction. The solution uses operators (heuristics or algorithms) to search the space. Their treatment of imagery is to


31

assign a form of representation (called pictorial or imaginal) to an ''internal representation when the information it contains appears similar, and similarly organized, to the information in an external picture or diagram, and when the inferences that can be drawn from it rapidly and effortlessly are similar in kind to those that can be drawn immediately from a picture or diagram" (1987, p. 327). The simulation models show promise, but the authors have not yet extended their tests to people, so we cannot really evaluate this approach. It is important to note, however, that Langley et al.'s (1987) definition of imagery seems too narrow to accommodate the kinds of abilities already discussed. In his chapter in this volume, Reed describes another approach to training, the use of an imaginal extension of analogical problem solving to new situations. Bassok and Holyoak (1989)' Gick and Holyoak (19831, Hayes and Simon (1976), Hinsley, Hayes, and Simon (1977))Krueger (19761, Needham and Begg (1991), and Novick (1988) tested transfer from one problem solving situation to other analogous ones. The general finding is that the transferability of the solution has to be made quite obvious, say by repeating it, before subjects transfer appropriately. Given these discouraging results, we cannot be sanguine about the learnability of creativity.

Summary Shepard's insights serve as useful guides to the study of the contribution of imagery to creativity and discovery. To summarize quickly, although Shepard's first conjecture that traditional verbal modes of communication may constrain the use of visualization and imaginal thinking was not addressed directly, Helstrup and Anderson's (1991, see also this volume) data suggest that visual strategies produce more mental discoveries than verbal strategies. Moreover, language may channel the interpretations given to images and impede the detection of alternative views (see review in Reisberg and Logie's chapter, this volume). Taken collectively, the evidence suggests some independence between two types of creativity, one primarily verbal and the other, primarily spatial. Shepard's second and third suggestions were that images may

32


afford more concrete richness than verbal descriptions and that the spatial nature of images renders them particularly amenable to spatial intuition and manipulation. This appears to be true when images are being generated and when their reinterpretation involves simple reorderings or reconstruals of the relations of components. Image reinterpretation is more difficult, however, when overall reference frames must be altered. It may be that creative individuals have faster access to their images, that their images have longer durations, or that they are able to refresh or regenerate images more rapidly than less creative individuals. These characteristics also would affect discovery within images. In a t least partial contradiction to this view were our results and the results of Anderson and Helstrup and Finke (see chapters in this book) that objects judged as creative are produced only some of the time by some of the people and that the production of objects judged creative during one session was essentially independent of the production of objects judged creative during a subsequent session. Nevertheless, despite the decline over a two-week interval in the production of descriptionsjudged to correspond to the drawings, the proportions of responses judged creative increased. We proposed that these results reflect a tendency for familiarity to suppress performance on the task, an effect that may be countered by the use of imagery. Shepard’s fourth characteristic was that vivid mental images may be specially effective in enjoining affective and motivational systems. This tantalizing possibility remains a challenge. Finally, the search for symmetry seems useful, particularly when extended to include natural discontinuities. Its utility may be constrained, however, by the greater difficulty in dissembling and transforming cohesive patterns and those with intact reference frames than less cohesive patterns and those with no reference frames. Challenges remain. Are some people better imagers than others as measured by image production and manipulation, rather than by pencil-and-paper or self-report? Some observerdimagers may process their image generation and memory searches more rapidly than others. These individuals presumably would be faster at gaining access to reference-frame reversals than others, and might be considered as more adept at discovery and, perhaps more creative. This notion implies that people judged creative are faster or more


33

likely to reverse figures than people judged less creative, a notion that has not been tested, to my knowledge. Another possibility is that more rapid discoverers or more creative individuals use strategies to focus their searches on different reference-frame sets earlier than less rapid discoverers or less creative people. This redirection of the searches could occur because the initial search of the same reference-frame set is not exhaustive but, rather, is treated heuristically as an initial, fast scan, which, if not productive, is quickly broadened. Some answers appear in the other chapters in this book. As a final challenge to the authors of these chapters and to our readers, I end with a quotation from Henri Poincark, reproduced from Miller (1974, p. 307): The genesis of mathematical invention is a problem that must inspire the psychologist with the keenest interest. For this is the process in which the human mind seems to borrow least from the exterior world, in which it acts, or appears t o act, only by itself and on itself, so that by studying the process of geometric thought, we may hope to arrive at, what is most essential in the human mind.

References Anderson, R. E., & Helstrup, T. (in press). Visual discovery in mind and on paper. Memory & Cognition. Arieti, S. (1976). Creativity: The magic synthesis. New York: Basic Books. Amheim, R. (1969). Visual thinking. Berkeley: University of California Press. Bassok, M., & Holyoak, K. J. (1989). Interdomain transfer between Journal of isomorphic topics in algebra and physics. Experimental Psychology: Learning, Memory) and Cognition, 15, 153-166. Brandimonte, M. A., Hitch, G. J., & Bishop, D. V. M. (1992). Influence of short-term memory codes on visual image processing: Evidence from image transformation tasks. Journal

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18,157-165. Chambers, D., & Reisberg, D. (1985). Can mental images be ambiguous? Journal of Experimental Psychology: Human Perception and Performance, 11, 317-328. Chambers, D., & Reisberg, D. (1992). What an image depicts depends on what an image means. Cognitive Psychology, 24, 145-174. Denis, M , , & Cocude, M. (1989). Scanning visual images generated from verbal descriptions, European Journal of Cognitive Psychology, 1,293-307. Ernest, C. (1977). Imagery ability and cognition: A critical review. Journal of Mental Imagery, 2 , 181-217. Finke, R. (1990). Creative imagery. Hillsdale, N J Erlbaum Associates. Finke, R. A., Pinker, S., & Farah, M. (1989). Reinterpreting visual patterns in mental imagery. Cognitive Science, 13, 51-78. Finke, R.A.,& Shepard, R. N. (1986). Visual functions of mental imagery. In K. R. Boff, L. Kaufman, & J. P. Thomas (Eds.), Handbook ofperception and human performance (Vol. 2,chapter 37,pp. 1-55). New York: Wiley Interscience. Finke, R. A., & Slayton, K. (1988). Explorations of creative visual synthesis in mental imagery. Memory & Cognition, 16, 252-257. Georgopoulos, A. P., Lurito, J.,Petrides, M., Schwartz, A., & Massey, J. (1989). Mental rotation of the neuronal population vector. Science, 243, 234-236. Ghiselin, B. (1952).The creative process. New York: New American Library. Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical reasoning. Cognitive Psychology, 15, 1-38. Gordon, R. (1949). An investigation into some of the factors that favour the formation of stereotyped images. British Journal of Psychology, 39,156-167. Guilford, J. P. (1967). The nature of human intelligence. New York: Scribner. Hayes, J. R., & Simon, H. A. (1976).Psychological differences among problem isomorphs. In N. Castellan, Jr., D. Pisoni, & G. Potts (Eds.) Cognitive theory, Vol. 2 (pp. 21-41). Hillsdale, NJ:


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Erlbaum Associates. Helstrup, T., & Anderson, R. E. (1991). Imagery in mental construction and decomposition tasks. In R. H. Logie & M. Denis (Eds.), Mental images in human cognition (pp. 229-240). Amsterdam: Elsevier Science. Hilgard, E. R. (1962). Introduction to psychology (3rd ed.). New York: Harcourt, Brace & World. Hinsley, D., Hayes, J. R., & Simon, H. A. (1977). From words to equations. In P. Carpenter, M. A. Just, & P. A. Carpenter (Eds.), Cognitive processes in comprehension (pp. 89-106). Hillsdale, NJ: Erlbaum Associates. Hyman, I. E., Jr., & Neisser, U. (1991). Reconstructing mental images: Problems of method (Emory Cognition Project Report #19). Atlanta, GA: Emory University, Department of Psychology. Intons-Peterson, M. J. (1981). Constructing and using unusual and common images. Journal of Experimental Psychology: Human Learning and Memory, 7,133-144. Intons-Peterson, M. J. (1984). Faces, rabbits, skunks, and ducks: Imaginal comparisons of similar and dissimilar items. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10,699-715. Klatzky, R. L. & Thompson, A. (1975). Integration of features in comparing multifeature stimuli. Perception & Psychophysics, 18,428-432. Kosslyn, S. M. (1980).Image and mind. Cambridge, M A : Harvard University Press. Kosslyn, S. M. (1983). Ghosts in the mind's machine: Creating images and using images in the brain. New York: Norton. Krueger, T. H. (1976). Visual imagery in problem solving and scientific creativity. Derby, CT: Seal Press. Langley, P., Simon, H. A., Bradshaw, G. L., & Zytkow, J. M. (1987). Scientific discovery. Cambridge, MA: MIT Press. Mandler, J. M. (1983). Representation, In P. H. Mussen (Ed.), Handbook of Child Psychology, Vol. 3 (4th ed.) (pp. 420-494). New York Wiley. Marks, D. F. (1973).Visual imagery in the recall of pictures. British Journal of Psychology, 64, 17-24. Miller, A. I. (1984). Imagery in scientific thought: Creating 20th

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century physics. Boston: Birkhauser. Needham, D. R., & Begg, I. M. (1991). Problem-oriented training promotes spontaneous analogical transfer: Memory-oriented training promotes memory for training. Memory & Cognition, 19,543-557. Novick, L. (1988). Analogical transfer, problem similarity, and expertise. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 510-520. Paivio, A. (1986). Mental representations. New York: Oxford University Press. Peterson, M. A., Kihlstrom, J. F., Rose, P. M., & Glisky, A.L. (1992). Mental images can be ambiguous. Memory & Cognition, 20, 107-123. Reed, S . K. (1974). Structural descriptions and the limitations of visual images. Memory & Cognition, 2, 329-336. Reed, S.K.,& Johnsen, J. A. (1975). Detection of parts in patterns and images. Memory & Cognition, 3, 569-575. Reisberg, D., Smith, J. D., Baxter, D. A,, & Sonenshine, M. (1989). "Enactedll auditory images are ambiguous; "Pure" auditory images are not. Quarterly Journal of Experimental Psychology, 41A,619-641. Roe, A. (1951). A study of imagery in research scientists. Journal of Personality, 19, 159-170. Roskos-Ewoldsen, B. (1989). Detecting emergent structures of imaginal patterns: The influence of imaginal and perceptual organization. Unpublished doctoral dissertation, Indiana University, Bloomington, IN. Shaw, G. A., & DeMers, S. T. (1986).The relationship of imagery to originality, flexibility and fluency in creative thinking. Journal of Mental Imagery, 10, 65-74. Shaw, G. A., & DeMers, S. T. (1986-87). Relationships between imagery and creativity in high-IQ children. Imagination, Cognition, and Personality, 6 , 247-262. Shepard, R. N. (1978).Externalization of mental images and the act of creation. In B. S. Randhawa & W. E. Coffman (Eds.), Visual learning, thinking, and communication (pp. 133-189). New York: Academic Press. Shepard, R. N. (1990).Mind sights. New York Freeman. Smith, J. D., Reisberg, D., &Wilson, M. (1992).Subvocalization and


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auditory imagery: Interactions between the inner ear and inner voice. In D. Reisberg (Ed.), Auditory imagery (pp. 95-119). Hillsdale, NJ: Erlbaum Associates. Solso, R. L. (1991). Cognitivepsychology (3rd ed.). Boston: Allyn and Bacon. Tinbergen, N. (1948). The study of instinct. Oxford: Oxford University Press. Torrance, E. (1966). Torrunce tests of creative thinking: Norms and technical manual. Princeton, NJ: Personnel Press. Wallas, G. (1926). The art of thought. New York: Harcourt Brace.

Acknowledgment

I wish to thank Wendi Russell and Dana Berey for their assistance with the experiment reported herein, and Rita E. Anderson and Beverly Roskos-Ewoldsen for their splendid editorial critiques, challenges, and encouragement.

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Imagery, Creativity, and Discovery: A Cognitive Pcrspectivc B. Koskos-Ewoldson, M.J. Intons-Peterson and R.E.Anderson (Editors) 0 1993 Elscvier Science Publishers B.V. All rights rescrved.

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Chapter 2 ~~

~~

THEINSA N D OUTS OF WORKING MEMORY: OVERCOMING THE LIMITSON LEARNING FROM IMAGERY Daniel Reisberg Department of Psychology Reed College Portland, OR 97202 USA

Robert Logie Department of Psychology University of Aberdeen Aberdeen, AB9 2UB,

UK

Boundaries on Learning from Imagery

A large quantity of research documents the communalities between mental images and pictures -in terms of what information images and pictures include, what information they omit, how that information is accessed, and so on. In general, images seem to share many functional properties with pictures, and, crucially for this volume, images seem t o share with pictures the potential for supporting discoveries, or for inspiring inventions, or for leading to problem-solutions. The evidence for this claim comes from several sources. The history of scientific discovery contains many reports of problem solutions suggested by imagery (e.g., Miller, 1986). Likewise, people commonly use imagery to anticipate visual appearance or spatial relations. Most persuasively, there is much laboratory evidence documenting that we c a n glean new, unanticipated information from images (e.g., Finke & Kosslyn, 1980; Finke & Kurtzman, 1981; Pinker & Finke, 1980; Richardson, 1980). Thus it seems obvious that we can and do learn from images, that images can surprise us or instruct us. Yet, in 1985, Chambers and Reisberg reported a robust failure to learn from imagery; taken at face value, their data indicated a sort of discovery that happens

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Daniel Reisberg & Robert Logie

routinely from pictures, but which does not happen with imagery. Concretely, Chambers & Reisberg (1985) showed their subjects drawings of classical ambiguous figures, for example, the ducklrabbit. Subjects were asked to memorize these figures, then the drawing was removed, and subjects were asked to form an image of the figure they had just seen. Subjects were then asked to reinterpret that image if they could (e.g., to find the duck in the rabbit image, or vice versa). To help them in this task, subjects were given a variety of hints and suggestions. Then, if all else failed, they were given a blank piece of paper, asked to draw the form they had just been imaging; they then tried to reinterpret their own drawing. No subjects in these studies were able to reinterpret their images, Subjects routinely succeeded, though, a moment later, in reinterpreting their own drawings. At the very least, these results point to a contrast between images and pictures, with the latter being easily reinterpreted in this procedure, while the former were not. (For a related result, see Hinton, 1979.) But these results pose a puzzle. Given that subjects can learn from imagery, can make discoveries in their images, what went wrong in the Chambers and Reisberg procedure? Why were these subjects not making a (seemingly) simple discovery from their image? To put this question more broadly, why is imagery sometimes capable of supporting discoveries and creativity, while sometimes it is not? What defines the limits on what we can learn from imagery? Several factors are likely to be relevant here. For example, one relatively uninteresting factor will be image complexity. Some discoveries about pictorial information involve very complex pictures or diagrams, and these might be too complex to image clearly. For discoveries of this sort, learning from images would fail, while learning from the appropriate picture might succeed. Or, as a similar example, some discoveries about pictorial information involve subtle nuances of form, and depicting these in an image might strain the limits of image acuity. Again, this would be a case in which learning from images would be difficult, even though learning from the corresponding picture might go smoothly forward. These factors doubtless constrain learning in many circumstances, but there are also deeper limitations on what can be learned from, or discovered within, an image. By way of introducing these, let us review some classic data from perception. A wealth of

The Ins and Outs of Working Memory

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Figure 1 Pictures of the Necker cube and the vasdprofiles figure are neutral with regard to three-dimensional organization, designation of figure and ground, and the like. But these pictures areperceived as having a specific organization, and this organization seems to govern phenomenal appearance, what the shapes will evoke from memory, and so on.

evidence makes it plain that the conscious, phenomenal percept contains much information not present in the retinal image. In Bruner’s (1957,1973) oft-quoted phrase, the percept goes “beyondthe information given’’in many ways. For example, the retinal image of Figure 1A has no three-dimensional organization; the retinal image has no designation of figure and ground, nor is it parsed in any way. The retinal image is simply a pixel pattern, nothing more. But the pattern-as-perceived does have a three-dimensional organization, does have specifications about figure and ground, is, in fact,

42


perceived as having a particular orientation. These specifications about the perceptual organization are all present in the percept, but not in the stimulus. These specifications play important roles in perceiving. They have a strong influence on phenomenal form. They have a strong influence on judgments of similarity and what a shape is seen as resembling. And, thanks to various perceptual linkages, a term due to Hochberg and Peterson (1987),these specifications also govern how other aspects of the stimulus will be perceived. What is crucial for our purposes is that these specifications also govern what can be learned, or discovered, about a perceptual form. Likewise, these specifications govern what a perceptual form is likely to evoke from memory. There are many results pertinent to these claims, but the major evidence is reflected in the standard illustrations of any introductory textbook. For example, consider the form shown in Figure 1B. We can show this form to subjects, and arrange, perhaps via instructions, for subjects to perceive it as a vase. Sometime later, we show the same figure to subjects, but this time we lead them to perceive it as two profiles. Subjects will, in this setup, routinely deny that they have seen the figure before, even though this exact stimulus was under their view just minutes earlier, Apparently, it is not the familiar geometry which governs recognition or discovery, it is instead the geometry-as-understood,in this case, the geometry with a certain specification of figurdground organization. The same is true for orientation. If Figure 2A is shown to subjects, many fail t o recognize the familiar shape of Africa (Kanizsa, 1979;Rock, 1973). This remains true even if subjects tilt their heads by 90 degrees, setting the figure upright. What matters is subjects’ understanding of upright, not retinal position, and when the form is understood as having a top different from Africa’s top, the form is not recognized. A great many results make broadly similar points. In general, what can be gleaned from a percept seems bounded by the half-dozen previously mentioned appearance specifications. These specifications jointly provide a reference frame within which the stimulus geometry is interpreted. (For further discussion of the relevant data, see Reisberg & Chambers, 1991. The reference frame terminology is Peterson’s, although we are using the term in a slightly different


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Figure 2 Perceived orientationgoverns recognitionfor many forms, so that subjects routinely fail to recognize the (perceptuallygiven) sideways map of Africa. Reiaberg & Chambers showed that the same was true in imagery (using a sideways map of Texas);what mattered was subjects' understanding of upright, rather than orientation on the "imagemedium."

manner than she has; cf. Peterson, this volume.) Thus, in these terms, what matters for learning or discovery is the stimulus within its reference frame, and not stimulus geometry per se. If some target or discovery is consistent with stimulus geometry, but not consistent with how the perceiver understands the geometry, learning is unlikely to go forward. As we have seen, numerous results warrant these claims about perception. In addition, Reisberg and Chambers (1991)have argued that similar considerations apply to imagery. (Parallel data, and a closely related conception, can be found in Peterson, this volume.)

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On their proposal, images, like pictures and like percepts, are depictions. That is, images directly represent the layout of the represented material, they preserve proximity and between-part relations, and so on. We regard these points as amply documented in studies of mental rotation, image scanning, and so on (e.g., Kosslyn, 1983; Shepard & Cooper, 1982). At the same time, however, images, like percepts, but unlike pictures, are obligatorily accompanied by a perceptual reference frame and are only understood within this frame. Hence discoveries from images, like discoveries from percepts, are bounded by this reference frame. In imagery, as in perception, one will make discoveries about the depicted form only if the discoveries are compatible with both the depicted geometry and the imager’s specifications about how that geometry is to be understood. Evidence for this claim is detailed in Reisberg and Chambers (1991). The evidence is easy to describe, since the experiments are modeled after the standard textbook demonstrations already mentioned. For example, subjects in one experiment were shown a series of nonsense shapes. After subjects had encoded each shape, they were asked to image it, and then to rotate their image by a specified amount - sometimes 90 degrees clockwise, sometimes 90 degrees counterclockwise, and so on. The tenth figure in the series, presented with no special notice, was the form shown in Figure 2B. Subjects presumably encoded this form as one more nonsense shape, and they were then instructed to imagine the form rotated by 90 degrees, so that they were now contemplating an image of a correctly righted map of Texas. Subjects were then told that this shape resembles a familiar geographic form, and were asked to identify that form. In perceiving this form, subjects presumably understood the side topmost in the drawing a5 being the form’s top. The form was therefore imaged with a reference frame identifying this top. It seems likely that imaged rotation would not change this understanding, on the hypothesis that imaged rotation would, in this regard, be like rotation on the retina (Olson & Bialystok, 1983; Rock, 1973). Thus, after the rotation, the image was isomorphic with Texas (i.e., shares a depiction), but, because of this assignment of orientation, was understood differently. Geometrically, the image and Texas are closely related, but, psychologically, the image has the


45

wrong reference frame, and consequently has a different phenomenal shape than Texas does, does not resemble Texas, and should not call Texas t o mind. Consistent with these claims, no subjects succeeded in discovering Texas in their images. Moments later, though, subjects were asked to draw a picture, based on their image, and more than half of the subjects were able to discover Texas in their own drawings. Again we see a case of learning failing t o occur with imagery, but succeeding from a picture, drawing attention to the functional contrast between these representations. More specifically, though, we here see a case of learning failing to occur despite the fact that subjects are imaging the ttcorrectll geometry. The learning seems to fail simply because subjects understand that geometry in an inappropriate way. There is a problem in interpreting these data, however. Perhaps the Texas form is too complex or too subtle to be imaged clearly. We know that subjects succeeded in memorizing the form their success with their own drawings tells us that. Thus subjects had a reasonably complete, reasonably veridical memory of the test form. But we might still worry about the adequacy of the image itself -whether it is complete enough, or specific enough, to support recognition. Given these concerns, subjects' failure t o discover Texas in their images might reflect a structural limitation on imagery, rather than (as alleged) an influence of the image's reference frame. To rule out this possibility, Reisberg and Chambers ran a second group of subjects, with one change in instructions. Rather than instructing subjects t o imagine the test form rotated by go", subjects were told directly to change their understanding of the form's top. In short, subjects were told directly how to change the image's reference frame. Thus, while the rotate instruction left subjects with an image isomorphic with Texas, but understood differently, the reassign-top instruction should leave subjects with an image both geometrically and psychologically congruent with the Texas outline. Consistent with our claims, many subjects in this latter group did discover Texas in their images. Thus the understanding of the image seems the crucial element in determining success in this task. If one changes the understanding, one changes the result. Reisberg and Chambers (1991) report a variety of other procedures which extend and confirm these claims. (See also

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Peterson, this volume. Reisberg & Chambers, 1991, also provide

Figure 3 Subjects imaging this form often discover the Arabic numeral if given a hint about changing the depiction's reference frame; subjects without this hint do not recognize the numeral.

discussion of several conceptual issues that bear on the generality of these findings.) As an example, subjects in one of the Reisberg and Chambers studies were shown the form in Figure 3, and asked to memorize the shape. Subjects had previously seen (and practiced memorizing) a series of training figures, each composed of the same black forms as the test figure, but in rearranged position. These training figures provided ample opportunity for subjects to learn the shapes of the black forms, and also encouraged subjects to pay special attention to the positions of each black shape. The training figures also served to emphasize the figural importance of the black forms, providing the appropriate set for viewing the test form (i.e., Figure 3).


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Once subjects had imaged the test form, they were asked what familiar object was depicted. For half of the subjects, no further information was provided. The other subjects were told to think of the figure as being the shadow cast by a solid object - in essence changing their understanding of figure and ground relations within the imaged form. The data show the expected pattern. No subjects in the no-hint group discovered the numeral 5 . These subjects were imaging objectively-familiar geometry, but they understood this geometry in the wrong way, and so no discoveries emerged. In contrast, many subjects in the hint group discovered the 5. When the image’s geometry and the image’s reference frame are consistent with those of the target, then discoveries routinely happen. To summarize this section, the Reisberg and Chambers results confirm, once again, that discoveries can be inspired by imagery, that one can find unanticipated forms in one’s own images. Thus images can serve a crucial role in learning and in problem-solving. At the same time, however, there appear to be strong boundaries on the learning and discoveries inspired by images. In a variety of procedures, we have shown that learning from imagery goes forward only if the image and target form share both geometry and reference frame. Learning from imagery does not take place if there is a mismatch between the image an.d target reference frames; this seems true even when subjects are imaging familiar configurations, configurations easily recognized with pictorial (rather than image) presentations.

A Rigid But Fluid Boundary We hasten to add, however, that this boundary on learning from imagery is a peculiar one. On the one side, the boundary seems relatively rigid. In our experiments, no subjects have discovered the target form in their images when the image and target were understood differently. Other studies have not replicated this zerolevel performance, and we will discuss this point in a moment (cf. Hyman, this volume; Kaufmann & Helstrup, this volume; Peterson, this volume). But all studies agree that there is a massive effect in the data. Discoveries from imagery happen almost universally when the discoveries are compatible with the image frame. Discoveries

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from imagery happen with much lower frequency (and, in our studies, never) when they are incompatible with the image frame. This is a strong effect, and it is this that leads us to describe the learning boundary as rigid. At the same time, however, this boundary on learning is easily moved. Subjects' specifications about an image - its figurdground organization, its orientation, and so on - are, after all, the subject's specifications. The specifications are set by the subject, are manifest in how the subject reads or understands his or her own image, and these specifications can be changed by the subject. We know that image specifications can be changed with a little prodding from the experimenter. This is crucial, for example, in the Reisberg and Chambers experiments (e.g., the reassign top experiment). This point is also clear in recent work by Brandimonte and Gerbino (in press), and by Hyman (this volume; Hyman & Neisser, 1991). In both of these latter studies, subjects were specifically instructed to change their understanding of an imaged form (e.g., the duckhabbit figure). Prior to this change (that is, when the image is understood "incorrectly"), discoveries from imagery rarely occurred. Subsequent to this change, discoveries routinely occurred. Peterson (this volume) has obtained similar effects using so called teaching examples as a way of conveying the required change in image specifications. Thus the overall pattern of these results resembles that of the Reisberg and Chambers findings with discoveries governed both by the imaged geometry and by how that geometry is understood, and with new discoveries becoming available once this understanding (the reference frame) is changed, For present purposes, though, these results remind us once again that, with instruction, an image's reference frame is easily open to change. In some ways, this pattern of results is peculiar. After all, nothing prevents a subject from deciding, on his or her own initiative, to change an image's reference frame. These changes would seem quite likely when subjects are specifically urged to explore their images, seeking new forms. Indeed, as we have seen, discoveries from imagery are much more likely if subjects change their image's reference frame. If, however, subjects did redefine their image's reference frame, this would undermine the impact of the experimenter-defined reference frame. As we have seen, though,


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the experimenter-defined reference frame has a huge effect on the data. We conclude, therefore, that these spontaneous redefinitions of the frame are surprisingly infrequent. Of course we need t o be careful here. We know that some subjects do make image discoveries that are incompatible with the image's initial frame (cf. Hyman, this volume; Kaufmann & Helstrup, this volume; Peterson, this volume); we presume that these are the subjects who have spontaneously redefined their own images - i.e., have changed the reference franies on their own, without instruction from the experimenter. But we are struck by how few of these subjects there seem to be. We read this as implying that, despite situational encouragement for this redefinition, subjects are either incapable or inept in this redefinition. That is, with experimenters' instructions, a clear majority of subjects can change their image's reference frame. Without the instructions, only a small minority makes these changes. A number of hypotheses are available for explaining this contrast, but this surely seems an issue in need of further research. It does seem appropriate, though, to sketch one way this research might unfold: Subjects can, of course, change an image's reference frame if they so choose. Moreover, they can change the reference frame in any way they choose: They can (for example) define any side of the form as the form's top; they can define the figure's configuration in depth in any of' a number of ways, and so on. This breadth of options may itself provide something of an obstacle for subjects: Their task suggests to them that a redefinition of the image will be useful, but subjects have no way of knowing which redefinition to choose, from the many that are possible. Conversely, the likelihood of subjects stumbling across the "correct" redefinition (i.e., the one that will lead to the target form) may be small, and this may be the reason why few subjects succeed (without some sort of aid). On this view, then, the duckhabbit or Texas procedures may be special in two senses. Not only clo these procedures require a change in reference frame, they require a specific change, if the sought-after form is to be discovered. Note, however, that one can design tasks without this second requirement - that is, tasks requiring a change in reference frame, but tasks for which any of a number of changes will serve. The implication of our claim is that creative, unexpected

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discoveries will be far more likely in tasks of this latter sort. (Finke & Slayton’s (1988) procedure may provide such a case; likewise the procedure employed by Anderson & Helstrup, this volume.)

Auditory Imagery and the Importance of Stimulus Support To return to our main agenda, we have now argued that learning from images is bounded, but that this boundary can be overcome. All subjects need to do to expand their imagery discoveries is to change the reference frame within which an image is understood. More specifically, subjects need t o understand the image within a reference frame that matches that of the target. Subjects seem easily able to do this with instruction, but do this infrequently without instruction. There is, however, something else subjects can do to escape the boundaries on learning from imagery. They can create a stimulus. In both the Chambers and Reisberg (1985) and Reisberg and Chambers (1991) studies, subjects were able to draw pictures, based on their images, and then t o make discoveries from these pictures that they had not made with the corresponding images. Why is this? We have argued elsewhere that some judgments, by their nature, require stimulus support. That is, these judgments can easily be made about a stimulus, but are not easily made with reference t o a mental representation (e.g., Reisberg, 1987; Reisberg, Wilson, & Smith, 1991). This leads to a question: If a judgment requires stimulus support, does that mean the judgment cannot be made with imagery? Some recent data suggest a surprising answer to this question. Most of the published data on imagery (and virtually all of the data in this volume) concern visual imagery. Yet claims about imagery are often framed broadly - suggesting that these claims should apply to imagery in modalities other than vision. In a recent series of studies, therefore, we set out t o examine whether claims made about visual imagery do in fact generalize to other imagery modalities. An early group of experiments (Reisberg, Smith, Baxter, & Sonenshine, 1989) was modelled after the Chambers and Reisberg (1985) studies, already described. Subjects were acquainted with


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auditory ambiguous figures, and then asked to image one of these figures. Once the image was in place, subjects were then asked whether they could reinterpret this image. As their ambiguous figures, Reisberg et al. exploited the fact that certain words, if repeated over and over aloud, yield a soundstream compatible with more than one segmentation. For example, rapid repetitions of the word life produce a physical soundstream that is fully compatible with segmentations appropriate to repetitions of life or of fly. These repetitions are usually perceived first as one of these words, then the other, then the first, changing in phenomenal form just as the Necker cube or duckhabbit do. This allows us to ask if imagined repetitions produce verbal transformations, just as heard repetitions do. Subjects in these studies were asked to imagine (or, in some conditions, actually heard) a voice repeating the word, stress, over and over. With an actual (perceived) stimulus, 100% of the subjects heard this soundstream transform into repetitions of dress, a construal fully compatible with the acoustical input. However, this transformation was rarely guessed by a control group, making the transformation a relatively clear indication of bonafide perceptual reversals. Subjects who imagined these repetitions often detected the stress-to-dress transformations. This seemed to indicate a sharp contrast with the data from visual imagery, in which subjects have routinely failed to reinterpret their images. However, subjects’ success in reversing auditory images turned out to depend on subvocalization. In one study, subjects were prevented from subvocalizing by having them chew candy, and this dropped reversals (i.e., detections of dress) to the level achieved by guessing subjects (25%). Reversals were also reduced (from 73% to 27%) when subvocalization was blocked by having subjects tightly clamp their jaws shut, firmly press their tongue up against the roof of their mouth, and hold their lips firmly shut. One might worry, though, that these manipulations (chewing, or clamping the mouth shut) do more than block subvocalization. For example, these manipulations might be generally distracting to subjects, and so disrupt performance for this reason. However, we know from various other studies that these manipulations do block covert speech and seem not t o have other effects, such as distracting

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the subjects (see, for example, Baddeley, 1986; Besner, Davies, & Daniels, 1981; Levy, 1971; Murray, 1968; Slowiaczek & Clifton, 1980; Wilding & White, 1985). We conclude, therefore, that the stress/ dress reversals really do depend on subvocalization, and so are blocked by these manipulations that prevent covert speech. But if stresddress reversals depend on subvocalization, what role does the inner speech play? Is the inner speech perhaps providing some kinesthetic cues, crucial for performance? Or is it possible that subjects subvocalize the to-be-imagined event, and then listen with some inner ear to find out what they have themselves produced? To address these questions, subjects in a further experiment were asked to perform this task while hearing an irrelevant message through headphones. This manipulation reduced the number of reversals from 73% to 13%, suggesting that subjects need both the inner voice and the inner ear to perform this task. The implication is that subjects are literally talking to themselves and then listening to this self-produced stimulus. Other studies show this t o be a widespread pattern in auditory imagery. For example, consider the following task (Smith, Reisberg, & Wilson, 1992). Subjects were visually presented with strings such as D 2 R and asked what familiar word or phrase would result if this string were pronounced out loud (detour). Some subjects were asked to perform this task while hearing auditory input through headphones, blocking use of the inner ear. Subjects were instructed to ignore this input, and it was in any event irrelevant to their task. Other subjects read the strings while repeating Tuh-Tuh-Tuhaloud, blocking use of covert speech. A third group of subjects performed with both the irrelevant auditory input and the concurrent articulation task (both inner ear and inner voice disrupted); a fourth group received neither type of interference. The results yielded the same pattern as the stresddress task. When subjects interpreted these strings with no interference (with auditory input absent and subvocalization possible) they were able to decipher 73% of the strings. But, denied the inner ear or inner voice, performance declined to 40% and 21%, respectively, and to 19% with both forms of interference present simultaneously. Again, it seems that subjects perform this task by speaking to themselves, and then listening to hear what they have said. Not all auditory imagery tasks show this pattern, however. For


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example, consider the following tasks. What familiar word would this produce if pronounced aloud: phluim? Or, would these sound alike if pronounced aloud: hejlhedge? These homophone judgments phenomenally seem to draw on auditory imagery and certainly depend on some representation of sound. But these judgments do not require subvocalization - that is, performance is not hurt if use of the inner voice is blocked (e.g., Baddeley & Lewis, 1981;Besner, 1987;Richardson, 1988;Wilding & White, 1985). For the sake of contrast, though, consider this task. Would these rhyme if pronounced aloud: days /maize? This task obviously resembles the homophone task just described. In both cases, subjects are shown a pair of letter strings, and must decide how these would be related, if pronounced aloud. Despite this similarity, the homophone and rhyme tasks yield rather different results. Homophone judgments seem not to depend on subvocalization, and performance is not compromised if subvocalization is blocked. However, the studies just cited also document that rhyme tasks do rely on subvocalization, and so performance in rhyme tasks suffers if subjects are prevented from using the inner voice. An account of this contrast was suggested early on by Besner (19871,and has recently been extended by Reisberg, Wilson and Smith (Reisberg et al., 1991;Smith et al., 1992). More generally, these authors have offered an account of why some judgments about sound seem dependent on subvocalization (and so are disrupted by concurrent articulation), while other judgments are not. We hasten to say that this account is speculative, since relatively few studies bear on this issue directly. Nonetheless, there is a pattern in the available evidence, and the pattern will call our attention back to issues raised earlier in this chapter. In a wide variety of tasks, one must create and then judge some mental representation of sound. For some of these tasks, one needs to do little more than this. That is, one can create these representations of sound as intact units, often drawing on some template, so t o speak, already in memory. One can then judge the representation without any further analysis -without any reparsing or reorganization. This is obviously true, for example, in the homophone judgments, because these require no analysis, only the activation of a single logogen in long-term memory. In cases of this sort, the inner voice seems not to be needed, and one can simply

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draw on pure auditory imagery. Other tasks require that one create a mental representation of sound, and then do some post-assembly operations on this representation - operations that might include segmentation, or some reparsing, or even mere maintenance. Tasks of this sort seem to require the support of the inner voice, and performance is disrupted if use of subvocalization is prevented. This pattern obviously fits with the cases we have described so far. The image reversal task (stress/dress) clearly requires that an auditory image be reparsed, and success in this task requires subvocalization. The D 2 R task likewise requires reorganization of an image, and also requires the inner voice. Similar considerations apply to rhyme tasks. In judging rhyme, one must re-segment the imaged sound, to cut away the word-initial sounds and judge the word-final sounds. Thus it is sensible that rhyme tasks require use of the inner voice. In contrast, homophone tasks require no postassembly analysis -there is no need for reparsing or reorganization. Therefore the inner voice is not required for homophone judgments. Finally, as one more example, findings indicate that concurrent articulation disrupts children’s spelling, even though it does not disrupt their reading (e.g., Kimura & Bryant, 1983). This again fits with the proposed pattern, on the assumption that spelling, but not reading, requires analysis of phonological codes, requires the creation of and then dissection of auditory images. (For further discussion of evidence compatible with these claims, see Besner, 1987; Reisberg et al., 1991; Smith et al., 1992.) This data pattern suggests an important role for subvocalization, and, in addition, this pattern draws us back to our earlier claims about stimulus support. In general, the key seems to be this. Some auditory tasks require judgments that are compatible with one’s initial understanding of a sound, while other tasks require judgments incompatible with this understanding. For tasks of the latter sort, subjects need to set aside their initial understanding to reanalyze or resegment the sound. This is precisely the case in which subjects need something like an actual stimulus, with an existence that is independent of the subjects’ thoughts and understanding. With a stimulus, the subject can take a neutral stance toward the to-be-judged sound, and so make new discoveries, in essence guided by the sound itself, rather than being guided by


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the sound-as-initially-understood. Within this context, subvocalization appears to provide a stimulus, albeit a covert one. In essence, subvocalization allows subjects to create an auditory event, and then to disown it, to hear the event as a stranger might. In this fashion, subvocalization can aid those auditory tasks requiring stimulus support.

The working memory system As we have now seen, many auditory tasks require a partnership between the inner voice and the inner ear, with subjects literally talking to themselves, and then listening to hear what they have pronounced. This partnership may seem familiar to many readers because a similar pattern can be found in the literature on working memory. It seems appropriate, therefore, to review that literature briefly; this will allow us t o make several points including one further advantage that derives from the use of subvocalization. It has long been known that there is a close relation between working memory and some sort of phonological or speech-based coding. For example, subjects in verbal short-term memory tasks frequently err by substituting phonologically similar items for the correct ones. Recall is also reduced if the to-be-remembered (TBR) items are phonologically similar to each other, even with visuallypresented materials (e.g., Baddeley, 1966; Conrad, 1964). These effects are generally attributed to phonological coding of the TBR items. The role of speech-based coding is also demonstrated by the so-called word-length effect, in which memory span for words that can be pronounced quickly is actually somewhat greater than span for slowly-pronounceable words (Baddeley, Thomson, & Buchanan, 1975). To explain these results, Baddeley and others (see, e.g., Baddeley, 1986; Vallar & Baddeley, 1984) describe a cognitive resource called the articulatory rehearsal loop. This loop involves two components, subvocal rehearsal and a phonological store, working in concert. For example, with visual presentation, subvocalization is used to load the TBR materials into the phonological store. The contents of the store decay, but subvocalization can be used to refresh the store’s contents.

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In this manner, one rehearses by talking to oneself, and then listening to hear what one has just said. This cycle can be repeated indefinitely, so that material can be held in working memory for as long as one wishes. However, the capacity of the rehearsal mechanism itself appears to be around 2 seconds' worth of speech, although the time for material to decay completely fiom the phonological store, in the absence of rehearsal, remains to be clarified (see, e.g., Baddeley & Lewis, 1984;Vallar & Baddeley, 1982). This conception of working memory plainly relies on a partnership between the inner ear and inner voice, just as does our conception 'of auditory imagery. Moreover, this conception leads to a number of testable hypotheses about working memory, and these have fared well in the laboratory. In the interests of brevity, we will simply say that this conception does an excellent job of predicting (among other things) when phonological confusions will or will not occur, when the word-length effect will or will not be observed, and so on. Thus we regard the notion of the articulatory loop as well supported by evidence. (Much of the relevant evidence is reviewed in Baddeley, 1986, 1990. For recent reviews, see Baddeley, 1992; Della Sala & Logie, in press; Logie, in press.) We wish to take special note, though, of the advantages conveyed by use of the articulatory loop. Rehearsal via this loop maintains information near-at-hand, serving as a scratch pad for working memory. Crucially, the rehearsal loop provides this function with minimal cost. Bear in mind that rehearsal draws on the speech system, and of course many of the relevant aspects of speech are highly automatized. Thus the central executive of working memory is needed t o initiate rehearsal, but, within the duration of each rehearsal cycle, processing can proceed automatically, freeing the executive to work on other matters. Hence rehearsal becomes an important resource in the support of time-sharing in working memory. Communalities and Contrasts in Auditory and Visual Imagery

It will be useful at this point to summarize the argument so far. A mass of evidence tells us that imagery can inspire discoveries and


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inventions. It also appears that there are boundaries on what can be learned from an image. In particular, discoveries from an image must be compatible both with the actual depiction and with how that depiction is understood. Put differently, images seem to be understood within a reference frame, and discoveries from imagery depend on the image within that frame. This pattern has emerged in studies of both visual imagery and auditory imagery, although the pattern manifests itself in somewhat different ways in the two modalities. This boundary on learning from imagery has a peculiar status. On the one side, the boundary seems relatively rigid. Discoveries from imagery are extraordinarily common when the discoveries are compatible both with the depiction and the reference frame; discoveries are relatively rare when they are incompatible with either depiction or reference frame. At the same time, though, this boundary on learning is readily escaped. Given explicit instructions or other appropriate cues, subjects can change an image’s reference frame, and this changes what can be discovered within the image. Likewise, subjects have the option of externalizing the image, either by drawing a picture (for visual imagery) or speaking aloud (for auditory imagery). The resulting stimulus then exists quite independently of any reference frame, and so can readily be understood within a new reference frame. So far, this summary has emphasized the same points for visual and auditory imagery. But the evidence also indicates a point of divergence between the modalities. In auditory imagery, subjects have the option of creating a covert stimulus, via subvocalization. Thus subjects can make discoveries from (subvocalized) auditory images even though they fail to make the corresponding discoveries from visual images. As a concrete case, consider the various studies of imaged ambiguous figures. The Chambers 8z Reisberg (1985) subjects failed to reinterpret a visual image of an ambiguous figure, and, correspondingly, the Reisberg et al. (1989)subjects failed t o reinterpret a pure image of an auditory ambiguous figure. In both cases, subjects easily reinterpreted the figure once a stimulus was provided (a drawing in the former study and overt speech in the latter). The point of contrast, though, arises when subvocalization was allowed. With access to this covert stimulus, the Reisberg et al.

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subjects were able to reinterpret the auditory image. Thus subvocalization plainly broadens the range of what can be accomplished with auditory imagery. In fact, auditory imagery seems often to rely on subvocalization, and, in particular, to rely on a partnership between inner speech and hearing. Subjects do not need to be coached or instructed in how to use this partnership; it seems instead to be a natural and spontaneous strategy. We have already sketched an account of subvocalization’s role in terms of the stimulus support it provides. It also seems that subvocalization can provide a further advantage. As we have seen, rehearsal in working memory takes advantage of speech to create an efficient and (largely) effortless storage buffer. Thanks to the automaticity of speech production, complex time-sharing becomes possible, as the mere maintenance of information can be done with minimal attention. Given these advantages, then, it is no wonder that subvocalization is a commonly used, spontaneous strategy.

The Possibility of Other Rehearsal Loops Consider exactly what is needed to create a rehearsal loop in working memory. First, one needs a highly efficient efferent channel so that production can be automatized, permitting time-sharing. Second, one needs some coding scheme, so that one’s actions can serve as representations. Finally, this.efferent production must feed into some afferent channel, so that the covert production can be recorded. This feed into an afferent channel is, of course, essential for our claims about stimulus support, and is also needed for working memory rehearsal, to close the rehearsal loop. These three criteria are certainly satisfied by articulatory rehearsal. For this rehearsal, the activity of speech provides the efferent channel (the inner voice), the rules of language provide the coding scheme, and the inner ear provides the relevant afferent channel. But many activities other than speech are entirely automatized; other coding schemes can be located or invented; and, of course, other efferent channels might feed into different afferent channels. Thus it is possible that other rehearsal loops exist, or can be created, in addition to the articulatory loop we have been considering.


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All of this is plainly relevant to our main agenda. We have argued that imagery provides poor support for some discoveries, namely, those discoveries that require a reference frame change. This limitation can be overcome, however, by means of stimulus support. This support is generally provided by external stimuli, but can also be provided by self-created, covert stimuli. In the case of auditory imagery, covert stimulus support is created through subvocalization, creating a covert auditory event. We have now argued that there is nothing unique about this partnership between the inner voice and the inner ear, and other partnerships, other rehearsal loops, may exist. Thus other forms of covert stimuli, and other forms of stimulus support, may be created. This leads us to ask: what about visual imagery? Could visual images, like auditory images, be enacted via some sort of efferent inner scribe, analogous to the inner voice? If such enactment were possible, it would carry real advantages - providing stimulus support for visual judgments requiring this support, and allowing subjects to overcome the apparent limits on visual imagery function. The issue, therefore, is whether such enactment of visual images is possible. The available evidence already indicates that other rehearsal loops can be created, in addition to the standard loop of articulatory rehearsal. For example, evidence suggests that the deaf use a manual form of rehearsal, with the efferent channel in this case being hand movements, and the afferent channel kinesthesis (e.g., Bellugi, Klima, & Siple, 1975;Shand, 1982;see also Campbell, 1992). There also is evidence that the hearing population can be taught to use a different manual system to perform rehearsal (Reisberg, Rappaport, & O’Shaughnessy, 1984). But what about visual imagery, and visual rehearsal? Baddeley has explicitly proposed that a visuomotor buffer provides one of the slave systems used by working memory and has suggested that visual imagery relies on this buffer (Baddeley, 1986; Logie & Baddeley, 1990). What is the structure of this buffer? Does it rely on a partnership between motoric output and some sensory channel, just as articulatory rehearsal seems to? The initial answer to this question would seem to be that visual imagery does not have this structure. That is, visual imagery seems to follow different rules from those for auditory imagery, although, to anticipate the argument t o come, we will argue that the evidence

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for this point is unpersuasive. We spend the remainder of this chapter exploring the suggestion that visual imagery may, under some circumstances, rely on something like an inner scribe. From this base, we will return to the question of what discoveries can, and what discoveries cannot, be made about one’s own visual images.

The Inner Scribe and the Inner Eye We have considered several points of contrast between auditory imagery and visual imagery. For example, auditory images are spontaneously reversible, unless one takes steps to block subvocalization. Visual images seem not to be spontaneously reversible (at least for most subjects), unless one provides subjects with specific hints or cues. So in one case we have reversibility unless one prevents a strategy; in the other case, we have no reversibility (or infrequent reversibility) unless one provides some help. Moreover, the reversal of auditory images seems to rely on stimulus support, and not on specific information about the image’s reference frame. In contrast, instructions about reference frame seem crucial in the visual case. All of this surely makes it look like visual imagery and auditory imagery are governed by different principles. In the same spirit, auditory images seem to function like stimuli, at least when subvocalization is allowed. The point of our discussion earlier in this chapter was that visual images do not function like stimuli, self-produced or otherwise. Again, this would appear to speak against the idea that visual imagery relies on a partnership between an efferent channel and a sensory channel. These arguments do not settle the issue. The arguments indicate that visual images, in some procedures, with some sets of instructions, function rather differently from auditory images. More specifically, the data indicate that, in some procedures, with some instructions, visual images are not accompanied by motoric enactment. We could ask, however, whether visual imagery always shows this pattern. What we really need to ask, therefore, is whether visual imagery euer draws on motoric support, with the functional benefits that we have proposed. We turn now to evidence that may bear on these questions. It


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will be useful in what follows to distinguish several claims. First, we will argue that there is more than one species of visual imagery; these various forms can be distinguished both functionally and neurally. Second, we will argue that one species of visual imagery is more properly considered spatiaVmotoric imagery, not visual. For imagery of this sort, one images by planning, or mapping out, a series of possible movements; there may be little involvement in this case from visual mechanisms or the inner eye. Finally, we will discuss whether this motoric imagery can produce a covert stimulus which then feeds into the channels of vision. It is this last claim, of course, which is directly pertinent to our earlier suggestions about a partnership in visual imagery between an inner scribe and inner eye.

Motoric Influences on Visual Imagery

A variety of research paradigms are interpreted as reflecting the properties of visual imagery, including chronometric studies of image scanning, studies of imagery mnemonics, studies of various sensory effects produced by imagery, and so on. We do not quarrel with the claim that imagery is indeed involved in these various paradigms; the issue, though, is whether the same imagery is involved in each case. As we see it, there has been an unspoken, and unexamined, assumption made by many imagery researchers, namely that visual imagery is one thing, manifesting itself in slightly different ways in a wide range of phenomena. We see no reason to credit this assumption. To the contrary, a number of considerations speak in favor of distinguishing various species of this imagery. For example, some imagery effects seem truly visual in nature, and may literally involve mechanisms within the visual system (e.g., Finke, 1989). Other imagery effects seem more spatial in their character, and may not draw on the visual system in any way (see, for example, Baddeley & Lieberman, 1980; Carpenter & Eisenberg, 1978; Farah, Hammond, Levine, & Calvanio, 1988; Jonides, Kahn, & Rozin, 1975; Kerr, 1983; Logie & Marchetti, 1991; Marmor & Zaback, 1976; Paivio & Okovita, 1971; Zimler & Keenan, 1983). Likewise, some imagery phenomena are predictively linked to imagery self-report, whereas others are not (e.g., Dean & Morris, 1991; Heuer, Fischman, & Reisberg, 1986;

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Reisberg & Leak, 1987). Neuropsychological data also imply that we may need a fractionation of visual imagery (e,g., Della Sala & Logie, in press; Farah et al., 1988; Kosslyn, 1991). Thus, the domain of visual imagery may be internally diverse, and we may be misled if we fail to distinguish the various species of imagery. In addition, and crucially for our purposes, the data suggest that at least some sorts of visual imagery draw on motoric enactment, suggesting a possible role for the (hypothesized) inner scribe. The relevant evidence, once again, derives from the literature on working memory. One widely used paradigm in visual working memory is to study the temporary retention of visual patterns. For example, subjects might be instructed to visualize a grid, and then to place, mentally, to-be-remembered items within the grid. (“In the lower-left corner, place a J. One square to the right, place a K , , . I’ and so on - after Brooks, 1968.) Retention of this sort of material is disrupted if subjects are simultaneously required to make arm movements that involve following a moving target (Baddeley & Lieberman, 1980). The concurrent movement task has little effect, though, on retention of similarly structured verbal material. Moreover, retention of the spatial material is unaffected by a concurrent brightness judgment task, which presumably involves visual rather than spatial processing. This pattern of data seems to imply that the matrix is retained via some sort of spatiallmovement code, rather than by a visual code. A number of other studies (Logie & Marchetti, 1991; Morris, 1987; Quinn, 1988, 1991; Quinn & Ralston, 1986; Smyth & Pendleton, 1989) also have reported evidence for a link between the control of movement and temporary memory for spatial material. Other results show a different pattern. For example, Logie (1986) required his subjects to retain information by means of a visual mnemonic, and were disrupted by a concurrent visual task (concurrent presentation of irrelevant patterns). Similar findings have been reported by Johnson (1982), and by Matthews (1983). Phillips and his colleagues have also demonstrated that subjects can retain static visual patterns (e.g., Phillips & Christie, 1977; see also Logie, Zucco, & Baddeley, 1990). This seems to imply that visuospatial working memory can deal with visual, as well as spatiall movement, information. Could it be that working memory contains two separate components, one specialized for visual information, one for spatial/


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movement information? Some evidence suggests that this is the case (see also Logie, 1989, 1991). Logie and Marchetti (1991) asked their subjects to remember either static visual images, or a sequence of movements. In the former condition, subjects had to retain a static array of color patches. Performance in this condition was disrupted by presentation, during the retention interval, of a series of irrelevant pictures. There was no memory disruption associated with performance of an unrelated movement task during the retention interval. When subjects were asked to remember the spatial sequence in which a series of color patches was presented, however, the reverse pattern of disruption was observed: Interpolated arm movement disrupted memory for this sequence, whereas interpolated, irrelevant pictures did not. A related pattern was observed by Hadden (1991). In a study of individual differences, Hadden discovered that memory for an object’s color was correlated with subjects’ self-reported imagery vividness, but memory for the object’s size was not. Conversely, memory for size was correlated with a psychometric assessment of spatial skill, but memory for color was not. This kind of crossover interaction, in the Hadden data or those reported by Logie and Marchetti, seems to provide an experimental double dissociation between a system that can retain static visual images, and a system that can retain a series of spatial displacements. Similar distinctions - between visual and spatidmotoric representations -can be found within the visual imagery literature. For example, Engelkamp (1986, 1991) and others (e.g., Saltz and Donnenwerth-Nolan, 1981) have shown that images that are enacted are better remembered than those that are not. Engelkamp documents that asking subjects to mime the act of smoking a pipe, or even to imagine miming this act, leads to better memory retention than asking subjects to imagine a static image of someone smoking a pipe. That is, images which are enacted are remembered better than images which are not. One last line of research also speaks to our theme. Studies of movement control reveal many points of overlap between the mental representations of movement, and mental representations of spatial position. As an initial observation, note that the parietal cortex is plainly implicated in the control of movement (e.g., Georgopoulos, Kalaska, Caminiti, & Massey, 1982,19831,and is also responsible for

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determining where an object is relative to the body (Anderson, Essick, & Siegel, 1987; Butters, Barton, & Brody, 1970). Georgopoulos and his colleagues have, in fact, documented patterns of neural activity in the parietal cortex that precede voluntary movement; the most straightforward reading of this is that the parietal activity instantiates a motor plan, or motor intention, for th.at movement (e.g., Georgopoulos, Lurito, Petrides, Schwartz, & Massey, 1989). Indeed, Georgopoulos et al. have documented mental rotation in this neural activity, plainly linking the study of motor planning with the study of imagery. For example, a monkey in one procedure was shown a visual cue, signalling a direction of motion. The monkey’s task in the relevant trials was to move in a direction 90 degrees counterclockwise from the direction indicated by the cue. Immediately after the cue’s presentation, the neural activity showed a pattern appropriate for motion in line with the cue. The vector of this activity then rotated, as a linear function of time, to the desired direction. In effect, the monkey rotated a motor plan, passing, in an analog fashion, through the directions intermediate between that of the cue and that of the target direction. The parallels are clear between this result and human studies on mental rotation. The suggestion is that, in human mental rotation (Shepard & Cooper, 1982), it is a motor plan being rotated; likewise, in image scanning (e.g., Kosslyn, 1983), subjects are moving a motor intent (perhaps an intent to point) across imagined space. It is interesting to consider the implications of this for specific results within mental rotation or image scanning, but that is not our project here, We simply note that, if this extrapolation is correct, then it may emerge that procedures thought to explore visual imagery are in fact revealing motoric imagery, instead!

A Partnership in Visual Imagery The previous section made two simple points: that the domain of visual imagery is internally diverse, and that one of the species of visual imagery seems, in fact, to be motoric imagery. Although we have not reviewed the evidence here, we note that another species of visual imagery does seem to be more strictly visual - employing pathways within the visual system, and showing many of the


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functional characteristics of vision (see Finke, 1989, for a review). The question now to be asked is the relation among these species. To claim enacted visual imagery, or to claim that the inner scribe feeds information t o the inner eye, we need to ask how (or whether) these various species of imagery interact. Unfortunately, little evidence speaks to this point directly. The best we can do, therefore, is to discuss the plausibility of the partnership idea. Let us return briefly to the articulatory case, i.e., the partnership between inner speech and the inner ear. One might reasonably ask how this partnership came to be -i.e., why evolution has provided us with this link between covert speech and hearing. One plausible suggestion is that this link serves as a feed-forward connection, priming the channels of hearing for upcoming speech. This may provide a means through which the speech produced can be checked for correctness (e.g., Zivin, 1986). This function would be particularly important, for example, in acquiring new spoken vocabulary, because, in this case, the production is not yet automatized, making it crucial that one match the sound of one’s own spoken output with auditory input from another speaker. Consistent with this, young children’s ability to repeat aloud words spoken by an experimenter is closely related to the children’s ability to acquire vocabulary for the first time (e.g., Gathercole & Baddeley, 1989, 1990). Likewise an impairment of the inner ear or inner speech in neuropsychological patients causes considerable difficulty in acquiring foreign language vocabulary (Baddeley,Papagno, & Vallar, 1988; Papagno, Valentine, & Baddeley, 1991). As a related suggestion, this feed-forward, from speech production to audition, might allow the speaker to filter hisher own voice, facilitating attention to other auditory inputs. These various (hypothesized) advantages would not be unique to speech output, nor to hearing. One could imagine that parallel mechanisms might allow one to monitor one’s own movements, to make certain these were faithful to one’s intentions. In addition, we know that, for a number of purposes, these movements must be fed into the visual system. For example, perceivers easily distinguish between image displacement across the retina caused by their own motion, and displacement caused by motion in the environment. To make this distinction, the visual system needs information about motor actions. All of this is consistent with the kind of efferent plus

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afferent partnership we are proposing, with motor plans feeding into the visual system. For the sake of discussion, then, let us assume that an inner scribe does exist, with its (covert) output feeding into the visual system (the inner eye). How would this influence subjects’ performance on imagery tasks? First, note that the inner scribe would not influence a large number of tasks. As we have seen, the stimulus support provided by the scribe would be relevant only t o some species of discovery, and only to some manipulations of one’s own images. But the stimulus support provided by the inner scribe could facilitate many other imagery tasks - namely those requiring a change in the image’s reference frame. For example, some of the discoveries documented by Finke and Slayton (1988) seem to fall in this category. We would expect, therefore, that the rate of creative discoveries documented by Finke and Slayton might increase if subjects were encouraged to enact their images - i.e., to sketch out, with some covert motions, the imaged forms. Correspondingly, it seems possible that some subjects are, on their own initiative, using this enactive strategy, and so creative strategies might be rendered less likely if enactment were prevented. Similar arguments might be applied to reversals of the duck/ rabbit figure. In the Chambers and Reisberg (1985) results, no subjects succeeded in reversing their image of this figure, but several subsequent studies have shown non-zero rates of reversal. We earlier suggested that these success reversals may be due to some subjects’ spontaneous redefinitions of the image’s reference frame, and we have discussed the fact that such redefinitions must be possible, but seem (given the data) to be relatively rare. We can now supplement this suggestion with a further hypothesis, namely, that some subjects may help themselves, with the duckhabbit image, by spontaneously enacting this image (again: covertly sketching out some pattern of motions, providing stimulus support for the visual discovery). With this stimulus support, subjects could set their initial reference frame to the side, and re-perceive the target form, leading to new discoveries. This would be entirely in line with our auditory imagery data, in which subvocalization provided a covert stimulus, capable of supporting discoveries that were not possible with imagery alone. Indeed, this enactment of visual imagery may be more likely


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when other forms of image maintenance (or image support) are ruled out, or made more difficult. For example, Brandimonte and Gerbino (in press; also Brandimonte, Hitch, & Bishop, 1992)have argued that reversals of the ducWrabbit are more likely if subjects are blocked from verbalizing while they are encoding the image. This procedure may deprive subjects of a verbal label for the form, which may in turn make the image more difficult to maintain, which may, finally, encourage subjects to rely on enactment as a means of aiding image maintenance. With the stimulus support then provided by this enactment, subjects might be more likely to reverse this figure. The remarks in the previous few paragraphs are plainly speculative, but are fully consistent with the conception we are offering: We have argued that discoveries from imagery are bounded, in a fairly rigid way, by an image’s reference frame. This boundary can be overcome in either of two ways - either by subjects changing the reference frame (spontaneously or with instruction), or by subjects creating some stimulus support (rendering their original reference frame irrelevant). These are precisely the two hypotheses just offered, concerning subjects’occasional successes in reversing the ducWrabbit figure. Which of these proposals accounts for these successes, however, is a matter for further research. In the meantime, though, these proposals serve to illustrate our discussion of the inner scribe, and, specifically, the role it may play in supporting discoveries from imagery.

Enacted Imagery, Temporary Memory, and Discovery Our discussion has by now covered a lot of ground, and so it seems worthwhile to reiterate the key points. Plainly imagery can inspire creative discoveries, and plainly one can learn new things by contemplating one’s own images. In general, though, these discoveries seem far more likely if they are compatible with the image’s initial reference frame. Discoveries not compatible with an image’s reference frame seem to happen with relatively low frequency, and, in some procedures, not at all. It is this that leads us t o argue that learning from imagery is bounded, i.e., that there are limits on what one can discover from one’s own images. We have argued, however, that these limits on imagery function

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can be escaped through the use of stimulus support. In many circumstances, this stimulus support is provided by self-produced stimuli; these can either be overt - for example, a self-produced picture or sound - or covert, as it is in the case of subvocalization. In general, it appears that subvocalization conveys rather large functional advantages, both in terms of stimulus support and in terms of the time-sharing it makes possible. Nothing in these advantages derives specifically from speech itself, leading us to ask whether these same (or comparable) advantages can be obtained in other ways. In particular, we have asked whether enactment of visual imagery is possible, potentially enlarging the range of what can be learned or discovered from a visual image. In many circumstances, visual imagery seems not to be enacted, and this places bounds on imagery function. Is visual imagery euer enacted? This question is legitimized by the clear diversity within the domain of visual imagery; it seems perfectly possible that some visual imagery is enacted, possibly leading t o novel depictions, and concomitant discoveries, even if other cases of visual imagery are not. The possibility of enactment is further fueled by the fact that some cases of visual imagery rely heavily on motoric imagery. More specifically, it seems that some cases of visual imagery may in fact rely on planning mechanisms within the motor system. We regard the points just listed as well-rooted in data. But all of this still leaves open the question of enacted visual imagery, and, more specifically, the possibility of an inner scribe feeding into the inner eye. In the end, we can argue for the plausibility of this partnership, but plausibility is the best we can do right now. In closing this chapter, we wish to reiterate the crucial importance of all this for imagery discovery, and for creativity. As a concrete case, informal discussions with colleagues in chemistry suggests that a great deal of discovery at the molecular level relies on imagery, specifically, on mental rotation of molecular structures, to see if two structures can fit together or dock to form a new combined structure. This form of discovery seems to require a new understanding of the molecules (of their orientation, of their interrelation), and so seems to require a reference frame switch. Thus, on our account, some form of enactment of the image seems likely to promote such discoveries. We have offered similar words about the discoveries documented in the laboratory by Finke and


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Slayton. Finally, at a more mundane level, even the planning of a novel route around a town may require an enacted image, with the enactment in this case perhaps taking the form of an imagined walk along potential routes! These potential applications present interesting research opportunit,ies,and underscore, once again, the potentially large contribution from image enactment. Thus we end this chapter on a speculative note -we simply do not know if the proposed partnership, enabling enacted visual imagery, exists. We have indulged ourselves in this speculation, though, because we believe it leads into important and uncharted territory, and so we would argue that this partnership is an important focus for future research. As we have seen, this research may illuminate the nature of working memory, and also several theoretical issues (e-g., the role of stimulus support, and thus the contrast between mental representations and external stimuli). Above all, this research may illuminate the nature of imagery hnction, and, obviously, the issue of what limits there may be on this function. We believe that our exploration of these issues, within this chapter, has already clarified these points to some degree, and has, in fact, led us to new questions about imagery, about working memory, and about creativity. We believe that further exploration along these lines will continue to enrich our understanding of these domains.

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Imagery, Creativity, and Discovery: A Cognitive Pcrspective

B. Roskos-Ewoidson. M.J.Intons-Petersonand R.E. Anderson (Editors) 8 1993 Elsevier Science Publishers B.V. All rights reserved.

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Chanter 3

BOTH DEPICTIVE AND DESCRIPTIVE IMAGES ARE

Deborah Chambers Department of Psychology North Dakota State University Fargo, ND 58102 USA Pictures or Propositions How are mental images represented? This question has been extensively debated, with proponents arguing that images are like either pictures or propositions (Kosslyn, 1981; Pylyshyn, 1981). The pictorialists argue that images depict what they represent in an analogue form, whereas the propositionalists argue that images are a description of a scene or object. These two choices have in the past been thought to be mutually exclusive - either images are like pictures or like propositions. One issue at the heart of this distinction is whether mental images have structural properties in common with actual physical objects such as pictures. That is, do mental images depict what they represent? If so, imagers should be able to reconsider their representations and find new interpretations of their images, similar to the way that perceivers find new interpretations of pictures. As can be seen in other chapters in this volume (see chapters by Hyman, Kaufmann & Helstrup, and Peterson), research indicates that imagers can reinterpret their mental images, suggesting that mental images do contain information that is subject to inspection and reconstrual. This similarity between mental images and pictures may make mental images a form of representation that is particularly well suited to creative discovery (see Anderson & Helstrup, this volume, and Finke, this volume).

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The research indicates that mental images share characteristics with physical pictures. But how far can we extend this comparison between images and pictures? At the extreme, we could argue that mental images, like pictures, are raw data structures that must be interpreted for imagers to apprehend their meaning. In this way, interpretations of images stand independently of the structural properties of images (or the depiction of images). However, our research (Chambers & Reisberg, 1992;Reisberg & Chambers, 1991) suggests that this characterization goes too far. We have found that mental images are both depictive like pictures and descriptive like propositions. Further, we find that both the depictive and descriptive properties contribute to what can be discovered from mental images, In fact, our research demonstrates that the descriptive aspects often control what is to be depicted within the image (Chambers & Reisberg, 1992). This chapter will examine the relation between the depictive and descriptive aspects of images.

Images Depict Imagers often claim that entertaining a mental image is just like perceiving a picture in the world. That is, when inspecting a mental image some feel that they are inspecting a representation that retains spatial layout and depth relation among objects, as well as size, color, shape, and texture. This experience of entertaining a mental picture is often so compelling that many imagers responding to Marks’Visual Inventory Questionnaire claim that their images are as clear and vivid as normal percepts (Marks, 1972). Experimental research supports the introspective report that images are similar to pictures. For example, research on mental scanning indicates that when subjects are asked to scan across an image, or rotate an image, zoom in on a n image to inspect detail, or pan back from on to make gross comparisons, their response times were all highly correlated with the time it takes to inspect pictures in the world. (For reviews of this large literature see Kosslyn, 1980, 1983;and Shepard & Cooper, 1982). This research indicates that images, like pictures, preserve the metric properties of space. Images have also been found to function much like pictures. Visual illusions such as prism-induced displacement (Finke, 1979)

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were found to be effective when subject imagined the stimulus situations. Likewise, modality-specific interference effects between imagery and perception suggest that the two may be processed by the same systems (Segal & Fusella, 1970). Clearly, images and pictures are similar in many ways. This similarity is evident in both introspective reports and experimental results. At the same time, there are a number of convincing arguments that images must differ from pictures because images, unlike pictures, are mental representations. Because images are mental representations, whereas pictures are not, they will have properties in common with other representations, such as percepts, that pictures will not have. For example, mental representations are characterized by intentionality; that is, they are meaningful. As Bretano (1874/1973, p. 88) states, “Every mental phenomenon is characterized . . . by what we might call . . . reference t o a content, direction toward an object.” Therefore, at the very least, mental images must be meaningful depictions, describing a specific view of a scene or an object. Pictures, on the other hand, can often be ambiguous as to what they represent. To take an example from Fodor (19751, a picture of a woman with a protruding belly may represent a woman who is pregnant or a woman who is overweight. There is no way from the picture alone to determine what, it is meant to represent. While the picture is ambiguous, a person’s interpretation, or thought about the picture, is clearly one or the other. If images are to serve as a vehicle of thought, they, like percepts and other mental representations, must include meaningful, descriptive information. In other words, images must be determinant representations (Fodor, 1981). Therefore, if an image resembles a picture then it must, at the very least, have a caption that will identify what the image represents.

Images are Meaningful Our own work is a clear demonstration that images are meaningful representations, i.e., descriptive information must accompany depictive information. We have shown that mental images of classical ambiguous figures are very difficult t o reverse

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(Chambers & Reisberg, 1985). In these studies, subjects were asked to create a mental image of an ambiguous figure (such as Jastrow's duckhabbit; see Figure 1). After a brief inspection period, subjects were instructed that the picture they imaged had an alternative interpretation and were asked to inspect their image to discover the new view. Subjects were told that furating on the right or left side of their image would help them make this discovery. If subjects failed they were asked to draw their image on paper and to inspect their drawing for the alternative figure.

Figure 1 Jaatrow's duckhabbit. Test stimulusemployedby Chambers and Reisberg (1986).

All of our subjects failed to find a new figure within their images of ambiguous forms; however, they unanimously discovered the alternative within their drawings. That is, subjects who created an image of the duck of Jastrow's figure were unable to find a rabbit within their image (and vice versa), but were able to discover the rabbit within their drawing. We argue that this descriptive information constrains imaginal discovery (or reinterpretation). Pictures, unlike images, are free of this interpretive information and,


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thus, can easily be reinterpreted. While our data indicated a zero rate of reversal, data collected by Hyman and Neisser (1991)and by Peterson, Kihlstrom, Rose, and Glisky (1992)have both shown approximately a 10% reversal rate (i.e., approximately 2 to 3 successes out of 20 subjects) under similar experimental conditions. Despite the discrepancy, we can safely say that it is very difficult to reverse images of ambiguous figures. These results present a clear difference between images and pictures. Images are clearly influenced by subjects' intentions to image a particular object. When viewing a picture of the duckhabbit figure, subjects are easily able to alternate between construals. However, the same is not true when inspecting a mental image of the figure. It appears that subjects' intentions limit what they can discover from their images. At first glance, the Chambers and Reisberg (1985)results appear to argue that subjects cannot discover a new form by inspecting their mental images. However, the imagery literature quite persuasively argues against this interpretation. In fact, there is evidence that subjects can inspect their images and discover new relations that were not anticipated at the time of the image's creation. For example, we can inspect our images and discover what a three-dimensional scene might look like from another viewing perspective (Pinker & Finke, 1980). We can also reorganize two letters of the alphabet and discover new shapes (Finke, Pinker, & Farah, 1989). Subjects who were instructed to image a "D" rotated counterclockwise by 90" and place a "J"in the middle of its spine often reported that their image resembled an umbrella. In addition, imagers can create objects that were originally unanticipated from a group of parts by combining and arranging them in imagery (Anderson & Helstrup, this volume; Finke, this volume; Finke & Slayton, 1988). For example, imagers might create a television from a square, a circle, and the letter V). These data demonstrate that subjects can make discoveries from their images, but the Chambers and Reisberg (1985)findings indicate that what can be discovered is limited by subjects' intentions to create an image of a particular object.

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Deborah Chambers Constraints on Image Discovery

In searching for possible factors that might act to constrain image discovery, we turned to the perception literature. We reasoned that factors which contribute to the overall appearance of the object (i.e., our percepts of an object, which includes both descriptive and depictive information) may act to limit what can be discovered from an image, because visual images, by their very nature, represent the appearance of an object or scene (Reisberg & Chambers, 1991). For example, Rock (1973) has demonstrated that the way a perceiver specifies the orientation of an object contributes to the appearance of that object. Rock made this point by demonstrating that subjects often fail to recognize that Figure 2 is a drawing of Africa rotated 90" counterclockwise. Similarly, we have found that how imagers designate the top of an image limits what they can discover from their images (Reisberg & Chambers, 1991). In our experiments, subjects imaging Figure 3 were unable to discover Texas, even when they imagined rotating it 90" clockwise, which places it in its usual upright orientation. In sharp contrast, we found a dramatic reversal of our results after we altered the instructions. When we asked subjects to change their specification of the top of the figure (i.e., change how they understood the top), approximately half of our subjects were able to identify the Lone Star State from their image of the initially unidentifiable figure. Thus, how the imager specifies the top of the image appears to control what can be discovered from an image. Both Hyman and Neisser (1991) and Peterson et al. (1992) have found that even ambiguous figures, like the ducklrabbit, could be reversed in imagery if subjects were given clues leading them to change their understanding of the front and back of their images. Reisberg and Chambers (1991) found similar results when they manipulated imagers' understanding of the figure-ground relation within their images. The Reisberg and Chambers studies (1991) make it clear that image discovery is not entirely based on the pictorial (or depictive) properties of an image; rather, learning depends on both the depictive and the descriptive properties. If either of these aspects is incongruent with a particular representation, as in the case of the rotated Texas, the image simply represents some other object - in


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Figure 2 Africa rotated 90" counterclockwise. After Rock (1973).

this case, an unidentifiable blob. It is obvious that if the depictive properties of our test figure were different (e.g., if the figure had a different shape) it would not resemble Texas. It is also true that if the perceiver (or the imager) attributes a different orientation or figure-ground relationship to the figure it would not appear to look like Texas. In other words, a percept "goes beyond the information given" by virtue of specifying a figure-ground organization for the perceived form, an orientation, a configuration in depth, and so forth. This specifying information is critical to what the percept will represent, what it will resemble, and what it will evoke from memory. The Reisberg and Chambers (1991) data make it clear that the same is true for images. (For a detailed discussion of these data, see Reisberg & Chambers, 1991). The essential claim being made here is that one's understanding

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Figure 3 Texas rotated 90"counterclockwise. After Reisberg and Chambers (1991).

of an image places boundaries on what one can discover from an image. Imagers' intentions to imagine, for example a duck, will lead them to create an image with a particular set of specifications, including figure-ground and depth relations, as well as a particular orientation (or, in Peterson's language, a particular reference frame; see Peterson chapter, this volume). These specifications will shape what the image resembles. Assuming that learning from images is based on appearance information, these specifications will also limit what can be learned from an image.


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What is the Relationship Between the Depictive and Descriptive Aspects of Images? The previously described data tell us that images contain both depictive and descriptive information. Subjects’ success in recognizing forms in their image (with a change in the specifications of their images) attests to the fact that images do retain appearance information. Likewise, the failure to recognize an imaged form when it is accompanied by incorrect specifications attests to the fact that the descriptive information is critical. But what is the relationship between the descriptive and the depictive information? It is possible that the depictive and descriptive information exist independently, much like a picture and its caption. If the two are independent, altering one will not necessarily lead to the alteration of the other, although it will change how imagers understand their images. Alternatively, the depictive and descriptive information might be combined in a unified representation, such as a structural description. In this case, a change in the descriptive information would also lead to a change in the depictive information. Again, the perception literature gave us some clues as to the type of interaction we might expect. Tsal and Kolbet (1985) demonstrated that when entertaining a picture of the duckhabbit figure, a change in construal causes a corresponding change in the focus of attention. That is, Tsal and Kolbet demonstrated that when subjects are viewing the duckhabbit figure, attention (measured by increased sensitivity to detect a probe) is deployed to the area that corresponds to the perceiver’s designation of the face of the animal. They demonstrated that when subjects were fixating on the right side of the figure they were more likely to perceive a rabbit, and if they fEated on the left they were more likely to perceive a duck. If imagery operates like perception, we can expect that imagers, like perceivers, would be more likely to attend to areas of their image that represent the face of the intended animal. Based on studies of performance with imagery tasks, Kosslyn (1980,1983) has argued that attention plays a role in maintaining an image. Kosslyn has argued that images begin to fade as soon as they are constructed, but that one can maintain the image by a refreshing process linked to mental scanning or attention. Further, Kosslyn

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argues that the resources needed for this refreshing process are limited; therefore, if the image is large, or complex, only some parts of the image can be represented at one time. This leads to the possibility that images do not include all aspects of the form they were meant to represent; i.e., images are vague about some aspects of their depiction. Given Tsal and Kolbet's results concerning attention, it seems quite likely that what is included in the image and what is allowed to fade is influenced by imagers' intentions. In this way, the description would actually be shaping the depiction.

Images are Vague We are not the first to suggest that images can be vague about some aspects of their depiction. Based on introspective evidence, James (1880/1950), KoMra (cited in Arnheim, 1969) and Titchener (1926) all agreed that images rarely include all aspects of their depiction. For example, KoMra noted that one subject reported imaging a coin with no denomination, another reported imagine a train but was unable to tell whether it was a freight or passenger train. More recently, Slee (1980) has exploited this as a measure of image vividness, asking to what extent an individual's image included aspects that would be critical to a picture of an object. For example, if a subject images a cup placed on a table, does the image include the shape of the table, or its color? Slee has shown that subjects vary on the amount of detail they include in their images. Slee's studies also point to another difference between images and pictures. Slee's subjects often report that their image included details such as the placement of the cup and the box on the table, but failed to include other details such as the shape of the table. Obviously, a picture of this scene could not fail to include the shape of the table, but images can be noncommittal on aspects that are critical t o pictures. Dennett (1981) has argued that this "noncommittal" aspect of images is a factor that clearly distinguishes mental representations (e.g., images and percepts) from physical representations (e.g., pictures and photographs). This evidence converges on findings from perception indicating that percepts, like images, ''are not everywhere dense". For example, Rock, Halper, and Clayton (1972) demonstrated that when we


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perceive objects we are often insensitive to many nuances of complex figures, especially when they do not change the global shape of the figure. They showed subjects a complex nonsense form for a few seconds, then removed the form and immediately presented two alternatives for a forced-choice recognition task. One of the alternatives was the original figure. The other test figure shared the global shape of the original figure, but differed in a small nuance of one section of the contour. Recognition performance was a chance levels, despite the lengthy study time and the zero retention interval. However, when the differing segments of the test figures were isolated, so that they were perceived as figures (rather than details of a larger shape), performance was quite good: subjects easily recognized the previously viewed form. From a somewhat different perspective, Hochberg (1981, 1982) similarly concludes that the "schematic map," which in his view constitutes a form percept, is not "everywhere dense." In several experiments, Hochberg (Hochberg, 1981,1982; Hochberg & Peterson, 1987)has demonstrated that the percept is dominated by "local cues'' within foveal view, and includes only a vague impression of information elsewhere in the form. Again, this argues that the percept does not include all details that are clearly visible within a stimulus, but is selective in important ways. Thus mental representations such as images and percepts are not literal or complete transcriptions of an object, but are instead selective: clear about some aspects of a scene or object, vague and indeterminate about others.

Does the Description Shape the Depiction? We hypothesized that what is depicted in an image and what is left vague depends on subjects' understanding of their images. In part, this understanding includes designations of orientation, figureground, depth relations, and so forth, and it also includes subjects' understanding of what the object is meant t o represent. To test this hypothesis we employed the diickhabbit figure and a paradigm similar to that used by Rock et al. (1972). Given Tsal and Kolbet's data and the arguments that indicate that images do no include all aspects of the imagined object, we

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reasoned that if subjects imaging the duck deploy attention differentially to the left side of the figure, then they probably have a more elaborated image of the duck’s head than the rabbit’s head. Hence, in a recognition test of slightly altered drawings of the ducWrabbit figure, subjects imaging a duck would be more likely to detect errors in the duck’s face, but would have a more difficult time detecting errors in the rabbit’s face. Just the opposite would be expected if subjects construed their image as a rabbit. In our experiments we asked subjects to image the duck or rabbit of Jastrow’s figure, then asked them which of the two pictorially presented shapes better resembled the imaged form. As in the study of Rock et al. (1972)’the test shapes differed only in small nuances of one section of the figure. Again, we hypothesized that imagery subjects, like Tsal and Kolbet’s perception subjects, attend to the area of their images depicting what they consider to be the face of the imaged animal. Consequently, subjects are likely to maintain this area of their images and to allow other areas t o fade. As a result, subjects should have a clear image of the animal’s face, but not a clear image of the rest of the figure. We expected, therefore, that subjects would easily detect departures from the original figure when the departures were located on areas that corresponded to what they considered to be the animal’s face, but do poorly otherwise. Thus, in our task we predicted that subjects imaging the duck would reliably choose the unaltered Jastrow figure if offered a choice between it (Figure 4a) and an alternative differing in the contour of the duck’s face (Figure 4b). (See Chambers & Reisberg, 1991, for a complete description of these studies.) Likewise, subjects imaging the rabbit would choose the unaltered figure if offered a choice between it (Figure 4a) and an alternative differing in the contour of the rabbit’s face (Figure 4c). Conversely, subjects would be less sensitive to the difference between the test stimuli when these differ on the “back”of the animal’s head. In the extreme, subjects would choose randomly between the original and the modified figure in this condition. It is possible that the modifications that we made to our test stimuli altered them in such a way to make them more or less prototypical of a duck or a rabbit. For example, the alterations made to the duck’s bill (Figure 4b) could potentially have produced a more


a)

Figure 4 Test stimuli employed by Chambers and Reisberg (1992): (a)Unmodified figure; (b) modification on the duck’s bill; (c) modification on the rabbit’s nose.

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rabbit-like figure, leading subjects thinking of their image as a duck to choose the original figure merely because it was more duck-like. Likewise, alterations made to the rabbit’s face may have produced a more duck-like figure, again leading subjects thinking of their image as a rabbit to choose the original figure. To investigate this possibility, we showed our figures to subjects who were led to expect either pictures of ducks or rabbits. They were asked to select among a set of test figures the most duck-like or rabbit-like figure. The results of these studies showed that the alterations made to our test stimuli did not significantly alter the prototypicality of the figures (for more details see Chambers & Reisberg, 1992). The main experiments employed a 2x2 design, with subjects either imaging the Jastrow figure as a duck or as a rabbit, then tested with a choice between the original and a stimulus distorted on the rabbit’s face. The results of these experiments were just as we predicted; Figure 5 shows the results from one of these procedures. However, we need to be cautions in interpreting these results. For example, it is possible that our results reflect a bias in perceptual encoding. that is, when subjects were asked to encode the figure they may have simply encoded the nuances of the attended side of the figure and failed to encode the nuances of the unattended side. Therefore, the results may be due to a bias in perceptual encoding, rather than the processes underlying the creation of an image. To eliminate this possibility, we repeated the above experiment with one critical change. After the subjects had encoded the figure and the test stimulus was removed from view, they were instructed that the figure could be viewed as a duck (for those who initially construed the figure as a rabbit). With this direct and explicit instruction, many subjects were able to reconstrue their image. Once this reconstrual was in place, subjects were tested in the same manner as in the above experiment. As shown in Figure 6 , subjects’ discrimination choices were completely predictable from the construal of the image they had in mind at the time of testing, and not from the construal they had in mind when initially viewing (and memorizing) the figure. Apparently, subjects who understood their image as a duck had a clear image of the duck’s face (as reflected in the accurate discrimination with the relevant test pair). However, when subjects changed their construal of the image they allowed this

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Subjects chose between the original figure and one modified on the

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* Duck'sface

1

Rabbit's face

1 Duck

Rabbit

Subject's Image Figure 5 Percent correct recognition. ("Correct" in this case means choosing the original form.) After Chambers and Reisberg (1992, Experiment 2).

portion of their image t o face or degrade, as revealed by their poor performance with the relevant test pair. By the same token, these subjects initially had only a vague image of the back of the duck's head; when the subjects changed their construal, they ''restored" this contour to make this section of the image precise. The data indicate that images, like percepts, can often be vague about some aspects of their depiction. Further, areas of vagueness can be predicted by knowing which construal subjects are imaging.

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Subjects chose between the original figure and one modified on the V

"1

Duck'sface

Rabbit's face

40

Rabbit Subject's Image AT TIME OF TEST Duck

Figure 6 Percent correct recognition. Experiment 4).

After Chambers and Reisberg (1992,

Tsal and Kolbet (1985) have shown that when subjects are viewing the duckhabbit figure as a picture, attention is deployed to the side of the figure that depicts the face of the animal that the subject is perceiving. Similarly, our data indicates that the face of the animal that subjects are imaging is more likely t o be fully articulated in the image than the back of the animal's head.


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Discussion Our results demonstrate the importance of both the depictive and the descriptive aspects of images. Images, like pictures, are depictive in that they represent size, spatial layout, a specific viewing position, and so on. However, images are also descriptive, representing a specific view of a scene or object. This specificity is accomplished by organizational properties such as orientation, figureground relations, unit formation, configuration in depth, and by the aspects of a scene or object that are depicted in the image. It is clear from our data that both the depictive and descriptive aspects of images play a role in what is represented in images and, subsequently, what can be discovered from images. The Reisberg and Chambers (1991) results show that the description is inseparable from the depiction (see Reisberg & Logie, this volume). Subjects who have mentally rotated an imaged form into its usual orientation, but who describe the image as having a different top, simply do not recognize the form even though the rotated form is isomorphic with the target figure. For an image t o remind us of a new object both the description and depiction must be congruent (see Hyman, this volume; Peterson, this volume, Reisberg & Chambers, 1991; and Reisberg & Logie, this volume). In addition, the Chambers and Reisberg (1992) data argue that the descriptive and depictive aspects are interactive. The description appears t o dictate what is to be specified and what is to be left vague in an image. In this way, an image of Jastrow’s duck is simply different from an image of Jastrow’s rabbit, including different specifications of orientation and also depicting different aspects of the form. Therefore, it is not surprising that subjects do not easily reconstrue their images of the ducldrabbit figure because an image of a duck is simply different from an image of a rabbit. This chapter has focused on the limitations of learning from images. By using paradigms that demonstrate both failures and successes in image discovery, we have been able to reveal the importance of both the depictive and descriptive aspects of images. However, this focus on the limitations of image discovery should not overshadow imagers’ ability to learn from their images. Images, like all other forms of thought, can lead us to new ideas. Clearly, many

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of the chapters in this volume demonstrate that images can support creative discovery, Visual images represent the appearance of a scene or object and changes in the appearance specifications may lead imagers t o discover a new object within their images. As discussed above, Finke et al. (1989) demonstrated that through a series of transformations imagers could be led to discover unanticipated objects. For example, take the capital letter "B"and rotate it 90" to the left, place a 'Irldirectly below it, and remove the horizontal line, Many subjects who successfully followed these instructions discovered a heart within their images. Similarly, Hyman (this volume) and Peterson (this volume) demonstrated that a change in subjects' frames of reference led many to reconstrue their images of ambiguous figures. We have shown that the same is true with geographical figures (Reisberg & Chambers, 1991). Further we found that changes in subjects description of their images often led to changes in their imaged depictions (Chambers & Reisberg, 1992). In addition, subjects can create novel objects from a group of distinct parts in imagery (see Anderson & Helstrup, this volume; Finke, this volume). These creations are most likely made by creating new descriptions of the relationship among the parts (i.e., by joining the parts in novel ways, specifying a new frame of reference, and so on). In sum, when imagers alter their descriptions of their images, they will often find unanticipated objects within their imaged depictions. There are several ways of thinking about the relations between the descriptive and depictive aspects of an image. The first possibility is that subjects' understanding of their image is effectively part of the image itself. That is, the depictive and descriptive aspects are represented in a unified representation, such as a structural description. In this way, the depictive and the descriptive aspects are both on the scene, influencing what an image contains, and hence what can be discovered from an image. At the same time, we note that the present data can also be read somewhat differently. Rather than arguing that the construal accompanies (or is a part of) the image, one could claim that the construal of the image directs the creation of the image. Once created, the image could then be represented in some neutral form, perhaps as a pixel pattern within an imagery buffer much like that hypothesized by Kosslyn. This pixel pattern would be influenced by the imager's intentions, such that the pixel pattern created t o be a


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duck image would include different material than one created to be a rabbit image. Nonetheless, the image, with that specific pixel patten, would function much as a stimulus - perhaps realized in some buffer in the visual system, processed through the normal channels of vision, and so on. This claim is consistent with the results of Chambers and Reisberg (1985, 1992). However, it is not clear how it fits the orientation and figure-ground results reported by Reisberg and Chambers (1991). In this work, subjects encoded a geographical figure in a novel orientation. Subjects were then asked either to imagine the form rotated, or to change their ttassignmentttof the image's top. They were then asked if their image reminded them of a familiar form. Many subjects in the "reassign" condition, but none in the "rotate" condition, recognized a new form. This is consistent with the unified representation view because the reassign condition should have led t o a revision in the image's description (i.e., the imagers' specification of top), while the rotate condition should not have (subjects can rotate a farm while maintaining the objectcentered specification of top). However, it is not clear how to understand these results in terms of pixel patterns because presumably both the rotated and reassigned conditions should have led to a new pixel pattern. Hence, we believe the full pattern of evidence favors a unified representation. Nonetheless, this is clearly a point on which further data are needed. These results also have important implications for the picture versus proposition debate. This debate described images as either purely pictorial or purely propositional. It is clear from the current results that neither is true. Images are truly a hybrid between depictions and descriptions.

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ambiguous? Journal of Experimental Psychology: Human Perception and Performance, 11, 317-328. Chambers, D.,& Reisberg, D. (1992). What an image depicts depends on what an image means. Cognitive Psychology, 24, 145-174. Dennett, D. (1981).the nature of images and the introspective trap. In N. Block (Ed.), Imagery (pp. 51-61). Cambridge, MA: MIT Press. Finke, R. A. (1979). The functional equivalence of mental images and errors of movement. Cognitive Science, 13, 51-78. Finke, R. A., Pinker, & Farah, M. (1989). Reinterpreting visual patterns in visual imagery. Cognitive Science, 13, 51-78. Finke, R. A., & Slayton (1988). Explorations of creative visual synthesis in mental imagery. Memory & Cognition, 16, 252-257. Fodor, J. (1975). The language of thought. New York Crowell. Fodor, J. (1981). Imagistic representation. In N. Block (Ed.), Imagery (pp. 63-86). Cambridge, MA: MIT Press. Hochberg, J. (1981).On cognition in perception: Perceptual coupling and unconscious inferences. Cognition, 10,127-134. Hochberg, J. (1982). How big is a stimulus. In J. Beck (Ed.), Organization and representation in perception. Hillsdale, NJ: Erlbaum Associates. Hochberg, J., & Peterson, M. (1987). Piecemeal organization and cognitive components in object perception: Perceptually coupled responses to moving objects. Journal of Experimental Psychology: General, 116, 370-380. Hyman, I. E., & Neisser, U. (1991). Reconstruing mental images: Problems of method (Emory Cognition Report #19). Atlanta, GA: Emory University. James, W. (1880/1950). The principles of psychology. New York: Dover. Kosslyn, S. (1980). Image and mind. Cambridge, MA: Harvard University Press. Kosslyn, S . (1981).The medium and the message in mental imagery: A theory. Psychological Review, 88, 46-66. Kosslyn, S. (1983). Ghosts in the mind’s machine: Creating and using images in the brain. New York Norton. Marks, D. (1972). Individual differences in the vividness of visual

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imagery and their effect on function. In P. Sheehan (Ed.), The function and nature of imagery. New York: Academic Press. Peterson, M., Kihlstrom, J., Rose, P., & Glisky, M. (1992). Mental images can be ambiguous: Parts, wholes, and strategies. Memory & Cognition, 20, 107-223. Pinker, S., & Finke, R. (1980). Emergent two-dimensional patterns in images in depth. Journal of Experimental Psychology: Human Perception and Performance, 6, 244-264. F'ylyshyn, 2.W.(1981).The imagery debate: Analogue media versus tacit knowledge. Psychological Review, 88, 16-45. Reisberg, D., & Chambers, I). (1991). Neither pictures nor propositions: What we can learn from a mental image? Canadian Journal of Psychology, 45,336-352. Rock, I. (1973). Orientation and form. New York: Academic Press. Rock, I,, Halper, F., & Clayton, T. (1972). The perception and recognition o f complex figures. Cognitive Psychology, 3, 655-673. Segal, S. J., & Fusella, V. (1970).Influences of imaged pictures and sounds on detection of visual and auditory signals. Journal of Experimental Psychology, 83, 458-464. Shepard, R. N., & Cooper, L. A. (1982). Mental images and their transformations. Cambridge, M A : MIT Press. Slee, J. (1980). Individual differences in imagery ability and the retrieval of visual appearances. Journal of Mental Imagery, 4 , 93-113. Titchener, E. B. (1926). Lectures on the experimental psychology of the thought-processes. New York: Macmillan. Tsal, Y., & Kolbet, L. (1985).Disambiguating ambiguous figures by Quarterly Journal of Experimental selective attention. Psychology, 37,352-373.


Imagery, Creativity, and Discovery: A Cognitive I’crspective B. Roskos-Ewoldson. M.J.Intons-Peterson and R.E. Andcrson (Editors) 0 1993 Elsevier Science Publishers B.V. All rights reservcd.

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Chapter 4

Imagery, Reconstructive Memory, and Discovery Ira E. H y m n , Jr. Department of Psychology Western Washington University USA I began this mental imagery research in response to a set of experiments that I found unbelievable. Chambers and Reisberg (1985) found that people could not discover the alternative interpretation of an ambiguous figure by using mental imagery. In my original response to that work (Hyman& Neisser, 19911,I was interested in outlining some conditions that would facilitate reversals of ambiguous figures using images. I attempted to frame discovery using mental images as a question of the experimental methods employed, rather than as indicative of the underlying relationship between imagery and vision. In subsequent investigation, I have tried to d.iscern how manipulation of visual information using imagery is similar to other memory tasks, such as the reconstruction of a story. Phrasing the issue of imagery-based discovery in the language of reconstructive memory rather than the language of perception and perceptiodimagery equivalences provides an alternative view of the problem. Chambers and Reisberg (1985)asked people to view a figure, such as the duwrabbit figure, and to form a mental image of the drawing. The subjeds then attempted to discover the alternative interpretation from their mental image of the figure. Not one could do so by examining their mental images, but almost every one could when viewing their own drawing of the figure made after searching their images. This demonstrated that the failure to reinterpret the figure was not due to a lack of information. Chambersand Reisbergclaimed that images could not be reconstrued because mental imagery does not involve construal in the

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first place -- people know what they are visualizing. The only way to discover anything is to imagine a different image. Since the subjects in the Chambers and Reisberg experiments did not know what the other interpretation was, they could not change their mental image. Because I would have expected this to be a reasonably simple task, I was surprised by these results. Apparently, I was not the only person. Chambers and Reisberg (1985) themselves noted that a priori they expected people to be able to do this task. Furthermore, they continued to conduct research in this area and found that under some conditions people could find novel interpretations of mental images (Reisberg& Chambers, 1986,1991). In the midst of a series of meaningless shapes that subjects were to imagine, subjects were shown an outline of the map of Texas rotated 90"counter-clockwise. They did not recognize this form as Texas. When they were asked to rotate their mental image 90" clockwise they still did not recognize the figure. When, however, they were told to make the lef%side the top of the figure and that it was an outline of a familiar geographical form, about half of the subjects discovered Texas. Reisberg and Chambers suggested this was an example of subjects changing their understanding of an image and therefore changing the image itself, by reassigning the top of the form. With the new image, subjects were reminded of something known and this allowed many people to discover the form of Texas, In thisfashion, changing mental images could lead to discoveries through remindings but not through the process of interpretation that is used in vision. Finke, Pinker, and Farah (1989)were also challenged by the original Chambers and Reisberg results. They conducted a series of experiments in which subjects imagined, rotated, combined, and edited simple figures using mental imagery. Their subjects were able to discover new interpretations from their images. Finke and his colleagues argued that images do contain visual idormation that allows interpretation and reinterpretation. They resolved the differences between their results and those of Reisberg and Chambers by suggesting that classical ambiguous figures are unique: To reinterpret an ambiguous figure one must be able to perceive the whole figure at once. Images, however, are composed of dynamically fading and regenerating pieces, and the process of regeneration requires the resources of working memory. Because the whole ambiguous figure must be maintainedfor reconstrual to occur, and because imagery tends to fade and regenerate over time, reinterpreting ambiguous figures is difficult, to say the least. According to Finke et al.,

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I01

the difficulty of maintaining a whole figure for reinterpretation is beyond the limits of working memory. Finke et al.’s argument is interesting because it suggests that the differences between imagery and perception found in discovery studies may be explained by similarities between imagery and another cognitive processmemory. Most models of imagery discuss the reliance of visual imagesupon memoryprocesses. For example,Kosslyn,Pinker, Smith, and Shwartz (1979)stated that images are created from stored information and maintained in a visual buffer (orworking memory). Deterioration of stored information in long term memory causes an image to be less clear and detailed than the original percept. In addition, visual working memory holds a limited amount of information and must constantly be refreshed. Thus some constraints on the imagery system are dictated by memory limitations. Additional limitations on the imagery system, and hence limitations on the ability to make discoveries using imagery, may be due to the process of creating an imagewith a reconstructivememory system. Bartlett (1932) is known for his early studies concerning reconstrudive remembering of verbal material. He asked subjects to recall a short story and then looked at the errors people made, including both omissions and intrusions. He interpreted the pattern of errors as evidence for the influence of general knowledge structures on the recreation of a story. Bartlett referred to these general knowledge structures as schemata. Since Bartlett, there has been a great amount of research conducted on the reconstruction of verbal material (e.g., Bransford & Franks,1971;Hyman & Rubin, 1990;Jenkins, 1974;Kintsch &vanDijk, 1978;Mandler &Johnson, 19771,and, relatedly, on autobiographical memories (e.g., Barclay, 1986; Neisser, 1982). According to Bartlett’s reconstructiveview of memory, the recall of a sbry is guided by story details that are available from memory at the time of recall, story gist, knowledge of events like those described in the story, similar personal experiences, cultural understanding of narrative forms, and general world knowledge. honstructive story recall adds information to fill gaps in the story and in memory, and may also change details to fit with general knowledge structures. Although Bartlett is known primarily for his studies of story memory, he also investigated memory for pictures. In having people describe line drawings offaces, he found evidence of schema-basedreconstruction based on an analysis of both omission and intrusion errors. This finding is particularly interesting because of the claim that mental images are

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similar to pictures (e.g., Kosslyn, 1981). Thus, there is reason to expect that the creation and maintenance of a mental image may involve reconstructive memory. Reconstruction of a visual memory as a mental image, like reconstruction of a story, would be based on visual details available at the time of recall, general visual form, knowledge of objects like the one being imagined, knowledge of the visual world, and cultural understanding of pictorial representation. The reconstructive creation and maintenance of an image should focus on the gist. In the case of images, as opposed to stories, the gist may be the general form. The reconstruction should also overwriteinconsistent details and fillin gaps in the remaininginformation. These additions will conform to the general form and to knowledge of the category of objects or events being imagined. The maintenance of the image will continue to emphasize the general form at the expense of details. Thus one can imagine a house without knowing the number of windows or the color of the trim. The reconstructive view of image construction suggests some constraints on discovery using mental images. Namely, discovering something about the gist or consistent details should be fairly straightforward, discovering something about less important details or something that contradicts the gist should be more difficult. This reconstructive view of imagery led me to two types of experiments. The first line of experiments (Experiments 1 and 2) investigated whether classical ambiguous figures can be reinterpreted using mental imagery (see Hyman & Neisser, 1991, for more detail). Others have also addressed this point (see Chambers, Kaufmann & Helstrup, Peterson, and Reisberg & hgie, all this volume). Our experimentswere modeled on the success of the Reisberg and Chambers (1986,1991) Texas experiment but used the duckhabbit and chefldog figures. We reasoned that subjeds’ images may have been limited by the gist of the figure they were imagining, until they were provided with instruction that allowed subjects to fill in details of the figure.The results of these experiments suggest that a view of image creation as a reconstructive memory task may be productive. The other line of experiments is based on ongoing research that more directly investigates the relation between reconstructivememory and mental imagery. I report one experiment (Experiment 31, conducted with Jeremiah Faries, that explored how the gist and details of visual information are remembered. This second area of research outlines some limitations that the


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reconstructivenature ofrememberingplaces on imagery-guideddiscovery.

Experiment 1 Method

If subjects who imagine one interpretation of the duwrabbit or chefldog figure are bounded, or limited, by the gist of the figure, their image may not include enough detail that is consistent with the alternate construal to be reinterpreted. If, however, subjects are encouraged to fill in detail, they may then be able to discover the other interpretation. Experiment 1was conducted to see if explicit instructions concerning the nature of the alternate construal .makea difference in the reversibility of an imagined figure. The explicit instrudions are assumed to cause the instantiation of additional information, thereby increasing the likelihood of discovering an alternative interpretation. There were two conditions, minimal and full information. Little or no reconshals were expected in the minimal information condition because this condition was similar to Chambers and Reisberg's (19851,and their subjects were not able to reconstrue their images. If'reconstruals are dependent on detail, then our fullinformationinstructions--thosethat encourage instantiationsof detail-should produce reconstruals. Subjects

Forty Emory University undergraduates were tested individually. They were assigned to one of two conditions that varied in the amount of instructions provided to help them reverse their images. Procedures

Subjectswere first familiarizedwith ambiguous figures. They were shown the Necker Cube, the Schroeder staircase, and the vasdfaces figures. Subjects had to indicate that they were able to see both If subjects experienced difficulty seeing both interpretations. interpretations they were provided with clues. Subjects were then told that the next part of the experiment would concern visual memory. They were told that they would be shown a line drawing for five seconds, that

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they should form a mental picture of the line drawing, and that they would later be asked to draw the figure from memory. Subjects were then shown either the ducWrabbit or the chefldog figure.'. Both figures were used for all subjects and order was counterbalanced. Orientation of the chefldog was also counterbalanced. Subjects were instructed to hold the image in their mind and then were asked if they had noticed, during presentation of the figure, that the figurehad two interpretations like the figures they had seen earlier. Data from subjects who said yes were discarded? Subjectswere then told that the figure did indeed have two interpretations and were asked to find the other interpretation. The information provided to subjects varied according to condition.

Minimal Information (n=20): This condition was modeled on the procedure of Chambers and Reisberg (1985). For the duckhabbit figure, subjects were advised that it might help to shift their focus across the image. For the chevdog, subjectswere advised to rotate.the image90"clockwise or counterclockwiseas appropriate with respect to whether the figure had been shown in the dog or chef orientation originally. Full Information (n=20): These subjects were given both orientation and categorical information about the alternative interpretation, modeled on information that was given to the subjects in the Reisberg and Chambers (1986, 1991) Texas experiment. For the duckhabbit figure, subjects were told to consider the back of the head they already "saw"to be the front of the head of a different animal. For the chevdog figure, they were told to rotate their image so that what they %awttas the

'I do not include illustrations of the duckhabbit figure because the figure is included in other chapters within this chapter. 2

About one quarter of the subjects were discarded because of previous familiarity with the duckhabbit figure. This minor problem arose because the duckhabbit figure was included in the text used in the introductory psychology class. However, the experiment was conducted before the figure was encountered in the course, and we were able to collect data from the students who had not looked ahead in the book.


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front would be the bottom of either the head of a man or an animal, as appropriate since the original presentation was counterbalanced to be in either the dog or chef orientation. Subjects succeeded by either naming the alternative interpretation or by providing a reasonable description. In keeping with the approach of Chambersand Reisberg(19851, other interpretationswere accepted-such as whale for dog,if the subject described the back end as appearing like a tail. All subjects were asked to draw the figure and those who had not reversed their mental image were asked to find the other interpretation in their drawing. The other ambiguous figure was then presented and the procedure repeated. Results

Very few of the subjects in the minimal information condition reversed their images, while approximately half of those in the full informationconditiondiscovered the alternativeinterpretation(see Table 1). It is important to note that even in the minimalinformation condition a few subjeds (one of 20 for the chtfldog and two of 20 for the ducklrabbit) were able to reverse their mental images. Although the numbers of successfbl discoveries in the minimal information condition are low, they contrast with the complete failure to reconstrue images shown by Chambers and Reisberg's (1985) subjects.

Experiment 2 The second experiment was a replication and expansion of the first experiment. The full information condition in Experiment 1 provided subjects with guidance concerning both orientation and category membership of the alternative interpretation. "he number of conditions was expanded in Experiment 2 to investigateboth orientation and category information separately as well as in combination. It was expected that providing only one piece of information would lead to a number of reversalsintermediate to the minimal and full information conditions. Because several subjects in Experiment 1were dropped due to familiarity with the duckhabbit figure, only the chefldog figure was used in this

Ira E. Hyman, Jr.

106 experiment.

TABLE 1

The number of subjects who reversed the figures using mental imagery

Ehperiment 1 Figure

Chef 1Dog

Reversed Image?

Yes

No

Yes

No

Minimal

1

19 (8)

2

18 (10)

Fd

8

12 (4)

11

9 (6)

DucklRabbit

Condition:

X2= 5.16, pe.02

Figure

Chef l Dog

Reversed Image?

Yes

No

Minimal

2

20 (5)

Orientation

3

19 (7)

ca%wY

2

20 (10

Full

8

14 (3)

X2 = 7.29,pc.01

Condition:

X2= 7.96,p 18

1

2

1A

2A

10

1c

1E

2c

28

20

2E

Figure 1 Patterns and parts used by Reed and Johnson (1975).

Results showing the limitations of imagery should challenge us to find what constrains our ability to reinterpret images. Recent work reported in this volume (Peterson, this volume; RoskosEwoldsen, this volume) shows how the perceptual characteristics of patterns constrains the discovery of new information. Peterson’s research studied how the processes of shape recognition influence people’s ability to reinterpret ambiguous patterns. She proposed that the ducWrabbit figure might be particularly difficult to reinterpret because it requires a reference frame reversal - the front of the duck is the back of the rabbit. Her subjects were more successful in using an image to reinterpret an ambiguous figure (snail-elephant) that did not require a reference frame reversal. Other investigators have studied how perceptual variables influence the discovery of parts in patterns or images. Roskos-

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Ewoldsen (this volume) proposed that people should be more accurate in detecting parts when the parts have high figural goodness and the patterns have low figural goodness. She reasoned that figurally good patterns are more coherent and are therefore harder to reorganize to discover new information. The results provided partial support of her hypotheses and depended on whether subjects were examining images or perceptual patterns. Good parts enhanced accuracy only for the image group and poor patterns enhanced accuracy only for the perception group. These findings reminded me of a correlational study that Angaran and I did to determine which perceptual variables most strongly correlate with the difficulty of detecting an embedded figure (Reed & Angaran, 1972). One of the best predicting variables was what we called analysis complexity, defined as F + G - P,where F is the complexity of the (embedded) figure, G is the complexity of the ground, and P is the complexity of the (complete) pattern. Our reasoning was that detecting an embedded figure should be difficult to the extent that the complexity of the parts exceeds the complexity of the whole. The correlation between analysis complexity and the time needed to find an embedded figure was .71 for mentally retarded children, .62for children in lower elementary school, .61for children in middle elementary school, and .57 for children in upper elementary school. Discovering new information, in general, may be much more difficult when one has to reorganize information that is already well organized. For instance, Mayer (1983) discussed this topic in the context of Tresselt and Mayzner’s (1966) study on reorganizing anagrams to make words, The letter transition probability (LTP) of anagrams is determined by how frequently pairs of letters occur in the English language. Low LTP anagrams, such as rhtue, consist of successive letter pairs that don’t frequently occur in language. High LTP anagrams, such as ahter, consist of successive latter pairs that do frequently occur. Tresselt and Mayzner (1966)found that poorly organized (low LTP) anagrams were solved much more quickly than well organized (high LTP) anagrams. Notice that organization, in this case, is measured quite differently than the figural goodness of patterns.

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Imagery is Effective but Insufficient A second limitation on using imagery to make new discoveries is that people may be able to effectively use their images to mentally scan patterns or simulate events, but more than imagev is required to discover new information. I shall argue that discovering functional relations between concepts is an example. A typical finctional relation is the relation between time, rate, and distance, Kosslyn, Ball, and Reiser (1978)studied this relation by measuring the time to scan between two objects in a visual image of an island. They found that scanning time was a linear function of the distance between the two objects when subjects imagined a dot moving at a constant rate from one object to another. Kosslyn and his colleagues interpreted this result as evidence that people can accurately scan visual images, but critics have argued that the result could be based on estimated time intervals if subjects have tacit knowledge of how rate and distance influence scanning time (Pylyshyn, 1981). Mitchell and Richman (1980)showed that people do know this relation because their estimated #can times were also linearly related to the distance between two objects. Hock, Lockhead, and I attempted to rule out the tacit knowledge explanation of mental scanning by designing an experiment in which people could not predict the results (Reed, Hock,& Lockhead, 1983). We measured scanning time of line configurations that varied in both length and shape. The shape was either a straight line, a spiral, or a maze consisting of lines meeting at right angles. Subjects in the perception condition were told to scan a pattern projected on a screen, and subjects in the imagery condition were told to scan an image of the pattern, following a 0.5 sec projection of the pattern on the screen. Scanning times for the perception (Figure 2a) and imagery (Figure 2b) conditions were virtually identical. In both conditions the rate of scanning differed significantly among the three shapes. In a second experiment we investigated whether people could predict their scanning rates. Following a 0.5 second presentation of each pattern, subjects estimated how long it would take to scan an image of that pattern. Figure 2c shows that the estimated scan times differed from the actual scan times, We concluded from these h d i n g s that people actually do mental scanning in a mental


"f 40

2 35$j

30-

58 2.5 -

E 205

15-

6-l 0

1.0

Q5

-

'25 2

Figure 2 Effeet of pattern configuration on (a) perceptual scan time, (b) imaginal scan time, and (c) estimated scan time. From Reed, Hock, & Lockhead (1983).

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scanning task and that they do not have good tacit knowledge of how the shape of patterns influences their scanning rates. But does scanning images improve one’s knowledge of how different shapes influence scanning rates? If people make predictions, scan images, and then again make predictions, would their predictions become more accurate? Unfortunately, we did not do this experiment, but I would guess that the answer is no because learning how the shape of a pattern influences scanning time requires more than doing the task. One must also be able to (1) judge the scanning time for each pattern and (2) integrate the scanning times over different lengths to determine the correct functional relationship for each shape. Another variation of Kosslyn’s mental scanning procedure was included in a study by Intons-Peterson and Roskos-Ewoldsen (1989). They asked subjects to imagine transporting a weight (either a 3ounce balloon, a 3-pound ball, or a 30-pound cannonball) as they moved between pairs of buildings on a campus map. Imaginal-group subjects imaged a map that they had previously learned and visualmap subjects saw the map. Notice that if the carried weights influence the rate of scanning, the balloon, ball and cannonball should cause different slope differences, similar to those shown in Figures 2a and 2b. However, the obtained scanning times were more similar to the parallel curves shown in Figure 2c. For the imaginalmap group, the slopes of the reaction-time functions did not differ across weights, but the y-intercept of the cannonballwas significantly higher than the y-intercept of the other two objects. Subjects’ estimates of their scan times for a short and a long distance were also highly parallel across weights. The mean estimates for the short distance were 3.01seconds t o transport the balloon and 4.10 seconds to transport the cannonball - a differences of 1.09 seconds. The mean estimates for the long distance were 7.03 seconds for the balloon and 8.14 seconds for the cannonball - a difference of 1.11 seconds. The differences between objects stayed the same, rather than diverged, as the distance increased. These aspects of the results could be explained by subjects’ tacit knowledge because the scan times more closely matched the parallel functions of subjects’ estimates than the diverging functions that would result from different rates of scanning. But other aspects of the results could not be explained by tacit knowledge or by demand


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characteristics of the experiment (Intons-Peterson, 1983). Subjects’ actual scan times were much slower than their estimated scan times. They also scanned the imagined map more slowly than the visual map, but the estimated times were the same for both maps. Although the concept of tacit knowledge was originally introduced by Pylyshyn (1981) to question whether imagery is a necessary theoretical concept, it is also useful to determine when imagery leads to the discovery of new information. People may effectively use imagery without discovering new knowledge because either the imagery produces results that correspond t o tacit knowledge or the difference between imagery and tacit knowledge does not lead to the revision of tacit knowledge. One constraint on attempting to improve our judgments about events by mentally simulating the events is that observation may not be sufficient to correct misconceptions, even when observation is based on perception. McCloskey and Kohl (1983) asked subjects to select the trajectory that a ball would follow if a string broke while someone was twirling the ball at a high speed in a circle. One group selected a trajectory from six trajectories drawn on paper. Another group selected a trajectory after watching computer simulations of the six trajectories. Contrary to expectations, the number of correct selections did not differ significantly for the two groups. Computer simulation of trajectories also failed to improve predictions of the path taken by a ball after exiting a curved tube. These results suggest that accurate mental simulation of the different trajectories would not be sufficient for selecting the correct trajectory. Mentally simulating the different paths would seem to be a reasonable imagery task. But, as suggested by the lack of effect of perceptual observation, accurate mental simulation of the alternative paths would likely be insufficient for improving predictions. If students did not improve their judgments after viewing the alternative trajectories, it is unlikely that they would improve their judgments after imagining alternative trajectories.

Imagery is Effective and Sufficient The previous analyses illustrate two ways in which imagery could disappoint us as a means to creative insights. First, our images will not always be sufficiently transformable to allow new

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interpretations of their structure. Second, processing images successfully will not always provide sufficient information for creating new knowledge. 1 would now like to examine a different paradigm that offers greater promise for making new discoveries. The paradigm requires mental synthesis - combining parts to make a whole. An early demonstration of mental synthesis is Shepard and Feng's (1972)study of mental paper folding. The task required judging whether arrows on two squares would meet if the squares were folded into a cube, Response times increased linearly with the total number of squares carried along during the folds, suggesting that subjects were using visual images to mentally construct the cube. Another example of a perceptual synthesis task is Palmer's (1977)research on combining two spatially separated 3-segment parts to form a 6-segment line pattern. Palmer was interested in the structure of patterns rather than in visual images, but good visual imagery skills should be very helpful for this kind of task. He measured how long it took subjects to combine the two parts and then measured their error rate by having them judge whether their synthesis matched a test pattern. The error rate was fairly low, and response times varied from 1.5 seconds for high-goodness parts to 4.5 seconds for medium- and low-goodness parts. Cooper (1990)has recently found that students constructed a three-dimensional representation of complex objects to make judgments about the relation among the top, front, and side views. She gave engineering students two of the three views and asked them to judge whether a third view was compatible with the other two views. She later showed them pairs of three-dimensional objects and asked them to identify which object could be formed from the two-dimensional projections they had seen earlier. T w o aspects of her findings suggested that subjects had previously synthesized a three-dimensional object to make judgments about the compatibility of the two-dimensional views. First, they were fairly accurate in identifjing the correct object. Second, they were significantly more accurate in identifylng the correct object when they had been correct on the compatibility task (90% correct identifications) than when they had been incorrect on the compatibility test (72% correct identifications).


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All of these mental synthesis tasks have a single correct answer. A single answer makes it easy to evaluate the accuracy of performance but makes it difficult to study creativity. The experiments described by Finke (1990) in his recent book on creative imagery allowed him to study creative synthesis by measuring how successfully people could combine parts to make recognizable objects or inventions. One interesting finding was that subjects created as many recognizable objects by using imagery as by using physical synthesis. Furthermore, mental synthesis of imagined parts resulted in significantly more recognizable objects than mental synthesis of perceived parts. Continuation of this approach should be particularly beneficial for increasing our understanding of the relation between imagery and creativity (Anderson & Helstrup, this volume; Finke, this volume). The results of mental synthesis tasks are impressive in demonstrating the effectiveness of imagery. Perhaps these findings are impressive because they require the synthesis of new knowledge rather than modifying previous knowledge. Finding a new part in a pattern, reinterpreting an ambiguous figure, and learning correct trajectories all require modifjrlng old beliefs. Changing one’s mind may be difficult, in general, regardless of the specific role of visual imagery. Training Studies

The results of the previously cited studies present a mixed picture of the effectiveness of imagery for discovering new information. Some results are encouraging, but others challenge us to find techniques that will enhance people’s ability to discover new information in their images. The experiments by Hyman and by Peterson (this volume) show that helpful instructions and appropriate training patterns can increase the number of successful reversals of ambiguous figures. For the ducwrabbit figure, Hyman told subjects to consider the back of the head in their current interpretation to be the front of the head for a different animal. For the chefldog figure, he told subjects to rotate their image. Peterson found providing training patterns that reversed in the same way as the test figure increased the number of reversals. Subjects who practiced on the goosehawk figure were

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more successful than subjects who practiced on the chefldog figure in reversing the dudrabbit figure. Both the goosehawk and duck/ rabbit figures require reference frame reversals. These findings provide a good start, but we need to provide more extensive training of a variety of methods to promote successful transfer across a wide range of problems. Practice on a specific technique, such as reference frame reversal, will only help us make discoveries when reversing the reference frame creates interesting information. People need to learn a variety of different methods to manipulate images so they have alternative approaches for making discoveries. We still know very little about how well people can transfer a promising method from one problem to another. Most work on analogy has focused on the transfer of specific solutions rather than on the transfer of general methods. In contrast, Novick's (1990) recent work focuses on the transfer of methods, such as using a matrix to organize information in a problem. Her research may provide helpful clues about how to train methods that will facilitate the discovery of new information across a variety of problems. But we will still need to learn much more about imagery-based techniques to design effective training procedures. The remainder of this chapter discusses four recommendations.

Recommendations The previously discussed findings provide a starting point for further work on how imagery can aid the discovery of new information. We clearly have more to learn, so I would like to make several recommendations to guide this work. First, we need to better understand how illustrations and diagrams facilitate problem solving. Second, we need to extend research on imagery to include realistic problem-solvingtasks. Third, we need to determine how imagery can lead to successful problem representations that differ from the more standard, symbolic representations. Fourth, we need to extend the study of self-reports to include a wider range of creative insights, such as those obtained by architects.


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Construct Theories of How Pictures Aid Problem Solving We would have a better understanding of how images aid problem solving if we had a better understanding of how pictures aid problem solving. This argument does not imply that pictures and images are identical. As discussed previously, pictures are better than images for reinterpreting patterns (Chambers & Reisberg, 1985; Chambers, Reisberg & Logie, this volume; Reed & Johnsen, 1975) and imagined parts are more useful than perceived parts for synthesizing patterns (Finke, 1990). But the substantial similarity between the functional equivalence of pictures and images (Finke, 1985) should help us predict when images are likely to facilitate performance based on the beneficial effects of pictures. For instance, Mayer (1989) found that adding labeled illustrations to scientific text helped students recall more explanative information in the text but did not improve recall of nonexplanative information. The passage explained how mechanic, hydraulic, and air braking systems operated, and the illustrations showed how the key parts of each system changed when applying the brakes. Of particular interest is Mayer’s finding that students who received the illustrations gave better answers to problem-solving questions, such as what should be done to make brakes more reliable, or more effective. A detailed model of how diagrams can facilitate problem solving (particularly physics and geometry problems) was developed by Larkin and Simon (1987).They proposed that diagrams often display information that is only implicit in a text, and therefore has to be computed to make it explicit. Even when both diagrammatic and text representations contain equivalent information, computational demands can differ in accessing the information. Related information is often located at adjacent locations in diagrams making it easier to recognize patterns, search for information, and make inferences. Diagrams are typically better representations not because they contain more information, but because they support more efficient computations. Larkin and Simon concluded their paper with a comment on visual imagery: In this paper, we have represented external diagrams symbolically as list structures, and the

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Stephen K. Reed inference processes as list processes in a production system language. These representations and processes could equally well be interpreted as denoting mental images and imagery processes in the brain. But much difficult psychological research, the exact character of which we can only dimly perceive, will be required to test this hypothesis. (Larkin & Simon, 1987,p. 98).

Although Larkin and Simon believe that external diagrams and images have similar properties of localization of information, they also believe that substantially less detail can be stored in images. In the next section, I propose some promising areas in which imagery may facilitate problem solutions because the diagrams do not require excessive detail that would prevent them from becoming useful imagined diagrams.

Determine How Imagery can Supplement Problem Solutions My second suggestion is that we need to expand our efforts to understand how imagery can facilitate solving problems. The relation between imagery and successful problem solving has not been ignored by psychologists, as is evident from the extensive review of this topic by Kaufmann (1990). However, Professor Kaufmann began his review with the statements that (1) our knowledge about the role of imagery in problem solving lags behind our knowledge of imagery in learning and memory, and (2) the field suffers from a lack of explicit theoretical formulations that could integrate previous findings and direct future research. My own research efforts in recent years have focused on the study of algebra word problems. Although many of these problems require that students make inferences about spatial relations, I have not studied the influence of diagrams on their inferences. It seems to me, however, that constructing diagrams might be beneficial and that some of the diagrams are simple enough to construct mentally. One of the reasons that I think diagrams would be beneficial is that we have recently discovered that inferences about spatial relations are systematically biased by irrelevant, verbal information (Reed & Zelmer, 1991). We gave psychology students 24 motion problems and asked them to classify the problems according to


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whether the two travelled distances mentioned in the problem should be added, subtracted, or equated. Consider the following problem: An athlete trains by running for 1.5 hours and biking for 1 hour, covering a total distance of 25 miles. If his running speed is 10 mph slower than his biking speed, how fast does he run? This is an example of a motion problem, consisting of two travelled distances, two speeds, and two times. Should the distances be equated, added, or subtracted? We wanted to determine whether an irrelevant relation, the relation between the two speeds, influences subjects’ decisions about distances. We had reason to expect such an influence. Previous studies have shown that novices often solve problems by using a meandend analysis search that focuses on the unknown variahle (Gick, 1986; Larkin, McDermott, Simon, & Simon, 1980; Sweller, Mawer, & Ward, 1983). Although the relation between the two speeds is irrelevant to deciding the relation between two distances, it may nonetheless bias students’ decisions because of its importance as an unknown variable. We tested these hypotheses by creating four questions for each problem by orthogonally varying whether the goal was to find the slower or faster of the two speeds, and whether the word slower or faster described the relation between the two speeds (the different questions was a between-subjects variable). Table 1shows the four questions for three of the problems used in our study. The correct answer is that the two distances should be added in the first example, subtracted in the second example, and equated in the third example. Our findings supported our suspicions. Subjects responded significantly more often that the two distances should be added when the goal was t o find the faster speed, and subtracted when the goal was to find the slower speed. Similar results were found for the biasing effect of the words slower and faster, although the bias was significant only for the addition responses. Students correctly classified only 44% of the problems, not much higher than the 33% correct classifications expected by chance. The large number of misclassifications and the significant biasing effect of irrelevant, nonspatial relations (such as speed) indicate that we need to find effective methods for improving spatial inferences.

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TABLE 1 Example of problems and questions used by Reed & Zelmer (1991) to study how irrelevant verbal information influences spatial inferences. Unknown Description Problem and Questions An athkte trains by running for 1.5 hours and biking fir 1 hour, covering a total distance of 25 miks. If his running speed is 10 mph slower than his biking slower slower speed, how fast does he run? faster slower If his biking speed is 10 mph faster than his running speed, how fast does he run? slower faster If his runningspeed is 10 mph slower than his biking speed, how fast does he bike? faster If his biking speed is 10 mph faster than his running faster speed, how fast does he bike? Karen’s boat can travel 160 miles further in 8 hours than Jane’s boat can travel in 10 hours. slower slower How fast is Jane’s boat is Jane’s boat is 25 mph slower? faster slower How fast is Jane’s boat if Karen’s boat is 25 mph faster? slower faster How fast is Karen’s boat if Jane’s boat is 25 mph slower? faster faster How fast is Karen’s boat if Karen’s boat is 25 mph faster? n m drove to his vacation home in 7 hours and returned by the same route in 5 hours. slower slower How fast did he drive to his vacation home if his initial speed was 18 mph slower? faster slower How fast did he drive to his vacation home if his return speed was 18 mph faster? slower faster How fast did he return from his vacation home if his initial speed was 18 mph slower? faster faster How fast did he return from his vacation home if his return speed WBB 18 mph faster? Note: Unknown refers to whether the question asks for the value of the slower or faster speed, and Description refers to whether the word slower or faster describes the relation between the two speeds.


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One approach would be to ask students to physically construct simple vector diagrams to represent the two distances in each problem. Following practice on constructing vector diagrams, with feedback, they would be instructed to mentally construct vector diagrams of the problems. Vector diagrams are sufficiently simple that their mental construction should be feasible if a high level of performance can be achieved during physical construction. Determine How Imagery can Replace Standard Solutions My third suggestion is that we need to discover how imagery can lead to novel representations of problems that can replace standard representations. Although the use of either physicallyconstructed or imagined diagrams might improve spatial inferences in solving standard word problems, few of us would classify these solutions as creative. The role of imagery in these situations is to facilitate the construction of standard solutions based on algebraic equations. Let’s now look at a more challenging problem that can be solved by a creative approach based on spatial inferences (Trismen, 1988). A man is standing on a bridge, 300 feet from the near side and 500 feet from the far side. A train is approaching the near side. If the man runs at a speed of 10 mph toward the train, he will reach the near end of the bridge just as the train does. If he runs at a speed of 10 mph away from the train, he will reach the far end of the bridge just as the train overtakes him. What is the speed of the train? You can solve this problem without using paper and pencil and without constructing equations if you can make the appropriate spatial inferences. My experience has been that people find this a challenging problem, and that even good problem solvers often prefer to search for an algebraic solution, rather than look for the simpler approach, See if you can find the solution by discovering helpful spatial relations. If you have not yet solved the problem, see if you can solve it after answering the following question: If the man runs away from

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the train, where will he be when the train reaches the near end of the bridge? The answer is that if the man runs 10 mph away from the train he should travel 300 feet by the time the train reaches the near end of the bridge. If he continues running at 10 mph, he and the train will reach the far end at the same time. The train therefore has to travel 800 (500 + 300)feet in the same time that the man travels 200 (500 - 300)feet. The train must therefore be travelling four times as fast as the man, or 40 mph. This kind of problem should be particularly useful for studying creativity and imagery, First, the solution based on spatial inferences is challenging and requires that we ignore the more direct approach of searching for algebraic equations. Second, making spatial inferences should be facilitated by imagery. Even if people physically construct a diagram to represent the initial state of the problem, they must appropriately move the train and man to discover helpful information. My own experience in solving this problem is that I initially thought about constructing an algebraic equation to represent all the relevant information. However, I quickly abandoned this approach for two reasons. First, I wasn’t certain that I could construct a correct equation. Second, because the distances are measured in feet and the speeds are measured in miles per hour, I might have to make some conversions to a common unit of measurement. I then decided to use a more imagery-based approach that did not require solving an equation. I mention my experience because it fits Kaufmann’s (1990) formulation of how imagery is used in problem solving. He proposes that imagery is a back-up system that is used when computational processes break down, because of either a lack of rule-based knowledge or because of the strain on working memory created by a high information load. Images allow the problem solver to construct perceptual-like mental models based on perceptual operations that are simpler than the computational operations. As I was writing this chapter I decided to try to solve the bridge problem by constructing algebraic equations so I could compare the algebraic solution with the imagery solution, Constructing equations initially requires that the problem solver determine what t o equate. The bridge problem specifies that the man and train reach the near


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side of the bridge at the same time when the man runs toward the near side, and both reach the far side at the same time when the man runs toward the far side. I therefore decided to equate the amount of time taken by the man and train to reach one end of the bridge. Time can be expressed as distance divided by speed. The time taken by the man to reach the near side is therefore proportional to 300 feet divided by 10 miles per hour. I decided to ignore the difference in units, hoping that conversion to a common unit would "cancel out" in the equation and therefore not be necessary. The time taken by the train to reach the near side is proportional to d divided by s, where d is the distance (in feet) of the train from the near side and s is its speed (in rnph), both of which are unknown. This leads to Equation 1.

300 feet -- -d 10 mph

s

Because there are two unknowns, I needed another equation t o solve for s. The other equation is the time to reach the far side of the bridge. The time required by the man is proportional to 500 feet divided by 10 mph. The time required by the train is proportional to d + 800 divided by s, where d + 800 is the distance of the train from the far side of the bridge. This leads to Equation 2.

10 mph

S

Solving Equation 1for d yields d = 30s. Substituting 30s for d in Equation 2 and solving for s yields s = 40 mph, which fortunately is the same answer obtained from the imagery solution. Shepard (1978) has suggested several reasons why mental imagery and spatial visualization can facilitate creative problem solving. These reasons are discussed in some detail by IntonsPeterson (this volume) so I will only briefly mention their relevance t o this example. One reason that imagery may lead to creative solutions is that it provides an alternative approach that differs from

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more traditional approaches. I believe that constructing equations is the more traditional approach for solving word problems because this method is typically emphasized in algebra classes. There is nothing wrong with this method if students can apply it correctly, but the imagery approach provides an alternative method for finding the solution. Shepard argued that images precede language development and can result in more intuitive solutions. The algebraic solution of the bridge problem depends on knowledge of algebra that may be lacking in many students. Those students who are able to solve the problem by making spatial inferences therefore have an advantage over students who rely solely on algebra. A third reason for using imagery is that the richness of imagery suggests new relations that are not immediately apparent in the verbal statement of the problem. Imagining the man running 300 feet toward the far end of the bridge has the advantage that we now know the location of both the man and the train, which greatly simplifies the problem. The algebraic solution required solving two equations because both the speed and location of the train were unknowns in the initial statement of the problem. A fourth reason is that imagery may help reveal structural symmetries and invariances. An example in the bridge problem is that it doesn’t matter whether the man runs 300 feet at 10 mph toward the near end or far end - in both cases the train will arrive at the near end. Recognizing this invariance lead to the relatively simple solution based on imagery. Collect Self-Reports from Nonscientists

My final suggestion is that we need to collect self-reports from nonscientists t o determine how imagery helped them make new discoveries. Self-reports of how people made important discoveries can further our understanding of the role of imagery in those discoveries. Shepard’s (1988) chapter, cited at the beginning of this article, contains many examples of how imagery aided scientific discoveries. It is important t o note, however, that Shepard did not seek out these examples until after he was confident that he could objectively study imagery in the laboratory. Relating laboratory findings to self-reports should be a promising approach t o relating imagery, which can be more effectively studied in the laboratory, to


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creativity, which in its highest form typically occurs when psychologists are not present to study it. The collection of self-reports has focused on scientific discoveries, which is a good place to begin, but we should extend this collection to other domains. Architecture is another occupation in which visual creativity is important. Figure 3 shows a dramatic new building in San Diego, the Emerald-Shapery Center. Developer Sandor Shapery worked out the basic ideas for the design by following Frank Lloyd Wright’s philosophy that good architecture often results from studying nature. Shapery began to study crystals and noticed that many crystals have a hexagonal structure, The final design, by architect C. W. Kim, consisted of eight six-sided spires combined in clusters to form the towers. The hexagonal shapes, besides their aesthetic appeal, have advantages for both construction and the quality of the interior spaces. All horizontal building faces are the same size, allowing for cost savings from the standardization of parts. In addition, there is more window surface area per square foot of floor area than in conventional, rectangular buildings. Every room opens toward the windows, creating a more open, spacious environment than suggested by the physical dimensions. The formation of the eight hexagonal towers into clusters reminds me of the laboratory synthesis tasks that I described earlier. These tasks require that subjects combine several parts to make a whole object. A hexagonal tower was the starting point for the design shown in Figure 3, but the planners needed to decide how to combine towers t o make an aesthetically pleasing and functional design. Mr. Shapery began using three-dimensional models early in his exploration of how to combine these shapes. Physical models are obviously helpful, and I am not arguing that complex architectural designs are created only with visual imagery. But psychologists should not be overly restrictive in emphasizing solely the role of imagery in visual thinking. As I mentioned in my introduction, McKim (1980)has argued that visual thinking is most effective when one can easily move between perception, imagery, and drawing. Many creative discoveries likely involve an integration of all three activities.

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Figure 3 The Emerald-Shapery Center, San Diego.


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Conclusions In conclusion, I have attempted to examine current research findings for clues regarding when imagery is likely to lead to new discoveries. New discoveries may be limited by either the ineffectiveness or the insufficiency of mental images. In the first case, images are too vague to support new discoveries. For instance, people usually find it difficult to reinterpret images to find a new part or an alternative interpretation. In the second case, images are effectively processed but don’t provide enough knowledge for new discoveries. People may be able to mentally simulate events, without changing their current beliefs. A third case is the successful use of images to discover new information, such as often occurs during mental synthesis tasks. These successful cases should motivate us to find effective training procedures to improve people’s ability to make difficult discoveries. These procedures should train people on a variety of methods for manipulating images and investigate the transfer of these methods to new problems. Improving people’s ability to effectively use images will depend on how much we learn about the role of imagery in creative thought. We would have a better understanding of how imagery aided visual thinking if we had better theories of how pictures aided visual thinking. We also need to extend imagery paradigms into problem solving domains that emphasize spatial knowledge. Some algebra word problems and most physics problems are good candidates. We need to explore how imagery can help us apply standard solutions and lead to changes from symbolic representations to novel, pictorial representations. Finally we need to link laboratory findings to selfreports of creative thinkers to identify the kind of spatial operations that are used across a variety of real-world tasks.

References Chambers, D., & Reisberg, D. (1985). Can mental images be ambiguous? Journal of Experimental Psychology: Human Perception and Performance, 11, 317-320. Cooper, L. A. (1990). Mental representation of three-dimensional objects in visual problem solving and recognition. Journal of

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Experimental Psychology: Learning, Memory, and Cognition, 16, 1097-1106. Finke, R. A. (1985).Theories relating mental imagery to perception. Psychological Bulletin, 98, 236-259. Finke, R. A.(1990).Creative imagery: Discoveries and inventions in visualization. Hillsdale, N J : Erlbaum. Educational Gick, M. (1986). Problem solving strategies. Psychologist, 21, 99-120. Intons-Peterson, M. J. (1983).Imagery paradigms: How vulnerable Journal of are they to experimenters’ expectations? Experimental Psychology: Human Perception and Performance, 9,394-412. Intons-Peterson, M. J., & Roskos-Ewoldsen, B. B. (1989). Sensoryperceptual qualities of images. Journal of Experimental Psychology: Learning, Memory, & Cognition, 15,188-199. Kaufmann, G. (1990). Imagery effects on problem solving. In P. J. Hampson, D. F. Marks, & J. T. E. Richardson (Eds.), Imagery: Current developments (pp. 169-196). London: Routledge. Kosslyn, S. M., Ball, T. M., & Reiser, B. J. (1978). Visual images preserve metric spatial information: Evidence from studies of image scanning. Journal of Experimental Psychology: Human Perception and Performance, 4, 47-60. Larkin, J. H., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science, 208, 1335-1342. Larkin, J. H., & Simon, H. A. (1987).Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65-99. Mayer, R. E. (1983). Thinking, problem solving, cognition. New York: W. H. Freeman. Mayer, R. E. (1989).Systematic thinking fostered by illustrations in scientific text. Journal of Educational Psychology, 81,240-246. McCloskey, M.,& Kohl, D. (1983). Naive physics: The curvilinear impetus principle and its role in interactions with moving objects. Journal of Experimental Psychology: Learning, Memory, and Cognition, 9,146-156. McKim, R.H.(1980).Experiences in visual thinking. Belmont, CA: Wadsworth.


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Mitchell, D. B., & Richman, C. L. (1980). Confirmed reservations: Mental travel. Journal of Experimental Psychology: Human Perception and Performance, 6, 58-66. Novick, L. R. (1990). Representational transfer in problem solving. Psychological Science, 1 , 1.28-132. Palmer, S. E. (1977). Hierarchical structure in perceptual representation. Cognitive Psychology, 9,441-474. Pylyshyn, Z. W. (1981). The imagery debate: Analogue media versus tacit knowledge. Psychological Review, 88, 16-45. Reed, S. K., & Angaran, A. J. (1972). Structural models and embedded-figure difficulty for normal and retarded children. Perceptual and Motor Skills, 35, 155-164. Reed, S. K., Hock, H. S., & Lockhead, G. R. (1983). Tacit knowledge and the effect of pattern configuration on mental scanning. Memory & Cognition, 11, 137-143. Reed, S. K., & Johnsen, J. A. (1975). Detection of parts in patterns and images. Memory & Cognition, 3, 569-575. Reed, S. K., & Zelmer, R. (1991, November). Acquired modularity for assigning relations in problems. Paper presented at the 32nd annual meeting of the Psychonomic Society, San Francisco. Shepard, R. N. (1978). Externalization of mental images and the act of creation. In B. S. Randawa & W. E. Coffman (Eds.), Visual learning, thinking, and communication (pp. 133-189). New York: Academic Press. Shepard, R. (1988). The imagination of the scientist. In K. Egan & D. Nadaner (Eds.), Imagination and education (pp. 153 -185). New York: Teachers College Press. Shepard, R. N., & Feng, C. (1972). A chronometric study of mental paper folding. Cognitive Psychology, 3, 228 -243. Sweller, J., Mawer, R. F., & Ward, M. R. (1983). Development of expertise in mathematical problem solving. Journal of Experimental Psychology: General, 112, 639-661. Tresselt, M. E., & Mayzner, M. S. (1966). Normative solution times for a sample of 134 solution words and 378 associated anagrams. Psychonomic Monograph Supplements No. 15, 1, 293-298. Trismen, D.A. (1988). Hints: An aid to diagnosis in mathematical problem solving. Journal for Research in Mathematics Education, 19, 358-361.

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Watson, J. D. (1968). The double helix. New York: New American Library.

Imagery, Creativity, and Discovcry: A Cognitive Perspcctive B. Roskos-Ewoldson. M.J. Intons-Peterson and R.E. Anderson (Editors) 0 1993 Elsevier Science Publishers B.V. All rights reserved.

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Chapter 11 ~~

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IMAGERY, CREATIVITY, AND DISCOVERY= CONCLUSIONS AND IMPLICATIONS Beverly Roskos-Ewoldson Margaret Jean Intons-Peterson Department of Psychology Department of Psychology Indiana Uni vers i ty University of Alabama Tuscaloosa, AL 35486 Bloomington, IN 47405 USA USA Rita E. Anderson Department of Psychology Memorial University St. John's, Newfoundland Canada A l C 5S7 This book represents our conviction that a cognitive perspective can inform research and yield insights into the relations among imagery, creativity, and discovery. Our main goal for this volume has been to explore the role of imagery in creativity and discovery, and to determine whether the introspective reports of imagery's use in creative problem solving are epiphenomena1 or cognitively valid. The chapters in this volume assessed, through discussion of current theory and research, our progress with respect to the following central issues: (a) identifylng the processes involved in creativity and discovery, and determining how imagery influences these processes; (b) determining which properties of visual and auditory imaginal processes facilitate or limit creativity and discovery; (c) determining whether the purported limitations of images reflect limitations of the imaginal system or are part of a more general limitation of cognitive

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processing capacity; and (d) determining other aspects of the imaginal process that may be used in the creativity/discovery process. The following summary recapitulates the main themes of the chapters and includes comments from discussion among the conference participants during the concluding session. We first describe the problems encountered while attempting to define creativity and discovery. Next, we discuss imagery’s role in the creative enterprise. Finally, we examine the insights delivered by applying the cognitive perspective to the relations among imagery, creativity, and discovery, and identify areas in need of further research.

What is Meant by “Creativity”and “Discovery”? We sought definitions of terms such as “creativity,” “creative,” and “discovery” so that we would share a common understanding. This goal was partially thwarted by some instructive and constructive disagreements.

Multiple Definitions One view (e.g., Anderson & Helstrup; Finke) emphasized the discovery process within the larger realm of the creative process. Discovery, in this view, is embedded in creativity. Proponents consider the cognitive processes involved in a visual discovery task; namely, construction and interpretation (Anderson & Helstrup) or generation and exploration (Finke). Another view (e.g., RoskosEwoldsen) described “creativity” as a process that results in a form or figure that may or may not be judged to be creative. Combinational play, similar to the others’ generation and construction, comprises the creativity (rather than the creative) process. Interpretation and exploration constitute the discovery process. This latter view is somewhat more sequential, with the products of the creativity process feeding the discovery process, although the processes can act independently. All views share the commonality of hypothesizing that cognitive processes are fundamental to both discovery and creativity. They differ in the relations and ordering of the processes of creativity and

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discovery to each other, and in the cognitive processes hypothesized to contribute to each. The views are compared and contrasted in more detail below. Three Views of the Creative Process Anderson and Helstrup describe the processes involved in the general visual discovery task, defined as the set of tasks in which subjects find parts in whole patterns, or synthesize or construct a whole from the parts. In this view of figure construction, the parts to be used are entered into a memory store and then are combined and constructed in a visual buffer to form a figure. The constructed figure is interpreted or searched for signs of a recognizable figure. Both controlled, goal-directed, and more gestalt-like automatic figure formation and segmentation processes are assumed to be involved in the construction and interpretation phases. Once a decision is made that the figure is recognizable, the product is reported by labelling and drawing it. Finke proposed the “Geneplore” model, a general view of creative discovery. In his model, Finke identifies two separate processes - generation of preinventive structures and preinventive exploration and interpretation. The inventor begins by generating a structure that may or may not correspond to any particular, useful product. The generated structure is explored for useful purposes or interpretations. The exploration itself may suggest the generation of a new structure, either by focusing or expanding a concept or part of the initial structure. In both of these views, the construction and interpretation (discovery)phases are of equal importance and creativity is assumed to be possible during either phase. In principle, constructions or interpretations can be identified as creative; in practice, however, the interpreted structure is judged for creativity by external judges. In contrast, Roskos-Ewoldsen redefines the concepts of creativity and discovery in terms of the types of cognitive processes that constitute each one. In her view, the phase of generation, construction, or combinational play, discussed by Anderson and Helstrup and by Finke, is defined as creativity. That is, creativity is manipulational, combinational, and generational play. Discovery, then, becomes the interpretation or exploration of the structures

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produced during combinational play, or simply the interpretation of existing structures. Clearly, the term creativity is used in quite different ways between the first two views and the last. Specifically, creativity, as used by Anderson and Helstrup and by Finke, refers to the larger realm of the creative enterprise, of which creative discovery is a part. In this sense, creativity involves an ability to see purposes for newly constructed forms that are unusual or original, Contrast this with Roskos-Ewoldsen's version of creativity, where the term is used in a more specific way to differentiate it from discovery. On her view, the process of creativity involves combinational play, whether or not the product is subsequently judged to be creative. The term discovery is also used differently in the three views. Again, Roskos-Ewoldsen takes a more narrow view of discovery than either Finke or Anderson and Helstrup. The latter researchers describe the discovery task as including both generation-construction and exploration-interpretation processes, whereas Roskos-Ewoldsen defines discovery as the process of exploration-interpretation only. The differences and similarities of these views are both constructive and instructive, for they lead to explorations of the views, thereby advancing our understanding of the creative enterprise.

Other Considerations The difficulty of defining creativity prompted the question: Can we or should we attempt a universal definition of creativity? The resulting discussion suggested that there may be different species of creativity. First, creating may be a form of problem solving. If so, creativity might occur only in relation to a goal or set of goals. Second, creativity may differ depending on the level at which one focuses. For example, what is considered creative for society may not be the same as that considered creative for an individual. Third, if we assume that creation is a process, is the final product a part of creativity? If the final form is a part of creativity, what criteria should be used to judge whether products or their interpretations are creative? Novelty or originality are ofien considered to be indicators of creativity. But if novelty is used as a criterion, problems remain because a product can be novel on different dimensions, and,


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conversely, products with similar values on one dimension may not be perceived as equally creative, overall. Fourth, how do creative scientists (artists, etc.) fit with our notions of creativity? Are these creative people qualitatively different than other, less creative scientists and artists? Or are they at one extreme on a continuum of creative abilities? These discussions reflect the difficulty of deciding on a definition of creativity, and led one conference participant to suggest that the attempt to define creativity may define it out of existence! We turn now to a discussion of imagery and its role in creativity and discovery.

Imagery's Role in Creativity and Discovery Properties of Imagery

What began as an investigation of imagery's role in creativity and discovery led to an opportunity to revisit what we know about imagery. Some general properties of images emerged as themes in many of the chapters. Imagery paradigms most often test a hybrid of language and perception, Subjects typically receive verbal instructions to image something, and the "something" may have to be retrieved from longterm memory. Hence, images are not exclusively visual replications of previously perceived stimuli, nor are they propositions. Rather, they are a true hybrid of both, having both depictive and descriptive qualities (see Chambers; Kaufmann & Helstrup). From most accounts, images are not pictures in the head, complete with all details, waiting to be searched for any piece of information. Instead, images are often produced with intention for some purpose. As such, images tend to be inherently meaningful (Chambers). That is, a description of the image to be formed, based on the intent of the imager, may guide the actual depiction or formation of the image. Second, images occur in many forms, Images range from conceptual images (e.g., intentional thought) to spatial images to mental pictures (e.g., experiential sensation), with spatial images occurring more frequently than either conceptual images or mental pictures (Kaufmann & Helstrup). Furthermore, there is a distinction

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between images that are generated through combinational play and those that are retrieved as visual “pictures” from memory or those that are replayed in the mind as if listening to a tape recording. Similarly, there is a difference between imagining with the use of efferent aspects of sound production (i.e., the musculature of the mouth; enacted imagery) and imagining without their use (“pure” imagery; Reisberg & Logie). By viewing imagery in terms of afferent and efferent partnerships, we begin to understand how, for example, visual imagery differs from auditory imagery. A third property of imagery is that it is part of the cognitive system and, consequently, is dependent on our limited-capacity working memory (Anderson & Helstrup; Chambers; Hyman; Kaufmann & Helstrup; Reisberg & Logie; Roskos-Ewoldsen). Images must be constructed from information stored in long-term memory or from the results of perceptual analysis. Once an image is constructed, it must be maintained over time. Not all information from memory or perceptual analysis will be represented in an image, nor will all information be maintained to the same extent. Because an image is generated and maintained in a limited-capacity system, the image may not be clear everywhere; some aspects of the image may appear to the imagery t o fade in and out, whereas other aspects may never have been there to begin with (i.e., not all details are filled in). Hyman suggested that imagery is like reconstructive memory. Images, like reconstructive memory, may embody the gist of the information originally encountered. Furthermore, aspects of the image that are congruent with our intent for the image may receive more attention and therefore be maintained more so than aspects that are less relevant to the intent (Chambers; Hyman). How are these properties of imagery related to its role in the creative enterprise? More specifically, how do these properties influence imaginal creativity and discovery? Imagery and Discovery Consider first the role of imagery in discovery. Though there is some disagreement about what is considered to be discovery (i.e., whether discovery involves both combinational play and interpretation or just interpretation), there is agreement that interpretation is a major part of the discovery process. With this


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agreement as a basis, we can discuss the limitations and successes of the use of imaginal processing in the discovery-interpretation process. It appears that images can be reinterpreted or reconstrued there does not appear t o be as absolute a limitation on the interpretability of images, as originally indicated by Chambers and Reisberg's (1985) results. If reconstruals that do not match experimenter-defined correct reconstruals (e.g., the ducWrabbit reconstrued as a fish) are accepted as possible answers, reconstruals are quite common (Kaufmann & Helstrup; Peterson). Although images can be reinterpreted to some degree, imaginal reinterpretations are not as easy as perceptual reinterpretations. This difficulty may occur because imagery is a process that is dependent on a limited capacity memory system and, hence, not all details will appear in an image. The details that appear tend to reflect the intentions of the imagery, and the demands of the task. Therefore, an image may not be reconstrued easily because the image has been formed with a priori meaning. If another image were to be formed from information stored in memory, the content may change, depending on the intent of the imagery (Chambers). Furthermore, an image requires internal support, unlike a drawing. That is, maintaining an image entails more processing capacity than looking at a drawing. The more working memory that is required to maintain the image, the less processing capacity there will be for imaginal discoveries (Anderson 8z Helstrup; Roskos-Ewoldsen). Factors other than processing capacity may also influence imaginal discovery. One factor involves the way an image is inspected, which is determined in part by the type of practice figure provided. Figural reinterpretations can range from reconstruals, where the parts of a figure take on new meaning as different parts of the alternative interpretation, to reference frame reversals, where tophottom and fronthack change from one interpretation to the next. If a figure requires a reference-frame reversal for reinterpretation, imaginal reinterpretation is easier when an appropriate practice figure (i.e., a figure that also requires a reference-frame reversal) is used (Peterson). The type of prompt provided when the subject does not spontaneously reverse an imagined ambiguous figure also affects the way the figure is inspected. If participants are given information

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about both the category to which the alternative interpretation belonged, and the orientation of the alternative (i.e., which perspective is top), then almost half of the participants are able to discover the alternative interpretation (Chambers;Hyman; Peterson). Only 10-15% of the participants who received minimal prompts were able to reinterpret their imagined figures (Hyman; Kaufmann & Helstrup, strict criterion; Peterson). Another factor influencing imaginal discovery is skill at spatial visualization. Kaufmann and Helstrup showed that highly skilled visualizers, as measured by a version of the Minnesota Form Board test, were more likely to reverse an ambiguous figure than Chambers and Reisberg’s subjects, who were unselected for visual or spatial abilities. A final factor involves the perceptual organization of a stimulus, which appears to influence how easily imaginal discovery can occur (Roskos-Ewoldsen). If an imagined pattern has been put together from good (well-organized) parts, discovery of emergent patterns embedded within the imagined pattern occurs more easily than when the imagined pattern was put together with poorly organized parts. The organization of the pattern itself also influences discovery within imagined patterns. Discovery is more difficult (i.e., takes longer) when the pattern is organized than when the pattern is poorly organized. Imagery and the Creative Process

As with discovery, there was some disagreement with what we mean by creative process. The creative process may be the process that gives rise to creative inventions, interpretations, and discoveries (e.g., Anderson & Helstrup; Finke). Roskos-Ewoldsen prefers to discuss not the creative process but creativity per se (i.e., combinational play and manipulation). Despite differences in opinion regarding creativity and the creative process, there is agreement that generation, construction, and combination are major components of the creative process. Given this agreement, we return to the question: Can imagery play a role in the creative process? The answer appears to be yes. First, research by Anderson and Helstrup, Finke, Hyman, and Intons-Peterson has shown that participants unselected for their


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imagery ability (or creative ability, for that matter) can imaginally combine simple shapes to form recognizable patterns, some of which are later judged to be creative patterns. But, is imagery critical to the creative endeavor?

Does Imagery Have a Special Status? Many people have claimed that imagery is critical to the creative process (e.g., Miller, 1984; Shepard, 1978). Shepard for example, argues that imagery has a special status primarily because it is relatively free of linguistic constraints. In particular, he claims that imagery has a richness and relation to external sources that is not fully preserved by language. That is, language may have a constraining influence on imaginal processing and, consequently, on the use of imagery in creativity and discovery. In fact, much of the research reported in this volume lends substance to Shepard's proposal that the conventions of language constrain the kinds of mental imagery operations involved in the processes of creativity and discovery. At one level, this is bound to be true because most experimental tasks involving these processes are presented via verbal instructions. In addition, Chambers and Kaufmann and Helstrup note that both depiction and description presumably are involved in imagery and, consequently, in creativity and discovery. The descriptive, linguistic shaping of imaginal processes, however, seems to be deep, tenacious, and difficult to overcome. Hence, linguistic features and demands will affect performance on tasks involving imagery, creativity, and discovery. The effects of language are shown clearly with respect to the linguistic and conceptual interpretation of images. As much of the research reported, the initial (verbal) interpretation of an image may resist reinterpretation or reconstrual. The most dramatic demonstration is Chambers and Reisberg's (1985)failure to find evidence for any reversals of ambiguous figures, of course, but even hints about using different linguistic-conceptual or spatial perspectives have not produced marked increases in the frequencies of reconstrual (e.g., Chambers, Hyman, Kaufmann & Helstrup, Peterson). Furthermore, Anderson and Helstrup found that asking subjects to use a verbal strategy reduced the number of recognizable patterns produced, compared to visual strategy instructions.

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This apparent suppression of recognizable patterns by a verbal strategy seems at odds with Finke's demonstration that subjects produced more responses judged creative when the responses had to fit specific categories than when they were not constrained t o a single category. Do Finke's results signal linguistic facilitation of creativity? They might, because language can be used to overcome at least some of the resistance to reinterpreting images. For example, when subjects were told which side of a tilted image of the state of Texas was the top, they were able to identify the shape, although they were unable to do so when given less precise verbal hints. Additional evidence of linguistic facilitation comes from other kinds of precise hints (e.g., Hyman, Peterson, Reisberg & Logie). Note, however, that the latter evidence is facilitation only in the sense that precise hints may combat resistance to reinterpretation of images. It does not really address the creativity issue, as Finke's results do. But we return to the question: Do his results signal linguistic facilitation of creativity? Again, the answer must be that it is possible. An alternative explanation does exist, however: Having a category label may aid the search and retrieval process. Subjects in Intons-Peterson's work often remarked that they "hardly knew where to begin" when drawing their images. Having a target category may focus the search, as required by the task. This perspective argues that the apparent facilitation of creativity afforded by specifying linguistic category may arise from the targeting of the search among alternatives to the number of images specified by the instructions. Summarizing the interrelations between language and imagery, language clearly affects imaginal activities by defining and constraining the interpretations of the mental products of imaginal processing. Language also may aid release from these constraints. Thus, although we are not yet in a position to generate finely tuned predictions of the interrelations of language and imaginal-spatial processing, we must be sensitive to language's existence and likely influence on all experimentation in this area. Shepard also proposed that imaginal activity has a special richness that is conducive to creativity. Intons-Peterson provides an example of the facilitating effects of imagery. Though she found no differences in the number of creative figures constructed during an initial test session among conditions that varied the likelihood of


323

using imagery to perform the task, she found that, after practice, more creative figures were produced by subjects in the imageryinducing conditions than by subjects in the conditions less likely to induce the use of imagery. Other evidence described in the chapters is tangentially related to Shepard's point that imagery is a rich alternative compared to language. Reed suggests that diagrams and pictures (and images, by extension) are particularly useful, not because they contain more information than verbal descriptions, but because they support more efficient computations than strictly verbal descriptions. Specifically, there are some problems that can be solved by imagining the spatial relationships among the elements of the problem to be solved, and "seeing" how the relationships change over time. This spatialimaginal inferential reasoning can be easier and less time-consuming than a more direct approach such as searching for algebraic equations (see also Lindsay, 1988). Reed also suggests that although diagrams may encourage this inferential reasoning, diagrams are static. Because mental images can be dynamic, they may facilitate the dynamical transformation of the diagram information. In addition, Peterson argued that reconstruals dominate in imagery; reference frames in perception. It is not clear from her research that the reconstruals of imagery provide greater richness than the reference frames of perception, but Shepard's view is that imaginal-spatial activity may have its own special richness. Part of that richness may be related to Peterson's reconstruals. Thus, in imagery, as in reconstruals, the manipulation of internal parts may be fairly easy, and modifying the overall configuration may be less easy, a position entirely consistent with Roskos-Ewoldsen's evidence. If so, these reconstruals are exactly the kind of mental manipulation that would be expected to foster both creativity and discovery. Shepard's third suggestion was that imagery, with its aspects of intuition and manipulation, may precede language developmentally. Evidence that young children develop efficient navigational systems before extensive communication (Mandler, 1983) and that monkeys show patterns of responses that resemble mental rotation even though they do not speak in the usual sense (Georgopoulos, Lurito, Petrides, Schwartz, & Massey, 1989) can be cited to support this view, These claims may be disputed, however, by people claiming

324


that many nonhuman animals possess effective communication systems. Finally, Shepard notes that symmetries may have a special status within visualization. Impressive support for this view emerged from a number of laboratories. Roskos-Ewoldsen found that symmetry, roughly equated to goodness ratings, has complicated effects, which may be related to Peterson's distinction between reconstrual and reference frame reversals. Roskos-Ewoldsen found that patterns previously judged to be poor were not as cohesive as good patterns, hence it was easier to dissemble or reparse poor patterns into their component parts than to dissemble or reparse good patterns into their components. The poor patterns tended to be less symmetrical than the good patterns and, thus, may be akin to the sensitivity of images to reconstrual of internal parts. Good (symmetrical)patterns cohere, require less processing time, and, like reference frame reversals, resist fragmentation or reinterpretation. In brief, then, the effects of symmetry (goodness) depend upon whether the symmetry is manifested primarily in the outer edges or perimeter of the object or internally. As a final note on Shepard's claim that imagery has a special status in creativity, we mention that imaginal manipulation of stimuli is often more difficult than doodling with, seeing, or hearing the stimuli. This difficulty is exemplified by Kaufmann and Helstrup's research. Their findings show that although participants who were chosen for their high spatial and visualizing abilities performed better than other unselected subjects (e.g., Chambers & Reisberg, 1985; Hyman; Peterson), less than 30% of the high ability students could reconstrue their own images, according to Chambers and Reisberg's reconstrual criterion. The bottom line is that creativity and discovery can occur with the use of imagery; we have not yet shown that imagery facilitates the processes, in comparison to the use of external support &e., doodling, seeing, hearing). Instead, what appears to be most important for the creative process is to be able to transform information from one code t o another--for example, from verbal to imaginal and back again--so as to gain multiple perspectives on the task at hand, a point mentioned during the final discussion session of the conference (see also Peterson).


325

Future Directions So far we have considered the cognitive aspects or Greativity and discovery, and we have explored the properties of mental imagery that facilitated or limited its use in the creative process. We now venture into even less charted territory by suggesting future research directions.

Training The training of people to use mental imagery in creativity and discovery has had a colorful past (e.g., McKim, 1972). Our research suggests that training should and can be informed by theory. Specifically, we know that the type of hints provided about changing orientations, or captions of “top” and “bottom,” is crucial for discovery (Chambers; Hyman). Likewise, the type of stimuli used in practice is important for discovery (Peterson). Further, practice itself appears to facilitate discoveries which are judged to be creative, especially when imaginal processes are likely to be invoked (IntonsPeterson). What about creativity? What kinds of training leads to improved combinational play? Reed argues that to understand the circumstances under which imagery will work, we should begin by investigating the circumstances under which diagrams work, for they may serve similar purposes. In addition, Reed suggests that we should investigate the work of individuals from domains where imagery is likely to be central, such as architecture.

Problem Solving Reed also suggests that we extend imagery paradigms to problem solving. How does imagery work within this realm? What are the cognitive processes that allow the use of imagery in problem solving? How does the use of imagery compare to the use of algorithms? How does using imagery compare with using diagrams? In a sense, research by Anderson and Helstrup, Finke, and IntonsPeterson already deals with problem solving. When participants are asked to combine parts in such a way that they form a recognizable form, or are asked to interpret a structure in terms of a given

326


category, the task can be perceived as a problem to be solved, with the solution being open-ended Le., there is no single correct answer).

Individual Differences Another direction for future research involves the range of cognitive abilities people may have to play combinationally with parts or to reinterpret or discover embedded figures. These are the abilities that drive the creativity and discovery processes. To understand these processes is to understand creativity and discovery. Intons-Peterson raises several questions related to individual differences. Can creative discovery be taught, or is it the special domain of a few gifted individuals? Some imagers may generate and search their images more rapidly than others - are these people more likely to reverse their images, make discoveries within their images, or be more creative than others who generate and search more slowly? Conversely, are creative individuals quicker at reversing or discovering from images than others who are less creative? Perhaps speed of generatiodsearch is not as important as the strategies used to complete the task. Creative individuals may focus their search for a solution differently than less creative individuals.

Cognitive Processes in Visual and Auditory Imagery Reisberg and Logie present an intriguing analysis of the similarities and differences between visual and auditory imagery, based on differences in working memory for auditory and visual information. More research exploring the afferentlefferent qualities of audition and vision, and their auditory and visual imagery counterparts, needs to be conducted.

Imagery within the Limited-Capacity Cognitive System There should be more emphasis not only on defining what we mean by creativity and discovery, and how imagery is able to be used in these processes, but also on understanding how imagery, creativity, and discovery fit into the cognitive system. Not only do we need to relate imagery to perception, but we need to understand better how limited processing capacities limit imaginal performance.


32 7

We also need to examine how the interactions between language and imagery affect creativity and discovery.

Motivation and Affective Concomitants Shepard (1978) argues that images are more likely to engage affective systems than verbal language. Finke talked about the "haunting" quality of many of the forms generated by his subjects, and the interest they had in pursuing the implications of their inventions. Intons-Peterson noted that although little work has been conducted in this area, recent work by D. Roskos-Ewoldsen and Franks (personal communication) suggests that affect and imagery are interconnected in the cognitive system. At this time it is unclear whether imagery drives the affective system or vice versa. Nor is it clear how motivational factors enter into our picture of creativity and discovery.

Summary Throughout this volume we hoped to define and discuss the major theoretical issues, including (a) processes that are involved in creativity and discovery, and how imagery influences these processes, (b)properties of visual and auditory imaginal processes that facilitate or limit use of creativity and discovery, (c) purported limitations of images, considered either as a limitation of the imaginal system or as a general constraint of processing capacity, and (d) other aspects of the imaginal process that may be used in the creativity-discovery process. We close by noting that in her introduction, Intons-Peterson revealed the limited creativity of psychologists with respect to our understanding of creativity. The four stages of creativity suggested by Wallas (1926)have not changed in the last seventy-five years. Our hope is that a cognitive perspective may help us to move beyond the old to new conceptions of creativity.

328

B. Roskos-Ewoldsen et al. References

Chambers, D., & Reisberg, D. (1985). Can mental images be ambiguous? Journal of Experimental Psychology: Human Perception and Performance, 11, 317-328. Georgopoulos,A. P., Lurito, J.,Petrides, M., Schwartz, A., & Massey, J. (1989). Mental rotation of the neuronal population vector. Science, 243, 234-236. Lindsay, R. K. (1988). Images and inference. Cognition, 29, 229-250. Mandler, J. M. (1983). Representation. In P. H. Mussen (Ed.), Handbook of child psychology, Vol. IIZ. (4thed.) (pp. 420-494). New York Wiley. McKim, R. H. (1972).Experiences in visual thinking. Monterey, C A BrookdCole. Miller, A. I. (1984). Imagery in scientific thought: Creating 20th century physics. Boston: Birkhauser. Shepard, R. N. (1978).Externalization of mental images and the act of creation. In B. S.Randawa & W.E. Coffman (Eds.), Visual learning, thinking, and communication (pp. 133-189). New York: Academic Press. Wallas, G. (1926). The art of thought. New York Harcourt Brace,

329

AUTHORINDEX A Ahsen, A., 126,146 Amabile, T.M.,258,283 Anderson, J.R., 129, 135,146,256, 283 Anderson, R.A., 62,67 Anderson, R.E.,5, 8,10,11, 13, 14, 15,20,21,27,28,30,31,32, 33,35,50,75,77,94,126,127, 145,147,189,190,191,192, 193,194,195,198,200,202, 215,219,223,224,226,231, 233,235,236,237,238,243, 246,250,251,259,297,314, 315,316,318,319,320,321, 325 Angaran, A.J., 291,311 Arieti, S., 2,33 Arnheim, R., 2,33,84,93 Attneave, F.,204,210,218

Bialystok, E., 44, 74 Biederman, I., 156,157,182,232, 250 Binford, T.O.,156,183 Bishop, D.V.M., 8,33,67,69 Block, N.,143,146,198,218 Boden, M.,282,283 Bradshaw, G.L., 30,31,35 Brandimonte, M.A.,8,33,48,67,69 Bransford, J.D., 101,120,278,283 Brentano, ,F.,79,95 Brody, B.A., 64,69 Brooks, L., 62,69 Brown, J.L., 203,204,220 Bruce, D., 224,229,250 Bruner, J., 41,69 Bruning, J.L., 165,183 Brunn, J., 229,251 Bryant, P., 54,73 Buchanan, M.,55,69 Butters, N.,64,69

B Baddeley, AD., 52,53,54,56,59, 61,62,65,69,72,73,74,76 Ball, T.M., 292,310 Barclay, C.R., 101,120 Bartlett, F.C., 100,116,118,120, 134 146 Barton, M.,64,69 Bassok, M.,31,33 Baxter, D.A., 23,25,36,50,51,57, 75,198,199,220 Begg, I.M., 31, 36 Bellugi, U.,59,69 Besner, D.,52,53,69

C Calvanio, R., 61,62,69 Caminiti, R., 64,72 Campbell, R., 59,69 Carpenter, P.A., 61,69 Cary, L.,203,220,229,251 Cave, K.R., 229,251 Chambers, D., 8,22,23,24,25, 26, 27,34,39,40,42,43,44,45, 46,47,48,50,57,66,69,75, 78,80,81,82,83,84,88,89, 90,91,92,93,94,95,97 99, 100,102,103,104, 105,108,

330

Author Index

109, 117, 118,120,121,128, 130,131, 135, 137,140, 142, 143,145,146,149, 152, 155, 156,157, 158, 159, 161,162, 165,167,168,183,185,194, 198,199,216,218,234,250, 258,283,289,299,309,317, 318,319,320,321,324,325, 328 Christie, D.F.M., 62,74 Clark, J.M., 180,183 Clayton, T.,85,87,88,96 Clement, D.E., 204,210,219 Clifton, C., 52,76 Cocude, M., 10,34 Cohen, C., 204,210,220 Conrad, R., 55,69 Content, A., 203,220,229,251 Cooper, L A , 44,64,76,78,97,187, 188, 198,221,255,256,283, 285,296,309 Cornell, E.H., 228,251 Csikszentmihalyi, M., 258,278,284

D Daniels, S., 52,69 Davies, J., 52,69 Dean, G.,62,69 Della Sala, S.,56,62,69 DeMers, S.T.,6,7,9,36 Denis, M., 10,34 Dennett, D.C., 84,94,129,130,131, 146 Donnenwerth-Nolan,S.,63,75 Duncker, K.,216,219

E Eisenberg, P., 61,69 Engelkamp, J., 63,69,132,146

Ernest, C., 7,34 Essick, G.K., 64,69

F Fagen, R., 248,250 Farah, M.J., 10,23,34,61,62,69, 81,94,96,100, 109, 117,120, 152, 173,183, 184, 198,200, 215,219,230,231,234,250, 258,284 Fanes, J., 99,107 Feng, C., 296,311 Findlay, C.S., 248,250 Finke, R.A.,7,10, 11, 12, 13, 14,20, 21,23,28,30,32,34,39,50, 61,65,66,69,72,74,75,76, 84,92,94,95,96,100, 101, 109,117,120,126, 133,134, 137, 145,146,152,183, 189, 190, 191,192,193,194,195, 197, 198,199,200,201,202, 204,215,216,219,223,224, 225,226,227,229,231,232, 233,234,236,237,239,242, 244,245,247,249,250,255, 256,257,258,259,260,262, 263,264,265,267,268,269, 270,271,272,274,275,276, 279,280,284,297,299,310, 314,315,316,320,322,325 Fischman, D., 62,72 Fisher, G.H.,153, 159,183 Flew, A.G.N., 132,146 Fliegel, S.L.,173,184 Fodor, LA., 79,96,134,146 Franks, J.J., 28, 101,120 Fusella, V., 79,97

Author Index G Gardner, H., 283,284 Garner, W.R., 204,210,219 Gathercole, S.,65,72 Georgopoulos, A.P., 28,34,63,64, 72, 323,328 Gerbino, W.,48,67,69 Getzels, J.W., 258,278,284 Ghiselin, B., 2,34,123,146,256, 281,284 Gibson, B.S., 155,183,184 Gick, M.L., 30,34,301,310 Glisky, M.L., 7,21,23,24,30,31, 36,81,83,97,154, 158, 165, 169,173,174, 175, 176,184 Goldman, A.I., 143,146 Gordon, R.,6,34 Guilford, J.P., 6,34

H Hadamard, J., 123, 146, 188,219 Hadden, S.,63,72 Halper, F.,87,88,96 Hammond, K.M., 61,62,69 Hampson, P.J.,124, 127, 148 Hannay, A., 132,133,146 Harman, G.H., 143,146 Harnish, R., 234,253 Harvey, E.R.,155,184 Hayes, J.R., 31, 34,35 Hazen, N.,228,251 Heil, J., 130,146 Helstrup, T.,5, 8, 10,11,13, 14,15, 20,21,25,27,28,30,31,32, 33,35,47,49,50, 75,81,94, 102,119, 126, 127, 132, 145, 147,189, 190,191,192,193, 194,195, 198,199,200,202, 215,217,219,223,226,228,

331

231,233,234,235,236,237, 238,243,246,249,250,251, 259,297,314,315, 316,317, 318,319,320,321,324,325 Heth, C.D., 228,251 Heuer, F.,62,72 Hilgard, E.R., 1,35 Hill, W.E.,153,183 Hinsley, D.,31, 35 Hinton, G., 40,72,151, 173,183, 203,216,219 Hitch, G.J., 8,33,67,69 Hochberg, J., 42,72,87,96,173, 204,210,219 Hock, H.S., 292,293,311 Hoffman,D.D., 155,156,183 Hoffman, R.,190, 191,219 Holton, G., 188,219 Holyoak, K.J., 31,33,34 Horowitz, L.M.J., 126,127,147 Hyman, I.E.,Jr., 8,21,24,25,27, 29,35,47,48,49, 73,75,81, 82,84,94,96,99,101,102, 120,128, 137,162, 165,184, 194, 199,234,239,297,318, 320,321,322,324,325

I Intons-Peterson, MJ., 10,28,30,35, 123, 134, 145,147, 181, 190, 194,198,200,202,204,215, 216,219,224,230,240,249, 251,257,258,259,270,284, 294,295, 305,310,320,322, 323,325,326,327

J James, W., 86,96 Jastrow, J., 80,88, 90, 93,152,159,

332

Author h d e x

161,164,184 Jenkins, J.J., 101,120 Johnsen, J.A., 22,36,151,185,203, 220,223,252,289,299,311 Johnson, N.S., 101,121 Johnson, P.,62,73 Johnson-Laird,P.N.,229,251,282, 284 Jolieoeur, P., 157,172,173,184 Jonides, J., 61,73

K Kahn, R., 61, 73 Kalaska, J.F.,64,72 Kanizsa, G., 42,73 KaufmaM, G.,5,8,21,25,28,47, 49,77,102,119,123,124,125, 126,127,130,144,147,148, 194,198,217,226,228,234, 249,300,304,310,317,318, 319,320,321,324 Keenan,J.M., 61,76 Kern, N.H., 61,73 Kihlstrom, J.F., 7,21,23,24,30,36, 81,82,97,154,158,165, 169, 173,174,175,176,184 Kimura, Y., 54,73 Kinbch, w., 101,120 Kintz, B.L.,165,183 Klatzky, R.L., 10,35,203,204,220, 221 Klima, E.S.,61,69 Koestler, A, 256,285 Kohl, D., 295,310 Kolbet, L., 84,85,88, 92,97 Kolers, P.A., 127,148 Kolinsky, R., 203,220,229,251 Kosslyn, S.M.,27,35,39,44,62,64, 69.73. 77. 78. 86. 94.96. 101.

102,118,120, 121,126,127, 133,137,148, 173,184,198, 203,220,225, 226,229,230, 234,251,252,255,285,292, 294,310 Krueger, T.H., 31,35 Kurtzman, H., 39,72

L Lachman, J.L., 227,251 Lachman, R.L., 227,251 Langley, P., 30,31, 35 Larkin, J.H., 299,300,301,310 Leak, S., 62,75 Levine, D.N., 61,62,69 Levy, B., 52,73 Lieberman, K.,61,62,69 Lewis, V.J., 53,56, 69 Lindsay, R.K., 323,328 Lockhead, G.R., 292,293,311 Logie, R.H., 25,28,31,55,59,61, 62,63,69, 73,74,102,106, 128,134,135,142,152,155, 157,198,199,232,234,299, 318,322,326 Lubart, T.I.,217,220,221 Luchins, A.S.,216,220 Lumsden, C.J., 248,250 Lurito, J., 28,34,64,72,328

M Maier, N.R.F., 182,184 Mandler, J.M., 28,35,101,121,229, 251,323,328 Marchetti, C., 61,62,63,69,74 Marks, D.F., 6,35,78,96,132,148 Marmor, G.S., 61,74 Marr, D., 153,156,184 Marschack. A.. 227. 248,251

Author Index Massey, J.T., 28,34,64,72,323,328 Mawer, R.F., 301,311 Matthews, W.A.,62,74 Mayer, R.E., 291,299,310 Mayzner, M.S., 291,311 McAlister, E., 204,210,219 McCloskey, M., 295,310 McDaniel, M.A., 134,147 McDermott, J., 301,310 McKellar, P., 126,132,148 McKim, R.H., 287,307,310,325, 328 Metzler, J., 255,285 Miller, A.I., 1,2,3, 33,35,39,74, 123,148,255,285,321,328 Mitchell, D.B., 292,311 Morais, J., 203,220,229,251 Morris, N., 62,74 Morris, P.E., 62,69,123,127,148 Murray, D., 52,74

N Needham, D.R., 31,36 Neisser, U., 8,24,35,48,72,81,82, 96,99,101,102,120,121,130, 131, 132,148,162,165,184, 229,252 Newell, A., 125,148 Nishihara, H.K.,156,184 Novick, L.R., 31,36,298,311

333

Palmer, S.E., 203,204,210,220, 296,311 Papagno, C., 65,69,74 Parsons, L.M., 173,183,227,252 Pendleton, L.R., 62,76 Perkins, D.N., 278,281,285 Peterson, L.R., 204,210,220 Peterson, M.A., 7,21,23,24, 28,30, 36,42,44,46,47,48,49,72, 77,81,82,84,87,94,97,102, 109,128,137,154, 155,158, 165,169,173, 174,175, 176, 184,194,199,234,236,289, 297,319,320,321,322,323, 324,325 Petrides, M., 28,34,64,72,323,328 Phillips, W.A., 62,74 Pinker, S.,10,23,34,39,74,81,94, 97,100,101,109,117, 118, 120,152,157,183,185,198, 200,215,219,232,234,250, 252,255,258,285 Pope, K.S., 127,149 Price, H.H., 133,149 Price, J.R., 153,184 Pylyshyn, Z.W., 77,97,292,295,311

Q Quinn, J.G., 62,74, 75

R 0 Okovita, H.W., 61,74 Olson, D.,44,74 O'Shaughnessy, M., 59, 75

P Paivio, A., 7,36,61,74,127,148, 180,183

Raaheim, K., 123,148,149 Raichle, M., 230,252 Ralston, G.E., 62,75 Rappaport, I., 59,75 Rawlings, L.,204,210,220 Reed, S.K.,5,22,23,28,30,31,36, 151,185,203,204,220,223, 252,258,285,289,291,292,

334

Author Index

293,299,300,302,311,323, 325 Reisberg, D., 8,22,23,24,25,26, 27,28,31,34,36,39,40,42, 43,44,45,46, 47,48,49, 50,52,53,54,57,59,62,66, 69,72, 76,76,78,79,80,81, 82,83,84,88,89,90,91,92, 93,94,95,97,99,100,102, 103,104,105,108,109,117, 120,121,128,130,131, 135, 137, 140,142,143,145,146, 149,152,155, 156,157,158, 159,161,162, 165,167,168, 183,185,194, 198,199,216, 218,220,232,234,250,252, 258,283,289,299,309,318, 319,321,322,324,326,328 Reiser, B.J., 173,184,292,310 Richards,W.A., 155,156,183 Richardson, J.T.E.,39,52,75,126, 149 Richman, C.L., 292,311 Rock, I., 42,44,75,82,83,86,87, 97,216,220 Roe, A., 2,36 Rose, P.M., 7,21,23,24,30,36,81, 82,97,154,158,165,169,173, 174,175,176,184 Roskos-Ewoldsen,B., 10,21,23,28, 29,30,36,134,147,199,220, 238,245,249,252,258,279, 289,294,310,314,316,318, 319,320,323,324 Roth, J.D., 234,252 Rothenberg, A., 144,145,149,181, 185 Rozin, P.,61,73 Rubin, D.C.,101,120

Rubin, E.,155,185 Ryle, G., 129, 130,132,149

s Saltz,

E.,63,75

Samuels, M.,188,221 Samuels, N.,188,221 Sanford, A.J., 125,149 Schwartz, A.,28,34,64,72,323, 328 Segal, S.J.,79,97 Shand, M.,59,76 Shaw, G.A., 6,7,9,36 Sheikh, A.A., 127,149 Shepard, R.N., 2,4,5,6,7, 8,9,27, 28,29,30,31, 32,34,36,44, 64,76,78,97,123,144,149, 181,182,185,187,188,194, 198,221,227,229,230,252, 255,256,284,285,288,296, 305,306,311,321,322,323, 324,327,328 Shorter, J.M., 130,131, 149 Shwartz, S.P.,101,121 Siegel, R.M., 64,69 Simon,D.P., 301,310 Simon, H.A., 30,31,34,35,123, 125,149,299,300,301,310 Singer, J.L., 127,149 Siple, P., 59,69 Slayton, K.,10,11, 13,14,34,50, 66,69,72,81,96,190,192, 193,198,199,203,204,215, 219,223,231,232,233,234, 239,244,250,257,259,284 Slee, J., 86,97 Slowiaczek, M.,52,76 Smith, G.E.,101,121 Smith, J.D., 23, 25,36,50,51, 52,

Author Index 53, 54,57, 75,76,198,199, 220 Smith, S.M., 194,219,279,280,284 Smyth,M.M., 62,76 Smythe, W.E., 127,148 Sobel, R.S., 144,145,149 Solso, R.L.,1, 37 Sonenshine, M.,23,25,36,50,51, 57, 75,198,199,220 Stein, B.S., 278,283 Sternberg, R.J., 123,150,194,217, 220,221 Sweller, J., 301,311

T Tarr, M., 157,185 Thompson, A.L., 10,35,203,204, 220,221 Thomson, N.,55,69 Tinbergen, N.,23,37,159,185,224, 253 Titchener, E.B., 86,97 Tolman, E.C., 229,253 Torrance, E., 6,37 Tresselt, M.E., 291,311 Trismen, D.A.,303,311 Tsal, Y.,85,86, 87,88,92,97 Tudor, L.,216,220 Tye, M., 198,221

V Valentine, T., 65,74 Vallar, G.,55, 56,65,69,76 van Dijk, T.A., 101,120

W Wallach, R.W., 229,251 Wallas, G., 1, 3,37,270,285,327,

335

328 Ward, M.R., 301,311 Ward, T.B., 194,219,279,280,284 Watson, J.D., 287,312 Weber, R.J.,234,253 Weidenbacher, H.,155,184 Weisberg, R.W., 181,182,185 Wertheimer, M.,188,221 Wheeler, D.,216,220 White, W.,52,53, 76 Wilding, J., 52,53,76 Wilson, M., 25,37,50,52,53, 54,75, 76 Wittgenstein, L., 129,150 Wynn, V.,69

Z Zabeck, L.A., 61,74 Zelmer, R., 300,302,311 Zimler, J., 61,76 Zivin, G.,65,76 Zucco, G.M., 62,74 Zytkow,J.M., 30,31,35


337

SUBJECT INDEX A Adaptation 225,227,248 Affective systems 5,20,28-29,327 Merent channel 58,66,127,318, 326 Algorithms 30,125,325 Anecdotal accounts 2-5,9-10,187188, 194,198,255-256 Architects 5,256,288,307 Aristotle 1 Articulation 52,54 -rehearsal loop 55-59 -suppression of 8 Artists 5, 282-283 Associations 175-182,194 Attention 85-86,92 Audition 48-54

B Beethoven, L. 281 Bohr,N.3

C Cardan, G. 5 Cognitive resources 232-236,248249 Componential analyses 156, 157, 163,231 Computer simulation 30 Construals 2,23-27,40-48, 77-92, 99-120,128, 130, 137, 140-145, 152-182,319,321,323,324 Construction 190-203,314-316 Cortex -Parietal 63-64

Creativity -and combinations 9,187-218, 225,258,314-316,318, 320,325 -and concepts 257-283 -and intelligence 6-7,194 -and inventions 39, 192,200218, 258-283,287-309 -and language 5-21,31, 189191, 198-215,257-283 -and motivation 28-29,217218 -and patterns 9-21,191-215, 223-249,256-283 -and people 2-5,30-33,123, 138, 187-189,217-218, 255,317 -and thought 387-309 -and visualization 255-283, 287-309 -as process or product 316-317 -constraints(restrictions)on, 82-84,93-94,102-103, 248-249,257,281,327 -definition of 10, 123, 181, 189-191,314-317,320 -inventions of 1-6,39,193-218, 258-283,287-309 -judgments of 10-11,13-21, 233-247,258-282 -models of 124, 134-137,142145,187-218,231-232, 279-282,315

338

Subject Index

D Decomposition 223,232-249 Demand characteristics 257,294-295 Depiction 8,25,40,44-47,57,68, 77-95,131, 132,317,321 Description 8, 13,22,77-95,128132, 134,317,321 Designers 5 Developmental perspectives 225-227, 230,249,323 -on creativity 27-28,225-227, 230,249 -on imagery 5, 27-28,225-227, 230,249,323 Diagram 31,255,288,299,300,303, 323,325 Didion, J. 3 Dirac 3 Discovery 3, 12-20,39,40-47,99120, 128,202,225-227.232249 -and imagery 1, 10,42-52 -and mental synthesis task 921,203-218,232-249, 287-309 -and drawing 10, 13-21,40-47, 57,99-105,111, 131, 232-249 -as interpretation 187-218 -constraints on 80-84,102-103, 248-249 -creative 12-20,187-218,231249,255-283 -definition of 189-191,256, 314-316 -models of 124,134-137,142145, 187-195,231-232, 279-282,315 -properties of 188

Domains -conceptual 273-274 Drawing -and discovery 10, 13-21,4047,50, 57,80-91,99-105, 112, 114-117,131,152, 159,210,227,234-249, 3 19 -and reconstrual 40-47,80,99105,110,152,159,227, 319 -as externalized imagery 41, 43,48-69,80,102-110, 137-142,232-249, 323324 Dynamic imagery 100,137,188,323

E Efferent channel 58,66,318,326 Einstein, A. 2,3,4,6,144,188,192, 194,255,288 Emerald-Shapery Center 307-308 Emergent patterns 30,195,197-218, 258,279-283,320 Emotions 5 Enacted imagery 25,162-169 Equivalence, functional 126,128, 133, 143-145,299 Evolutionary perspectives 225,227, 229,230,248-249 -on imagery and creativity 2728, 225,227,229,230, 248-249 Expectations 9 -of experimenter 236-239 -of subjects 236-239 Experimenter bias 236-239,257 Expert-novice comparison 4,6-7,9, 32,324

Subject Index Eye of beholder 241-249 Eye of creator 241-249

F Familiarity 13,21-22,216 Faraday, A. 3,4,5,255 Feynman, R. 3,255 Figure-ground 41-43,48-50,83-84, 87,95,155,158,161,165, 166168,195 -organization 41-42,83-84 -reversals 40,50,82-95,158 Figures, ambiguous 8,22-28,4060, 57,79-95,99-109,135, 137138,140-143,152,289,297, 319 -chefldog 99-104,138,140-143, 159-161,166-168,297 -Jastrow ducwrabbit 8,22-26, 40,48,49,50,66,67, 80-82,85,87-93,95,99107,135, 137-138,140143, 152, 159-168,172182,289,297,319 -Fisher snaillelephant 153, 159, 170-172 -goosehawk 23, 159-160,165, 166-167,297 -Hill wifdmother-in-law 138, 153 -Mach book 23, 153, 158, 168 -Necker cube 39,51,103,107, 138,152,153,158,167 -Rubin vasdface 41, 104, 107, 138,159,161 -Schroeder staircase 103, 107, 138, 152 -Texas 43-47,49,82,83, 100102, 104

339

Figures, embedded 22, 151,214, 223,230,233,289,291 Figures, geometric 111-117 Fleming, A. 287 Form -and fundion 277-283 -preinventive 192-283,315 Franks, J. 29,327 Functional perspective 223-232,249

G Geneplore model 195,279-282,315 -generative phase 195,279-282 -representations 195,279-282 -preinventive structures 195 Goodness -of parts 23, 29-30,110-120, 202-218,230,291,296, 320,324 -of patterns 29-30,110-120, 202-218,223-224,230, 237-240,242-244,291, 296,320,324

H Hawking, S. 288 Heisenberg, W.3 Heuristics 30, 125 Homophone judgments 53-55 Hume, D. 133

I Illumination 1,3 Imagery -ability (see Marks’ Visual Inventory Questionnaire) 78 -and affectivdmotivational systems 5,20,28-29,32,

340

Subject Index

327 - a d l h i t a t i ~ n39-48,8044, ~ 86,93-94,98,134, 158, 289-295,304,319,320, 326-327 -auditory 23,25,50-58,199, 326,327 -definition of 133, 135 -dynamic 100, 137,188,323 -enacted 25, 59,62-29 -functional role of 126-137 -grammar of 129-132 -loss of 83 -motonc 59,60-64,68-69 -static 63,323 Images -amount of detail 173,175 -amount of information 39 -and discovery 4,42-47,99120, 129-145,288-309 -and motivation 5, 20,28-29, 32,327 -construal/reconstrual of 2,2327,40-48,77-95,99-120, 128, 130, 137, 140-145, 152-182,319,321,323, 324 -definition of 125-126,131, 134, 151 -depictive 8,25,40,44-47,57, 68,77-95,131, 132,317, 321 -descriptive 8, 13,22,77-95, 128-132,134,317,321 -detection of 130 -drawing of 10,13-21,40-47, 50,57,80-91,99-105, 110, 112, 114-117,131, 152, 159,210,227,319

-enacted 25-59,62-69 -externalization of 41,43,4869,80,102-110,137-142, 232-249,323-324 -fading of 85,87, 137,142,318 -kinetic 188 -orientation of 42-47,87 -prototypical 88,241 -rotation of 10,28,44-47,64, 78,93-95,97, 100, 157, 233,323 -spatial 6,9,27-32,61-63,135, 223, 228,229,287-309, 317,322 -usefulness of 289-309 -vividness of 63,86 Incubation 1,3 Individual differences 15-19,30-33, 63, 119, 138, 141-142,217-218, 229,249,326 Inner -ear 52, 55-59,65 -eye 60-66,132-134 -scribe 58,60-66 -speech 52,57,65 -voice 52-56,58-59 Intelligence 6-7,194 -,see also Creativity Intentions 79,84,95,128,129,130, 133,135,137,142, 144,317 Interpretation 25, 79,99-120,133, 140-145,152, 161-162,176182,190-203,225,231,257, 314-316,318 -of images 8, 25-27,79-95,99120, 133,140-145,152, 161-162,176-182,255, 231, 232-249,257 -of percepts 25-27,79-95,99-

Subject Index 120,133, 140-145,152, 161-162,171-182,225, 231,232-249 Interference 8,9,12,20-21,52,62, 79, 173 Introspection 78,86,188,256,313 Intuitive spreading approach 225227 Inventions 1-6,39,193-218,258-283, 287-309

K Kekul6, F.A. 2, 181,255 Kim, C.W. 307 Kinesthetic cue 52,59 Kofia, K. 86

L Learning 127 -from images 39-53,78-95 Levels of analysis 224-231 -framework 225-231 Levels of processing 126

M Marks’ Visual Inventory Questionnaire 78 Maxwell, J.C.2, 4, 6,144,288 Meaning 79-95,317 Memory -limited capacity 210,214 -shape 24, 151-182 -working 39-69,101, 125,249, 304,319,326 Mental tasks -construction/reconstmction 927,44-45,79-81,99-120, 138-143,158-180 -discovery 12-20,40-47,99-

341

120,158-180,200-211, 223-227,232-249 -paper-folding 296 -rotation 10,27,44-47,64,78, 93-95,97,100,157,233, 323 -Scanning 42,61,64,78,86, 100,292-295 -sQipts 180 --,see also Schemata -simulation 30,295,309 -synthesis 9-21,236-249,258, 277,296-297,315 -in studies of imagery 109-117 -and creativity 256-259 -traditional methods in 256259 -cognitive science 256-259 Mind‘s eye 132-134,198,200 -,see also Inner Eye Minnesota Paper Form Board 138, 217,229 Models -Anderson and Helstrup’s model of visual discovery 231-232 -Bartlett 99-120 -Biederman’s Recognition-byComponents 156-157 -computational 124,225 -computer simulation 30,295, 309 -connectionist 230 -creativity 187-218,279-282, 315 -depictive 8,25,40,44,57,68, 77-95,131,132,317,321 -descriptionalist 8, 13,22,7795,128-132,134,317,

342

Subject Index

321 -discovery 195,279-282 -dispositional 131 -empiricist 133, 134 -equivalence 133-134 -Finke’s Geneplore 195,279282, 315 - W e ’ s model of imagery 133134 - K a ~ f m a24, ~ ’ 134-137, ~ 142145 - K o s s l ~ ’ 118, s 127 -Paivio’s dual code 127 -pictorialist 132-134,137 -reconstructive remembering 99-120 -Roskos-Ewoldsen’smodel of creativity and discovery 194-197 Motivation 5,20,28-29,327 Motoric imagery 59-64,68-69 Mozart, W.A. 2, 3, 281

N Newton, I. 4 Nicklaus, J. 2 Novelty 10,11, 13, 68,93-95,123, 124, 125,181, 195,216, 218, 241,246,247,248,256,258, 278,279,282,288,303,309, 316 Neurophysiological evidence 64-65, 225-227,230 -Parietal lobe 63-64

0 Organization 291 -Ofparts 188,200-218 Orientation 42-48,82-83,93,95,

100, 157 Originality 258,261

P Pascal, B. 5 Patterns 223,233-249,315 -complexity 234,238 -emergent 199-218,247 -goodness 23,29 -pixel 26, 41,93 -properties of 199 Pauli, W. 3 Perception 24-28,40-45,77-95,99120, 124, 125,133,142, 144, 153,193,195,318,320 Percepts 40-42,77-95,151 Perceptual linkages 42 Personality 194 Philosophical issues 129-137,143145 Phonological coding (store) 52 Physicists 3 Pixel patterns 27,41,93 Plato 1 Play -combinational 9,187-218, 225,258,314-316,318, 320, 325 Poincarb, H.1,3,33 Positron emission tomography (PET) 230,249 Practicality 258,261,273,276 Practice effects 13-21,31-32,216, 323,325 Practical implications 214-217,282283,287-309,317-327 Preinventive forms 195,266-283, 315 Preparation 1, 3, 270

Subject Index Problem -definition 123 -finding 278 -programming 123,144 -solving 30-31,39, 47,123, 127, 181,182,288-309, 316, 325-326 --and use of diagrams 31,255, 288,299,300,303,323, 325 --and illustrations 30,288 --and use of imagery 30,47, 181,288-309 --four stages of 1-3,325 --simulation of 30-31 --transfer t o analogous problems 30-31,288-309 Processes -automatic 194 -controlled 194 Productivity -,see also versatility 15-21 Propositions 22,77-78,124,125, 126,151,181,317

Q Quantum mechanics 3

R Ratings -correspondence 13-21,233247, 258-282 -creativity 13-21,233-247,258282 Recognition 190 -of patterns 44-47,190,198218,290 -of shapes 44-47,153, 157, 172, 173,190,198-218,

343

290 Reconstructive memory 99-120,318 Reconstrual 2,23-27,40-48,77-95, 99-120,128,130,137,140-145, 152-182,319, 321,323,324 -structural 176-180,176-178 Reference-frame 21-27,29, 32,4252,57-58,66,67,84,94,153182 -definition of 23,42,153 reversals 23-27,42-52,58, 290,297-298,319 Rehearsal loop 55-56,58 Reinterpretation 22-27,32,40-50, 77-95,99-110,187,200-218, 227,297,319-322,324 -of ambiguous figures 22-27, 40,50,99-110,200-218 -of images 22-27,40-50,77-95, 99-110,227 Relativity 3 Representation 23-24,31,54,58,7795,145, 156,182,223,227230,238,239,241,288 -analog 75, 124 -conscious 124 -depictive 8,40,44,77-95 -descriptive 8-13,22,77-95 -imaginal 30 -mental 30,54,81,95,288 -pictorial 30,288 -propositional 77-78,124,125, 126, 182 Reversals 23-27,29,52,60,66,67, 79-95,99-110,140-145,152182 --,seealso reconstrual, reinterpretation -figure-ground 140-145

344

Subject Index

-reference-frame 23-27,42-52, 58-66,79 Rhyme judgments 53-54 Rigidity 216 Roskos-Ewoldsen, D. 29,327 Russell, W.12

S Schemata 101,117,119,180,321322 Scratch pad 56 Schrodinger, E. 3 Self-reports 2-7,61, 68,307 -,see also anecdotal accounts Spatial ability 6-7 Spatial inferences 223,228,229, 288,300,303-306,309,317, 322 Static imagery 62-63 Stimulus -geometry 42-49,299-300 -support 41,43,48-69,80, 102110, 137-142,232-249, 323-324 Story construction 8, 101-102,110121 Strategies 101, 117, 119,180,321322 -for creative discovery 197-199, 202-218,236-249,260283 -symbolic 124 Structure -description of 22 -exploratory 260 -invariances of 6 -reconstruals 162 -symmetry in 6,29-30,32, 153,324

-three-dimensional 81, 151, 296,307 Subjects -design students 138-143 -engineering students 296 -gifted 6-7 -unselected undergraduates 10,11-21,28-29,40, 204-211,234,236,276, 283,300,320,324 Subvocalization 25-26,51-62, 66-69 Surls, J. 2, 188,194, 198 Synthesis 9-21,236-249,258,277, 296-297,315

T Tacit knowledge 294-295 Tesla, N. 5,9,287,288 Thinking 127,131,144,270,283, 287 -homospatial 145 Time-sharing 56-58 Training to use imagery 29-31,295309,325 Transfer 15 Transformations 8, 10,145,233, 234,238,324

V Verification 1, 3 Versatility 15-21 -principle of 15 -,seealso productivity 15-21 Vividness 86-87 -Marks' Visual Inventory Questionnaire 6,35,78, 86,95

Subject Index

W Watson, J. 2, 6,287,288 Working memory 39-69,101,125, 249,304,319,326 -articulatory loop 55-56,58 -central executive 56 -limited capacity 210,214, 249,304,318,326 -scratch pad 56 Wright, F.L. 307

345


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