Psychological Bulletin1993. Vol. 113, No. 2, 211-228

Copyright 1993 by the American Psychological Association, Inc.0033-2909/93/S3.00

Comparative Cognition: Beginning the Second Centuryof the Study of Animal Intelligence

E. A. Wasserman

Comparative psychology has undergone many changes since its inception in Victorian Englandsome 100 years ago. Gone are the amusing anecdotes of pet owners and amateur naturalists,replaced by the detailed observations of behavioral scientists made under carefully controlledconditions. Yet, many of the persistent problems in the comparative analysis of intelligence remain:Are the cognitive processes of animals like those of humans? Can researchers construct a phytogenyof intelligence? What is cognition without language? This article briefly reviews the history of thestudy of comparative cognition. It then discusses 2 of the most active and important areas ofempirical inquiry—memory and conceptualization—to acquaint readers with contemporary re-search in the field. Given increased contact with the related areas of cognitive science, behavioralneuroscience, and behavioral ecology, comparative cognition should continue in its 2nd century tomake significant contributions to the overall understanding of the principles of behavior.

How familiar a scene it is. A learned and eloquent scientistgazes upward toward the distant heavens, sighs wistfully, andplaintively asks "Is there life beyond earth? Is that life intelli-gent? If so, can we communicate with it?"

What a noble quest: to search out alien life and to interactwith it. A quest not only noble but also generously funded bygovernmental agencies. Radio telescopes, orbiting satellites,and both staffed and unstaffed cosmic expeditions have beenand will be constructed and undertaken to find extraterrestriallife—at great public expense and with much media fanfare.

I wish not to demean these important efforts but rather tosuggest that an equally challenging and probably more fruitfulsearch for alien intelligence can take place—right here onearth. Thousands of species of animals inhabit this planet,many of them exhibiting notable craft, flexibility, and ingenu-ity in adapting to the numerous challenges of survival. Thecareful and scientific study of our planetmates may shed consid-erable light on the nature of intelligence, on the character ofcognition without language, and on the very possibility of com-munication with extraterrestrial life—if it is ever found. Per-haps most important, comparing the intelligence of many spe-cies of animals may help us know better what it means to behuman.

Although the study of animal intelligence has been an ongo-ing concern of scientists for some 100 years—Romanes's (1883/1977) classic book, Animal Intelligence, was published in 1883—most people know very little about it. The present popularityof many nature programs on television plus the great publicitythat several research projects on animal behavior have recentlyreceived suggest that now might be an opportune time to out-

I thank G. Burghardt, H. Davis, M. Rilling, D. Rumbaugh, N. Spear,and L. Van Hamme for their editorial and technical help in preparingthis article.

Correspondence concerning this article should be addressed to E. A.Wasserman, Department of Psychology, University of Iowa, Iowa City,Iowa 52242.

line for both specialists and nonspecialists the essentials of thescientific field known as comparative cognition. In addition,recent developments in human cognitive psychology have againmade the study of animal intelligence central to a traditionalgoal of psychology: namely, "to view complex human abilitiesas emerging from configurations of elementary associative pro-cesses that could be studied in simple organisms" (Gluck &Bower, 1988, p. 227).

This reassessment stands in stark contrast to earlier dis-missals of animal behavior and cognition as irrelevant to thehuman species. By way of illustration, one trio of textbookauthors justified their near-total disregard of nonhuman intel-ligence thusly:

Whenever higher mental processes are involved, we heartily dis-agree that human and animal behavior are necessarily governedby the same principles. We regard the human as a specializedproduct of evolution, as an animal whose cognition is also special-ized. This means that humans and animals may share some cogni-tive abilities, but it is not a foregone conclusion that they do.(Lachman, Lachman, & Butterfield, 1979, p. 42)

Although it would be foolhardy to conclude on the basis ofexisting evidence that there are no substantial differences inhuman and animal cognition, it is far better to examine thematter with an open mind than from the prejudiced perspec-tive of anthropocentrism. Thus, the present article explores thequestion of animal intelligence from, I hope, an objective andcomparative vantage point.

In pursuit of this overall objective, the present article firstsketches a bit of the interesting history of comparative cogni-tion and then introduces two of its most important and activeresearch areas: memory and conceptualization. Additional dis-cussion concerns numerical competence and language behav-ior and the place of comparative cognition within the biology ofbehavior.

Readers should be warned that in a review such as this, it isimpossible to do full justice to all areas of relevant research orto give full credit to all past and present workers in the field.

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212 E. A. WASSERMAN

Although I make no claims to comprehensiveness and thor-oughness, I do believe that the present article effectively intro-duces the field of comparative cognition to newcomers andusefully reviews and discusses key topics and theories for indi-viduals who already have some knowledge of the field.

Readers should be further warned that clear and detaileddefinitions of many important terms—indeed that of intelli-gence itself—are not given in this article; nor are they given inmost others on comparative cognition. It may be far simpler toprovide precise operational definitions of elements or aspects ofintelligence than to give a good definition of the overarchingconcept—for animals or people (for more on the definition ofhuman intelligence, see Sternberg, 1986; for more on broaderconceptions of human and animal intelligence, see Stenhouse,1973).

Historical Perspective

Evolutionary Theory

In the middle of the 19th century, in England, HerbertSpencer and Charles Darwin proposed that the minds as well asthe bodies of animals had undergone a process of organic evo-lution. Living animal species can thus be compared—behav-iorally and anatomically—with the resulting similarities anddifferences providing important clues to the ancestry of behav-ioral and anatomical traits.

Since then, considerable progress has been made in elucidat-ing the structural evolution of animals. Much less progress hasbeen recorded in understanding the evolution of their intelli-gence. Beyond the obvious problem that most behavior doesnot fossilize, many actions that one characterizes as intelligentare not those that are common to all members of a species;instead, these intelligent actions are the often idiosyncratic re-sponses that individual animals exhibit to specific environmen-tal problems or circumstances. This fact means that properdocumentation of animal intelligence requires not only carefulrecording of the relevant behavior but also precise knowledgeand even control of the pertinent environmental variables. Thelatter point is of real historical significance, given the somewhatawkward start that Darwin and his student, George J. Ro-manes, gave to the field of comparative cognition.1

Methodology and Evidence

Both Darwin and Romanes had a clear agenda. They be-lieved that support for the theory of the evolution of intelli-gence could come by documenting a continuity of cognitionamong living animal species. Such documentation was initiatedby collecting literally hundreds of tales of animal genius, asrelated by pet owners, naturalists, and zookeepers. Take, forinstance, this tale of feline guile by one of Romanes's (1883/1977) friends:

Our servants have been accustomed during the late frost to throwthe crumbs remaining from the breakfast-table to the birds, and Ihave several times noticed that our cat used to wait there in am-bush in the expectation of obtaining a hearty meal from one ortwo of the assembled birds. Now, so far, this circumstance in itselfis not an "example of abstract reasoning." But to continue. For thelast few days this practice of feeding the birds has been left off.

The cat, however, with an almost incredible amount of fore-thought, was observed by myself, together with two othermembers of the household, to scatter crumbs on the grass with theobvious intention of enticing the birds, (p. 418)

As might be surmised from this vignette, the early anec-dotists were not always impartial observers of behavior norwere they necessarily careful recorders of either the behavior inquestion or the conditions that promoted the behavior. As inter-esting and suggestive as these anecdotes were, they could notstand the tests of scientific scrutiny, as they were of dubiousobjectivity and replicability. The anecdotal method simplywould not do to establish a science of comparative cognition, apoint made forcefully by C. Lloyd Morgan (1894/1896).

A countryman of Spencer, Darwin, and Romanes, Morgan(1894/1896) is often credited with stimulating the scientificstudy of animal intelligence by investigating the behaviors ofnewly hatched chicks reared without their mother. Morgan rea-soned that with very young animals, he could more effectivelylimit and control the individual's prior experience; and withmaternal isolation, he could remove the confounding influenceof imitation on the behaviors he observed. Although Morgan'svarious research projects seem quaint and amateurish by to-day's standards (they were conducted in his own poultry yard),they set the stage for the more powerful and refined methods ofPavlov and Thorndike.

As most students of behavior are aware, I. P. Pavlov, in Russia,and E. L. Thorndike, in the United States, developed highlyreliable and objective methods for investigating associative con-ditioning in animals. It is a fair conclusion that most progress inthe experimental investigation of comparative cognition hasbeen the consequence of the creative application or modifica-tion of their two basic methodologies. Later, I review a sam-pling of that empirical evidence.

Interpretation

The Darwinian agenda not only sought to blur any sharpdivisions between human and animal intelligence, but also itinterpreted animal behavior in terms of human behavior andprivate experience. This anthropomorphic bias is implied inDarwin's (1871/1920) declaration of mental continuity betweenhumans and animals:

The difference in mind between man and the higher animals,great as it is, certainly is one of degree and not of kind. We haveseen that the senses and intuitions, the various emotions and facul-ties, such as love, memory, attention, curiosity, imitation, reason,etc., of which man boasts, may be found in an incipient, or evensometimes in a well-developed condition, in the lower animals.(p. 128)

The question of mental continuity was also of concern toDarwin's student, Romanes. He hypothesized that there might

' Most historians have been very harsh in their criticisms of Ro-manes's contributions to comparative psychology. However, more re-cent discussions of his ideas have cast the work of Romanes in a muchmore favorable light (see Rilling, 1992, for a discussion of Romanes'suncelebrated experimentation on counting in chimpanzees, and seeWasserman, 1984, for a more general consideration of Romanes's influ-ence on comparative psychology).

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 213

be a cognitive scale roughly paralleling the phylogenetic scale.Placement along this scale could be determined by objectivebehavioral tests: Can animals learn to behave in accord withspecific situational demands deemed necessary to evidencesome cognitive capability, such as memory, association by con-tiguity, reason, or communication? If so, then they must possessthat mental capacity.

Romanes (1884/1969) constructed an elaborate chart tracingthe representation of numerous cognitive processes throughoutthe animal kingdom. As one progresses from more primitive tomore advanced organisms, more advanced forms of cognitionare assumed to be added to less advanced ones.2 Thus, althoughhumans may sit at the summit of intelligence, humans mayshare with animals a number of cognitive capabilities, that num-ber decreasing as evolutionary kinship becomes more remote.

Romanes (1884/1969) also made an important effort to dis-tinguish the objective and subjective aspects of animal behav-ior. As the following passage illustrates, Romanes saw thatovert action and subjective experience cannot be equated.Whereas one might judge that the performance of similar re-sponses by humans and animals implies the operation of com-mon cognitive or emotional processes, any subjective experi-ences that may accompany those behaviors are inherently pri-vate; their existence can only be hypothesized by analogy withhuman experience.

Now, by mind we may mean two very different things, accordingas we contemplate it in our own individual selves, or in otherorganisms. For if we contemplate our own mind, we have an imme-diate cognizance of a certain flow of thoughts or feelings, whichare the most ultimate things, and indeed the only things, of whichwe are cognizant. But if we contemplate mind in other organisms,we have no such immediate cognizance of thoughts or feelings. Insuch cases we can only infer the existence and the nature ofthoughts and feelings from the activities of the organisms whichappear to exhibit them. (Romanes, 1883/1977, p. 1)

From its earliest years, comparative psychologists have foundit extremely tantalizing to speculate on the nature of consciousexperience in animals (for a review, see Burghardt, 1985). Noless than Morgan (1894/1896) championed the use of intro-spection in the interpretation of animal behavior:

The wise and cautious student never forgets that the interpretationof the facts in psychical terms is based upon the inductions he hasreached through introspection. The facts are objective phenom-ena; the interpretation is in terms of subjective experience, (p. 47)

Even today, we find Griffin (1976,1978) insisting that subjec-tive animal experience falls within the proper province of thefield of comparative cognition (what he calls "cognitive ethol-ogy"—see upcoming discussion).

However tempting it may be to project onto animals one'sown thoughts and feelings, most workers in the field of compar-ative psychology have deliberately resisted that temptation.One of the earliest behavioristic students of animal behavior,H. S. Jennings (1904/1976), recognized the unverifiability ofconsciousness as an accompaniment to action:

It is clear that objective evidence cannot give a demonstrationeither of the existence or of the non-existence of consciousness,for consciousness is precisely that which cannot be perceived ob-

jectively. No statement concerning consciousness in animals isopen to refutation by observation and experiment, (pp. 335-336)

His more celebrated contemporary, J. B. Watson (1913), evenmore vigorously asserted that "I have virtually denied that thisrealm of psychics is open to experimental investigation" (p.175). In addition, the late B. F. Skinner (1977) commented onthe regressive and unproductive character of mentalistic analy-sis, according to which

a science of animal behavior must be replaced or supplemented bya science of animal feelings. It would be as extensive as the scienceof behavior because there would presumably be a feeling for eachact. But feelingsare harder to identify and describe than the behav-ior attributed to them, and we should have abandoned an objec-tive matter in favor of one of dubious status, accessible onlythrough necessarily defective channels of introspection, (p. 3)

The present state of research and theory in comparative cog-nition is strongly rooted in the experimental investigation ofprecisely controlled and recorded animal behavior. Interpreta-tions usually center on the mechanisms and processes of cogni-tion rather than on the nature or contents of subjective experi-ence. In addition, considerable attention is paid to the biologi-cal substrates of cognition, with due regard for the fact that anunderstanding of the biology of intelligent behavior is verymuch a long-term goal.

Considered next are two key areas of research in comparativecognition—memory and conceptualization—so that one maygain a clearer appreciation of the progress that has been madein evaluating the thesis of mental continuity between humansand animals. It is made evident that although some of the re-search is truly comparative, other work seeks primarily to ex-pand the known cognitive competencies of animals. Learningthe limits of animal cognition is one of the most active avenuesof contemporary investigation (Wasserman, 1981). Fully docu-menting the known competencies of animal cognition allowsresearchers to better ascertain whether similar behavioral re-sults in humans may be due to the operation of the same biologi-cal processes or mechanisms.

Animal Memory

"The most fundamental principle of mental operation is thatof memory, for this is the conditio sine qua non of all mentallife" (Romanes, 1884/1969, p. 35). These lines by Romanesexpress in the strongest terms the centrality of memory to anunderstanding of cognition in behavior. Even a cursory surveyof the most prestigious periodical in human cognition—theJournal of Experimental Psychology: Learning, Memory, andCognition—will reveal the continued prominence of the studyof memory in humans since the early work of Ebbinghaus. Yet,despite Romanes's early pronouncement and the vast body ofresearch on human memory, the systematic study of memoryhas not historically been a prime focus of workers investigatingthe behavior of animals under controlled laboratory condi-tions.

2 Incidentally, Romanes also assumed that the same accretion ofcognitive capabilities occurs as a human develops from birth to adult-hood.

214 E. A. WASSERMAN

Several factors probably contributed to the lack of experimen-tal attention paid to animal memory. First, initial interest cen-tered on associative learning as a result of the pioneering effortsof Pavlov and Thorndike. To Watson (1913) and the other earlybehaviorists, little else seemed to be necessary to understandthe intelligence of organisms than their learning of stimulus-response associations. Second, extreme conservatism governedthe analytical efforts of the early behaviorists. Morgan (1894/1896) had persuasively argued against the interpretive excessesof attributing gratuitous cognitive processes to animals whensimpler processes seemed to do, and most later researchersabided by his famous "canon of parsimony." Finally, whereasthe basic procedures of Pavlov and Thorndike served the earlyinvestigators of animal learning exceedingly well, the more elab-orate techniques necessary for studying memory were notnearly as well developed. W. S. Hunter (1913) did devise thedelayed-response paradigm, in which, after a delay, an animalmight identify which of several potential food sites it earlier hadseen baited. Yet, successful performance in this task might notbe the result of some enduring cognitive or neural process; itmight as well have been due to the animal merely maintainingits bodily orientation to the baited site during the delay period(see Fletcher, 1965, for further discussion of such "behavioralmediation").

The past 2 decades have seen a veritable explosion of interestin the experimental investigation of memory in familiar labora-tory animals like rats, pigeons, and monkeys. In part, this devel-opment is due to a realization that learning alone is incapableof explaining intelligent action; other cognitive processes likememory, attention, and conceptualization must also promoteadaptive behavior in complex and changing environments.Also critical to the rise in the study of animal memory has beenthe emergence of new experimental techniques with sufficientpower and reliability to disclose clearly the operation of mem-ory and other cognitive processes.

Let's now consider the contemporary study of animal mem-ory—particularly short-term memory—to gain a fuller under-standing of the methods, results, and theories with which mostworkers have been concerned (see Spear, Miller, & Jagielo,1990, for a broader review of the areas of animal memory andlearning).

Basic Methods and Findings

Quite independently, J. Konorski (1959), in Poland, and D. S.Blough (1959), in the United States, reported two delayed dis-crimination methods that have come to be standard techniquesin today's investigation of animal memory.

In one version of Konorski's (1959) procedure (Wasserman,1976), pigeons view two visual stimuli in succession on anickel-sized pecking key. Each member of a pair of stimulimight be presented for 5 s, with a variable time interval betweenthem. In the delayed matching-to-sample paradigm, foodwould follow the second (or test) stimulus if it was the same asthe first (or sample) stimulus, but food would not follow thesecond stimulus if it was different from the first. By measuringthe pigeon's rate of response to the test stimulus on trials withmatching or nonmatching sample and test stimuli, one canassess the degree to which memory of the first stimulus controls

responding to the second. It so happens that pigeons peck theresponse key at high rates when food is likely but at low or zerorates when food is unlikely. With a short (1-s) interval betweensample and test stimuli, the rate of response to the test stimuluson matching trials may exceed that to the test stimulus onnonmatching trials by a factor of 10 or more. However, as thesample-test delay is lengthened, the response rate differentialdeclines in an extremely orderly way. This inverse relation be-tween delay interval and differential test responding docu-ments the forgetting of sample information.

In Blough's (1959) procedure, two or more simultaneouslypresented test stimuli follow the sample stimulus.3 Only one ofthem is correct and leads to food if chosen; any other selectiondoes not lead to food. In the delayed matching-to-sample para-digm, one of the test stimuli is the same as the sample and theremainder are different from the sample. With a short intervalbetween the sample and test stimuli, pigeons showed a strongtendency to peck the correct (matching) test stimulus. How-ever, as the sample-test delay is lengthened, choice accuracydeclined, again documenting the forgetting of sample informa-tion.

The essential difference between these methods is that withKonorski's (1959) procedure the animal must decide whether torespond to the test stimulus, whereas with Blough's (1959) pro-cedure the animal must decide to which test stimulus to re-spond. This procedural difference notwithstanding, the twomethods produce highly similar results. Thus, not only doeseach technique yield a decline in memory as the sample-testinterval is lengthened under the delayed matching-to-sampleparadigm, but also discriminative performance in each case isdirectly related to the duration of the sample stimulus and thetime between trials (e.g., Nelson & Wasserman, 1978; Roberts &Grant, 1976).

An important variant of each general method involves sam-ple and test stimuli drawn from different item pools. Thus,animals might be shown different colors as sample stimuli anddifferent forms as test stimuli. No physical matches are possi-ble; only arbitrary or symbolic matches can hold. (In a particu-lar version of Konorski's, 1959, procedure, then, food wouldonly follow red-square and green-circle sequences but not red-circle and green-square sequences.) This so-called delayed "sym-bolic" matching-to-sample procedure has afforded researchersspecial opportunities to expand the investigation of animalmemory.

So, with true matching-to-sample procedures, it has beenshown that pigeons can remember the color of a sample stimu-lus, its shape, its orientation, and its spatial location (for a reviewsee Spear et al., 1990). However, with the symbolic matching-to-sample procedure, it has also been possible to show that tem-poral aspects of a stimulus can be remembered. Thus, pigeonsgiven Konorski's (1959) method remembered different dura-tions of a red sample stimulus and reported that memory dur-ing test stimuli of differing line orientations (Wasserman, De-Long, & Larew, 1984). They remembered not only two verydifferent stimulus durations (2 s and 16s), but also a whole range

3 Actually, his is a delayed version of Skinner's (1950) matching-to-sample technique.

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 215

of more or less different durations (1,2,3,4,5,6,7, and 8 s), andsample-test durations as long as 16 s.

Beyond the attributes of single sample stimuli, pigeons givenembellished versions of the symbolic matching-to-sample para-digm have also been shown to remember the temporal order(e.g., red-green) of a series of two different color sample stimuli(Weisman, Wasserman, Dodd, & Larew, 1980), the spatialorder (e.g., left-right) of a series of two identically colored sam-ple stimuli (Wasserman, Nelson, & Larew, 1980), and the rela-tive duration (e.g., short-long) of a series of two different colorsample stimuli (Dreyfus, Fetterman, Smith, & Stubbs, 1988).Furthermore, rats have successfully been trained to press one oftwo levers, depending on the number of prior auditory stimuli(two or four) in a simplified version of Blough's (1959) proce-dure (Fernandes & Church, 1982; also see Davis & Albert,1986). (A later section of this article considers related aspects ofnumerical discrimination.)

Yet another way in which the memory of complex informa-tion has been studied has involved sample stimuli comprisingtwo or more manipulable attributes or elements (Riley & Roit-blat, 1978). Pigeons were thus shown two-element samples com-posed of color (red or green) and line orientation (horizontal orvertical) elements. Using Blough's (1959) method, tests withjust color comparisons or just line comparisons each yieldedhighly accurate performance, implying that both the color andthe line orientation information of the compound samples werediscriminated and remembered by the pigeons. Significantly,accuracy on these compound sample (color and line) trials waslower than on other trials involving only element samples (coloror line), suggesting that the two sources of sample informationon compound trials competed with one another for what inhumans is called divided attention (for more on this "dividedattention" notion see Brown & Morrison, 1990, and Riley &Brown, 1991).

Flexibility of Memory

Early in the modern era of memory research, it was proposedthat memory might be explained by analogy with a simple elec-tronic component—the capacitor. In the same way that electri-cal charge grows in the capacitor when current is applied to it,the strength of a memory trace might grow, the longer the sam-ple stimulus is observed; and in the same way that electricalcharge dissipates from the capacitor when current is drawnfrom it, the strength of a memory trace might fade, the longer ithas been since the sample stimulus has been observed. Al-though the initial evidence supported this "trace" theory ofanimal memory (Roberts & Grant, 1976; also see Guttenberger& Wasserman, 1985), more recent research indicates that ani-mal memory is far more intricate and flexible than is impliedby a capacitorlike trace.

Cuing the delay interval. Suppose that, in the delayed match-ing-to-sample paradigm using either the Konorski (1959) or theBlough (1959) procedure, subjects are given additional infor-mation during the sample stimulus concerning the length of theupcoming delay interval (Wasserman, Grosch, & Nevin, 1982).With two delay intervals (e.g., 2 s and 8 s), two stimuli (e.g., a toneand white noise) can be used to cue those delays. When perfor-mance here is compared with a control condition in which the

added stimuli are completely uncorrelated with the upcomingdelay intervals, the correlated condition enhances memory atthe short interval but impairs memory at the long interval.Further evidence that delay interval signals affect memory per-formance comes from tests in which a short delay is cued but along delay is given and in which a long delay is cued but a shortdelay is given. Cuing a short delay but giving a long one im-proved memory above that obtained at the correctly cued longdelay; cuing a long delay but giving a short one impaired mem-ory below that obtained at the correctly cued short delay.

Just where in the sequence of events (sample stimulus, delayinterval, test) the delay cue is exerting its effect and how it isdoing so is not yet known, although one possibility is that dif-ferential attention is paid to the short- and long-cued samples(for more on this issue, see MacDonald & Grant, 1987; andWasserman et al., 1982). What is known is that delay intervalcuing similarly affects human memory performance. Humans,too, show a steeper memory function—with better memory atshort delay intervals but poorer memory at long delay intervals—on a paired-associate immediate memory task when infor-mative time tags are provided than when they are not (Hinrichs&Grunke, 1975).

Cuing the test stimuli. Imagine that one were to combinetrue and symbolic matching-to-sample paradigms withinBlough's (1959) general procedure. Here, each of the two samplecolors would require choice of its same color stimulus whenboth colors were shown as the test stimuli; each of the twosample colors would also require choice of a specific line orien-tation when both line orientations were shown as the test stim-uli. If color tests and line tests were equally likely and unpredic-table, one might suspect that this task would pose no specialchallenge for the pigeon, as its memory for the color of the priorsample stimulus should afford it the means of choosingcorrectly on each type of test: color or line. Now, imagine thataccompanying each sample stimulus is one of two forms thatare perfectly correlated with the upcoming test dimension: Asuperimposed circle signals a color test and a superimposedtriangle signals a line orientation test. Here, there could be adecided advantage to the bird's discriminating and using theform cues; advance warning of the test dimension might enableit to prepare for the upcoming test and to set itself to respond tojust one particular stimulus. Without correlated test dimensioncues, the animal would have to engage in more elaborate andpossibly more difficult preparations and to set itself to respondto two particular stimuli depending on the nature of the testitems. Note that test dimension cuing would have an advan-tageous effect only if there were an anticipatory or expecta-tional aspect to animal memory. A decay or trace theory wouldlead one to predict that test dimension cuing would have noinfluence on memory.

To see if cuing the test dimension has any effect on memory,Stonebraker and Rilling (1984) gave pigeons initial trainingunder the previously mentioned conditions and then occasion-ally miscued the test dimension, giving a color test after thetriangle and a line test after the circle. Memory on miscuedtrials was much poorer than was memory on correctly cuedtrials, thereby suggesting that subjects had come to anticipateparticular test stimuli after particular prior cues. As in delayinterval cuing, researchers have much more to learn about how

216 E. A. WASSERMAN

precuing affects memory (see Grant & MacDonald, 1990, andSanti, Musgrave, & Bradford, 1988, for more on this issue). Yet,these and other data indicate that anticipatory or expectationalprocesses are importantly involved in animal memory (Honig& Dodd, 1986; Honig & Thompson, 1982; Wasserman, 1986)and human memory as well (Cohen, 1989).

Directed forgetting. Within the domain of research on hu-man memory, it is customary to posit the operation of controlprocesses: means by which memories are modulated in accor-dance with the needs of the individual or the demands of thetask (Atkinson & Shiffrin, 1968). By their very nature, controlprocesses comprise many of those flexibilities and intricaciesof memory that fall outside the scope of trace theories.

One such key control process is rehearsal. It is often said thatrehearsal is a covert activity that helps to sustain the memory ofsome prior event. Whereas engaging rehearsal should aid inretaining earlier information, terminating rehearsal should im-pair retention. To investigate the role of rehearsal in humanmemory, workers have developed the so-called directed-forget-ting paradigm (Bjork, 1972). In one version of the paradigm,shortly after presentation of the trial stimulus, subjects aregiven one of two cues (e.g., red or green colors) either to re-member or to forget the prior stimulus. Here, it is generallyfound that when memory tests are given, retention is far worseon forget-cue trials than on remember-cue trials, implying thatthe poststimulus cues were affecting the rehearsal process andthereby modulating memory. It has further been found thatpostponing the forget cue in a delay interval of fixed durationleads to a loss in its effectiveness; that is, memory for earlierinformation improves the later into the delay interval the forgetcue is given (Weiner & Reed, 1969). This result suggests thatspontaneous or uncued rehearsal before the forget cue protectsthe memory from the decremental effect of the forget cue.

Beginning with a study by Maki and Hegvik (1980), severalworkers in the area of animal memory have endeavored toascertain whether directed forgetting is uniquely human. Re-search with both pigeons (Grant, 1984; Maki, 1981; Rilling,Kendrick, & Stonebraker, 1984) and monkeys (Roberts, Maz-manian, & Kraemer, 1984) has adapted the delayed matching-to-sample paradigm to this end by adding brief postsamplecues to signal that a test for sample memory either would orwould not be given. As in the case of human memory, animalmemory proved to be much lower on forget-cue trials than onremember-cue trials. In addition, memory was more markedlyreduced if the postsample cue was presented early than if it waspresented late in the delay interval (Grant, 1981; Stonebraker &Rilling, 1981).4

Serial position function. Further evidence inconsistent withtrace theory is well established in the area of human verbalmemory. There, it is frequently found that memory for a seriesof items is a "bowed" function of input position: memory beinghigh for initial (primacy) and terminal (recency) items but lowfor items in intermediate input positions (e.g., Crowder, 1976).Whatever else the bowed serial position function means fortheories of memory—primacy perhaps reflecting long-termmemory and recency reflecting short-term memory—it cer-tainly violates the monotonically increasing function predictedby trace theory.

Is this bowed serial position function demonstrable in non-

verbal animals? Yes, say Wright, Santiago, Sands, Kendrick,and Cook (1985). They trained both pigeons and monkeys on aserial-probe-recognition task. Lists of color slides were pro-jected one at a time on the upper of two rectangular screens.Each of the four list items—all different from one another—was shown for 1 s (monkeys) or 2 s (pigeons) with a 1-s intervalbetween items. A probe item was projected on the lower screensome time after the fourth list item. If the probe item was arepeat of one of the list items ("same" trial), then a response tothe right-hand manipulandum was correct and was reinforcedwith food or drink; if the probe item had not been presented inthe prior four-item list ("different" trial), then a response to theleft-hand manipulandum was correct and was reinforced.When 1 s to 2 s for pigeons or 1 s to 10 s for monkeys separatedthe final list item and the probe test, memory for List Items 1and 4 exceeded memory for List Items 2 and 3, thus reproduc-ing the classic bowed serial position memory function. Atshorter list-test delays, the serial position function rose mono-tonically; at longer list-test delays, the serial position functionfell monotonically. Not only did the primacy and recency por-tions of the serial position curve greatly depend on how longafter the last list item the probe test was given, but also pre-cisely the same changes in memory performance held for hu-mans tested under similar circumstances.5

These and other results thus suggest that animal memory isfar more complex and flexible than was once thought and thatsimilar control processes may modulate both human and ani-mal memory. Such empirical parallels are, of course, all themore significant given that the nonhuman animals in all ofthese investigations were nonverbal creatures.

Conceptual Behavior

Humans and other animals are constantly confronted withan extraordinarily complex array of external stimuli. Yet, senseis somehow made of these varied and varying stimuli. One wayof reducing the demands on an organism's sensory and infor-mation-processing systems is for it to treat similar stimuli asmembers of a single class; by so doing, substantial cognitiveeconomy can be achieved, thus freeing its adaptive machineryto deal with other competing exigencies of survival. In addition,categorical processing permits an organism to identify novelstimuli as members of a particular class and to generalize knowl-edge about that category to these new members. Thus, an organ-ism need not be bound to respond to only those stimuli withwhich it has had prior experience, correspondingly enhancingits ability to cope with a continually changing world.

Although theorists have often extolled these adaptive virtuesof categorization and conceptualization, we remain far fromunderstanding exactly how organisms process stimuli so as to

4 Further discussion of directed forgetting and alternative accountsof it can be found in Kendrick and Killing's (1986) book, in which theyalso consider a broad range of animal memory phenomena.

5 Further evidence on the serial position effect can be found in Bu-chanan, Gill, and Braggio (1981), in Reed, Chih-Ta, Aggleton, andRawlins (1991), and in Kesner and Jackson-Smith (1992). The last arti-cle also considers the neural mechanisms of human and animal mem-ory processes.

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 217

partition the world into classes of related objects and events.Indeed, given early writings on the subject, we should wonderwhether nonhuman animals are even capable of conceptualbehavior. Nearly a century ago, Morgan (1894/1896) deniedanimals the ability to behave conceptually. To do so, he said,requires that

we neglect all that is variable and focus the attention on the uni-form relation. [Then] we have reached a conception, and this con-ception is not concrete, particular, and individual, but abstract,general, and of universal application, (p. 263)

Morgan believed that only adult humans (not even children) arecapable of conceptualization. Several recent lines of evidenceare radically changing that initial opinion.

Object Concepts

One familiar instance of conceptual behavior involves thekind of open-ended categorization response one makes whenone labels different natural (e.g., cat) and human-made (e.g.,chair) objects with different nouns. Such verbal behaviors areoccasioned by specific instances of wide variability and individ-uality. Indeed, accurate classification even extends to categori-cal exemplars never seen before. Is it at all possible for nonhu-man animals lacking language to engage in this form of concep-tual or classifactory behavior?

To answer this question with regard to the familiar labora-tory pigeon, a new technique was devised to train it concur-rently to discriminate stimuli from several human languagecategories. The specific method (Bhatt, Wasserman, Reynolds,& Knauss, 1988, Experiment 1) was based on the techniqueparents often use to teach their children to label objects in apicture book—the "name" game. When the page is turned, thechild is asked to look at the object and then he or she is re-quested to name it. If he or she is correct, praise is the reward. Ifhe or she is incorrect, the result is encouragement to try again.Finally, if self-correction fails, he or she is provided with thecorrect name. To implement this method with pigeons, a colorsnapshot was displayed on a 3-in. square frosted plastic screen,and the pigeon was required to peck a clear plastic key coveringthe screen 30 times. Completing this observing response re-quirement led to the illumination of four different color keysjust beyond the corners of the viewing screen. A single choiceresponse was then permitted. If it was to the correct key forreporting the stimulus on the viewing screen, all of the visualstimuli were turned off and the pigeon was fed mixed grain; ifthe response was to any of the three incorrect report keys, allreport key lights were turned off and the trial was repeated.Only the first choice response of a trial was scored; correctiontrials were not considered in analyses of performance. In sev-eral studies, the 40 slides seen in each daily session depicted 10different examples each of cats, flowers, cars, and chairs. Thepictures contained one or more instances of the critical stimu-lus object; the objects were indoors or outdoors; near or faraway; centered or off center; and in different colors, orienta-tions, and backgrounds.

In one representative experiment (Bhatt et al., 1988, Experi-ment IB), a group of four pigeons attained a mean level ofdiscriminative performance of 76% correct during Days 26 to

30 of training, after beginning the investigation near the chancelevel of 25% correct. Also noteworthy were the results of 2 laterdays of test performance with the 40 original training slides andwith 40 brand-new slides of cats, flowers, cars, and chairs.Mean accuracy to old slides was 81%, and to new slides it was64%. Although test performance was highly discriminative toboth sets of stimuli, accuracy was reliably higher to old than tonew pictures, perhaps because the birds remembered some orall of the old slides. Finally, there was no evidence for any of thestimulus categories being harder or easier for the pigeons todiscriminate (contrary to the suggestion made by Herrnstein,1985, that pigeons cannot categorize human-made stimuli).Thus, pigeons are able concurrently to categorize stimuli fromfour classes of natural and artificial objects and also to extrapo-late that categorization to completely novel test stimuli, albeitat a somewhat lower level of accuracy.

Perhaps even more important were the results of a subse-quent investigation (Bhatt et al., 1988, Experiment 3) in which alarge pool of 2,000 unique snapshots (500 from each of fourcategories) were shown to pigeons on a one-time-only basis.Without the benefit of any stimulus repetition, the birds at-tained a mean accuracy level of 70% correct on Days 46 to 50.Either the pigeon has an undocumented ability to remember arather large number of stimuli it has seen only once (cf. Vaughan& Greene, 1984, who showed that pigeons can remember up to320 pictures seen at least 28 times each) or it can abstract somekind of generic or prototypical information from varied stim-uli, as implied by Morgan's (1894/1896) earlier quotation andby several more recent models of conceptualization (Smith &Medin, 1981).

It is surely no small matter to demonstrate that nonverbalanimals like pigeons are so adept at categorizing snapshots ofreal objects (also see Herrnstein, 1985). Yet, one is bound towonder just how similar this feat is to the conceptual behaviorof humans. Here, two additional projects suggest that the simi-larity may be more than accidental.

In one investigation (Wasserman, Kiedinger, & Bhatt, 1988,Experiment 2), two groups of four pigeons were trained to cate-gorize the same set of 80 snapshots. The first (or true category)group had to peck one of four keys to report each of 20 stimulifrom four human language categories: cats, flowers, cars, andchairs. The second (or pseudocategory) group had to classifythe very same slides into random assortments, in which each ofthe four pseudocategories comprised equal numbers of cat,flower, car, and chair slides. Over Days 37 to 40 of training,pigeons on the true categorization task averaged 79% correct,whereas pigeons on the pseudocategorization task averagedonly 44% correct (a small but reliable rise from 25%). Thus,learning proceeded far faster when the to-be-trained categoriescoincided with human language classes than when they did not.These and other results (Astley & Wasserman, 1992; Edwards &Honig, 1987; Herrnstein & de Villiers, 1980; Wasserman et al.,1988, Experiment 1) suggest that to pigeons, members of hu-man language categories resemble one another more than theyresemble members of other language categories. The pigeon'scategorization behavior thus confirms the nonarbitrary natureof human language terms, at least for the object categories theyhave thus far been given.

In another project (Bhatt, 1988), three groups of four pigeons

218 E. A. WASSERMAN

were trained to categorize photographic slides. The threegroups of pigeons were given 48 daily training trials comprising12 copies of 1 example from the categories cat, flower, car, andchair (Group 1); 3 copies of 4 examples from the same catego-ries (Group 4); or 1 copy of 12 examples from the same catego-ries (Group 12). The rate of learning to a criterion of 70%correct was an inverse function of the number of examples percategory. Of additional importance were the results of a general-ization test with 32 novel stimuli, 8 from each category. Here,accuracy was a direct function of the number of examples givenduring training. The mean percentages of correct choices ongeneralization test trials were 27% for Group 1,45% for Group4, and 62% for Group 12. Thus, although increasing the diffi-culty of original learning, greater numbers of training examplesper category enhance the accuracy of generalization perfor-mance, perhaps because of the increased likelihood that anygiven test stimulus will resemble one or more of the remem-bered training stimuli or because abstracted prototypes aremore representative of the entire class the greater the number ofexemplars seen (Smith & Medin, 1981). Not only are these dataorderly, but they neatly correspond with a large body of re-search on categorization in humans (reviewed by Homa,Burrel, & Field, 1987) and with a recent report on two-categorydiscrimination in pigeons with 5 vs. 35 examples of black-and-white bird and mammal sketches per category (Cook, Wright,& Kendrick, 1990). Whether such interesting correspondencesin conceptualization by humans and animals will continue tobe found is surely to be explored in future research.

Abstract Concepts

One of the empirical hallmarks of conceptualization is theindependence of discriminative responding on the specific de-tails of the prevailing stimuli. Thus, it was imperative in workon object concepts to show that discriminative responding es-tablished to a set of training stimuli also extended to a set ofuntrained test stimuli. To have conceptualized chairs requiresthat new chairs occasion the same response as old ones. Aneven more abstract level of conceptualization may be achievedwhen organisms attach the terms same or different to a pair ofsimultaneously or successively presented stimuli. (With succes-sively presented stimuli, the terms novel or familiar would simi-larly suggest an abstract level of conceptualization.) Here again,the critical test comes when new pairs of stimuli are given to seewhether the organism appropriately labels untrained stimuli.

Matching to sample. One setting in which acquisition of asame-different concept has been studied is the matching-to-sample paradigm discussed earlier. The success of pigeons intheir original mastery of this task might suggest that matchingto sample would readily transfer to new stimuli. However, sucha result has not been obtained (for reviews and critical analysessee DAmato, Salmon, Loukas, & Tomie, 1986; Edwards, Miller,& Zentall, 1985; D. Premack, 1978). Compared with pigeons,both new- and old-world monkeys more readily generalize theirvisual matching-to-sample performance to novel stimuli (e.g.,DAmato & Salmon, 1984), as does the bottlenose dolphin in anauditory matching-to-sample task (Herman & Gordon, 1974).

However, the clearest evidence of spontaneous transfer ofmatching-to-sample performance comes from chimpanzees.

Oden, Thompson, and Premack (1988) taught four infantchimpanzees to match to sample using a set of only two objects,a lock and a cup. In the simultaneous matching-to-sample pro-cedure they used the chimpanzee was handed a sample object;it was then required to choose from the set of two test objectsthe one that was the same as the sample object on that trial. Acorrect choice resulted in social and gustatory reinforcement,whereas an incorrect choice did not. After reaching a criterionof 83% correct, the animals were given a series of tests withnovel objects and fabrics. Test accuracy on these trials averaged85%. Thus, the chimpanzees transferred their matching-to-sample performance without decrement to brand-new stimuli,suggesting that they had strongly conceptualized the same-dif-ferent relation.

It is surely noteworthy that dolphins and primates morereadily generalize their matching-to-sample behavior than dopigeons. However, does this mean that pigeons are completelyunable to appreciate the abstract relation of sameness-differ-ence? Other evidence suggests not.

Paired comparison. Yet another procedure has been used toassess control over behavior by same and different stimuli. Inthe paired-comparison procedure, two stimuli are either simul-taneously or successively exposed. Then, two response alterna-tives are afforded to subjects: one for reporting that the stimuliwere the same and the other for reporting that they were differ-ent. Correct choices occasion reinforcement, whereas incorrectchoices do not.

In a project by Santiago and Wright (1984), pigeons weretrained on a simultaneous visual paired-comparison proce-dure. During original training, 105 color slides of fruit, flowers,animals, people, and other natural and human-made objectswere shown in pairs on a split screen. After making an observ-ing response to a clear panel covering the split screen, twochoice keys were lighted: the left for reporting that the twoslides were different and the right for reporting that they werethe same. Half of the trials involved same stimuli and half in-volved different stimuli. The large number of training stimulithat were used guaranteed that no stimulus occurred on morethan one trial in a session, in the hope that the birds' behaviorwould more likely come under control of the same-differentrelation than under control of the specific features of the stim-uli. After training to over 80% correct on the original set ofslides, the pigeons were shown 105 brand-new slides. First-ses-sion transfer performance averaged 70% correct. This score wasa bit lower than transfer performance to the training slides; but,it was much higher than the 50% score expected by chance, andit compared quite favorably with the 72% first-session transferscore of rhesus monkeys trained and tested under virtuallyidentical circumstances (Wright, Santiago, & Sands, 1984).

Familiarity-novelty discrimination. Further evidence thateven pigeons can appreciate abstract stimulus relations comesfrom a recent report by Macphail and Reilly (1989). In thisproject, pigeons were shown a series of color slides depictingindoor scenes, outdoor scenes, objects, faces, and so on. Eachslide was shown twice in each daily 48-trial session, and slideswere never reused from one session to another. Pecks to thefirst presentation of a given slide were reinforced with food,whereas pecks to the second presentation were not. After onlyfour sessions of discrimination training, pigeons pecked much

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 219

more often on the first presentation of a slide than on its secondpresentation. Because of the continually changing compositionof the slide arrays, these results suggest that the pigeons werereadily able to discriminate familiar from novel stimuli, quiteapart from the specific attributes of each stimulus display. Mac-phail and Reilly proposed that earlier difficulties in traininghighly general same-different or familiar-novel reports in pi-geons may have been due to procedural factors rather than toany cognitive limitations of the species.

Oddity discrimination. Whereas the familiarity-novelty dis-crimination of Macphail and Reilly (1989) necessitates succes-sively presented stimuli, a related problem, also requiring ab-stract conceptualization, does not. In an oddity concept, choiceis made of the odd stimulus in an array of three or more simulta-neously presented novel stimuli. Lombardi, Fachinelli, and De-lius (1984) first established an oddity discrimination in pigeonsgiven problems arranged from a pool of either 5 or 20 white-on-black visual forms. After reaching nearly equivalent levels ofperformance (the group given fewer stimuli learning faster thanthe group given more stimuli; cf. Bhatt, 1988), all animals weretested with brand-new forms. Highly reliable transfer was ob-served, that transfer being better for pigeons given more train-ing stimuli than those given fewer training stimuli (cf. Bhatt,1988). Interestingly, an analogous project with rats given visualand olfactory oddity tasks failed to find evidence of an oddityconcept (Thomas & Noble, 1988).

Equivalence Class Concepts

The quest for clear evidence of conceptual behavior has alsobrought about the development of new analytical ideas andexperimental procedures. For instance, the object concepts dis-cussed earlier could be and probably were based solely on physi-cal similarity. Despite our present inability to isolate and manip-ulate the relevant physical features of such complex stimuli assnapshots of cats, flowers, cars, and chairs, theorists can easilyappeal to the well-documented principle of primary stimulusgeneralization to account for transfer to novel instances fromthe training categories.

Yet, other theorists (e.g., Lea, 1984) have insisted that trueconceptual behavior must be based on something more thanmere physical resemblance. Learning a response to somemembers of a heterogeneous set of stimuli should ideally "prop-agate to all members of the set, without regard to similarity"(Herrnstein, 1990, p. 150). This requirement reduces to the dem-onstration of transfer of control through secondary stimulusgeneralization (Hull, 1943), and sets of such physically dissimi-lar yet functionally substitutable stimuli are called equivalenceclasses (see Sidman, 1986, for one specific rendering of thisgeneral idea).

Initial research by Sidman et al. (1982) using matching-to-sample procedures suggested that although children couldform equivalence classes, neither rhesus monkeys nor baboonscould do so. More recent research using different procedures ismore encouraging to the idea that animals other than humanscan form equivalence classes (Vaughan, 1988; Wasserman, De-Volder, & Coppage, 1992; Zentall, Steirn, Sherburne, &Urcuioli, 1991). In Vaughan's (1988) experiment, for example,pigeons were reinforced with food for pecking at a set of 20 out

of 40 slides, all 40 of which depicted trees. Pigeons were shownthe 40 slides in different random orders each session. The slideswere divided into two arbitrary assortments: one positive (rein-forcement in their presence, 1+) and the second negative (noreinforcement in their presence, 2—). Different birds were givendifferent 1+, 2- slide assortments to reduce the possibility thatsome unknown physical feature of the slides was associatedwith category membership. After the pigeons learned to dis-criminate the slides (responding to 1+ but not to 2- stimuli), thecontingencies were reversed (1—, 2+) and then reversed again,repeatedly. After dozens of reversals, the pigeons were able todiscriminate the positive from the negative collections after pre-sentation of only the first few stimuli in each. Evidently, thebirds had formed a common stimulus class for each of the twoslide collections; by sampling a few slides, the pigeons could tellwhich equivalence class had a positive or a negative valence inany particular session.

In the familiar terminology of Rosch and Mervis (1975), itmight be said that Vaughan's (1988) birds had learned a subordi-nate concept, in which particular instances of a basic-level con-cept, like trees, were segregated in subgroups. In higher levelgroupings, is there any evidence that animals can learn to col-lect stimuli from different basic-level concepts into superordin-ate concepts? Yes. Wasserman et al. (1992) used a three-stepprocedure with pigeons, in which collections of perceptuallydissimilar stimuli, like chairs and cars, were first associatedwith a common response. Then, a new response was learned tojust one of those classes of stimuli, like chairs. Finally, subjectswere tested for their tendency to make the new response to theclass of stimuli (cars) not given during the second step. Pigeonsshowed a strong propensity to make the new response to stim-uli with which that response was never before associated. Thus,merely by being associated with a common response in the firststep, classes of perceptually dissimilar stimuli appear to amal-gamate into a new superordinate category of functionally equiv-alent stimuli.

Although not the end of the story, it does appear that diverseconcepts are learnable by common laboratory animals, likepigeons, with different experimental methods being more orless conducive to disclosing those conceptual abilities.

Other Active Research Areas

In the previous discussions of animal memory and concep-tual behavior, I tried to provide readers with a broad overviewof two of the most active and systematic areas of research incomparative cognition. Of course, there is no way to discuss thefull range of research in the field in one review article. Inter-ested readers should consult several edited volumes (e.g., Hulse,Fowler, & Honig, 1978; Kendrick, Rilling, & Denny, 1986;Roitblat, Bever, & Terrace, 1984; Weiskrantz, 1985) and text-books (Pearce, 1987; Roitblat, 1987) for more comprehensivecoverage of comparative cognition.

Before leaving specific research domains within comparativecognition, however, two additional topics are considered, witha special eye toward matters of experimental strategy and evi-dential interpretation. These two areas—numerical compe-tence and language behavior—have fostered rather more de-

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bate, but less systematic data, than the areas of animal memoryand conceptual behavior.

Numerical Competence

Does number control the behavior of animals? If so, thendoes such discriminative control resemble counting and othermathematical behaviors in humans? Recent research suggests aclear yes to the first question and a guarded perhaps to thesecond (for a review of the literature and additional criticalcommentary, see Davis & Perusse, 1988).

As is often the case in comparative research, matters of defini-tion can be critical to deciding if the behaviors of differentorganisms are alike. So, the seemingly simple question "Doanimals count?" requires operational definition of counting.Unfortunately, considerable debate exists concerning that verydefinition (see, for example, Davis & Perusse, 1988, and Gallis-tel, 1989, for different viewpoints). Rather than trying to solvethis definitional dispute directly, some investigators have under-taken behavioral analyses to identify more basic cognitive skillsthat appear to be necessary for any organism to show countingor higher mathematical abilities. Washburn and Rumbaugh(1991) thus sought evidence on the more definite question "Cananimals learn that different symbols are associated with differ-ent quantities of food?" An affirmative answer to this morelimited query would indicate that the animal under study has aprerequisite skill to engage in more complicated mathematicalperformances, like counting and adding.6

In one set of experiments (Experiments 1, 2, and 3), Wash-burn and Rumbaugh (1991) gave two rhesus monkeys thechoice of responding to two arabic numerals; whichever nu-meral was chosen determined the number of food pellets given.For example, in a 2-9 pairing, choosing the 2 resulted in receiv-ing 2 pellets, whereas choosing the 9 resulted in receiving 9pellets. The monkeys showed a clear tendency to choose thelarger numeral, that tendency increasing as the difference be-tween the numerals increased. Also, one of the monkeysshowed clear generalization to pairs of numerals that had neverbefore been presented during training. In a final experiment(Experiment 4), Washburn and Rumbaugh further examinedthe monkeys' symbolic capabilities by presenting five differentnumerals on each trial. Each selection delivered the appro-priate number of food pellets and eliminated that numeral fromthe next choice opportunity. Here, both animals tended tochoose the largest numeral available, with their performancevarying somewhat as a function of both the number of numer-als available and the differences among the numerals. As a sam-ple of performance, one monkey first chose the 8, then the 6,then the 5, and finally the 4 when given successive choices of8-6-5-4-1,6-5-4-1,5-4-1, and 4-1, respectively. These results ledWashburn and Rumbaugh to conclude that "rhesus monkeyslearned . . . that symbols (i.e., arabic numerals 0-9) were asso-ciated with different quantities of pellets and ordinally se-quenced the symbols that indexed those quantities" (p. 192).

A further claim by the authors implies that this ability maybe limited to primates: "These rhesus monkeys displayed a pro-ficiency at discriminating, representing, and ordering quanti-ties beyond that yet demonstrated with any nonhuman species"(Washburn & Rumbaugh, 1991 p. 192). However, Bhatt and

Wasserman (1987) had earlier found that pigeons could learn toassociate four different color keys with four different quantitiesof food reinforcement and that theirchoice of a reference sched-ule of food reinforcement was a clear function of the alternativequantity of reinforcement they were given, choice of the refer-ence quantity declining as the alternative quantity was in-creased. In addition, Hulse and O'Leary (1982) had even earlierfound that rats given access to a four-arm radial maze withdifferent quantities of food at the ends of each arm learned toorder their within-trial selections in accord with those quanti-ties. After 5 weeks of training, at least 75% of the rats' choiceswere ordered 18-6-1-0 (0 = no choice to the 0-pellet arm).

A wide range of animal species can thus associate differentarbitrary stimuli (e.g., numerals, colors, or spatial locations)with different quantities of food. Furthermore, their choiceamong those arbitrary stimuli clearly preserves the ordinal rela-tions those stimuli have with different food quantities. Now,researchers can logically pursue questions concerned with nu-merical operations, such as counting and adding, which mightbe performed on those symbols (see Boysen & Capaldi, 1992,for much more work on this question).

Language Behavior

The popular and scientific attention paid to recent researchin language behavior in animals is unprecedented. Many of theapes, dolphins, and avians that have been studied in this workare as well or better known by name than their human investi-gators. In addition, the rivalry among those investigators hasoccasionally sparked rancorous debates, which some wouldclaim have done rather little to advance the understanding oflanguage behavior in nonhuman animals.

As most readers are already aware, a focal question of thisgeneral line of work is "Is language a uniquely human phenome-non?" Some of the most exciting and controversial researchaddressing this question involves teaching animals various hu-man-made communication systems, including vocal (Pepper-berg, 1981), gestural (Gardner & Gardner, 1984; Herman,Morrel-Samuels, & Pack, 1990), token-based (A. J. Premack &Premack, 1972), and computer-based (Rumbaugh, 1977)schemes. No effort is made here to rule on whether the behav-ioral feats heretofore performed by the many animals in thesediverse projects proves them to be capable of humanlike lan-guage. Rather, as in the case of numerical competence, the ques-tion is whether animals possess any of the component skillsnecessary for language behavior. This more limited approachyields some clear and unequivocal conclusions.

Central to language is the idea of reference: "To the extentthat the communication of information depends on the arbi-trary pairing of terms with conceptual categories, then thatbiological function of a natural language depends on the rotelearning of paired associates" (Gardner & Gardner, 1984, p.401). Thus, in Project Washoe and in follow-up studies, theGardners successfully trained chimpanzees to make one of

6 Such a "componential" analysis of counting can be seen to accordwith the general approach of Gluck and Bower (1988) to complex cog-nitive performance mentioned in the introduction.

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 221

many manual gestures in American sign language to refer tomembers of such human language categories as cats, flowers,balls, and shoes.

The chimpanzees transferred the signs they had learned for a fewballs, shoes, flowers, or cats to the full range of the categorieswhenever they found them and however represented, as if theydivided the world into conceptual categories just as humans do.(Gardner & Gardner, 1984, p. 400)

Thus, the chimpanzees had passed the definitional criterion ofreference wherein the animal "has a lexicon of arbitrary signalsthat symbolically stand for objects, events, concepts, and fea-tures" (Roitblat, 1987, p. 278).

Interestingly, the Gardners (Gardner & Gardner, 1984) enti-tled their article describing this work "A Vocabulary Test forChimpanzees." Note that Bhatt et al. (1988) found essentiallythe same result with pigeons, albeit with only four motor behav-iors being used for their reporting four categories of objects.Although use of the word vocabulary for either pigeons orchimpanzees may be controversial, the findings from each spe-cies clearly demonstrate the operation of reference in nonhu-man behavior, at least for some kinds of conceptual categories.7

Also critical to language is the notion of grammar: "a finitelist of rules that can be used to produce an infinitely largenumber of expressions" (Roitblat, 1987, p. 278). Allied to thenotion of grammar is that of symbol sequence or syntax:"wherein the same symbols in different orders. . . can expressdifferent meanings" (Roitblat, 1987, p. 278). Many of the lan-guage-learning projects in animals have been criticized for fail-ing to show grammatical competence. For instance, Terrace,Petitto, Sanders, and Bever (1979) concluded that although apescan learn many isolated symbols, these projects "yielded noevidence of an ape's ability to use a grammar" (p. 891). Lawfulregularities in symbol order were observed in those projects;however, such ordered responding "can, in each case, be ex-plained by reference to simpler nonlinguistic processes" (p.900). It is no small matter to show that even pigeons can betaught to produce an ordered string of up to five different re-sponses in the absence of external discriminative feedback(Terrace, 1991). Such sensitivity to response order is obviously anecessary skill for grammatical performance. However, it doesnot easily allow for the production of novel grammatical se-quences entailing the same or new responses.

The issue of symbol order has been also investigated in ani-mal behavior with regard to the question of different ordersconveying different meanings. Here, it has been found that dif-ferent sequences of colors can effectively signal different con-tingencies of reinforcement to pigeons (e.g., Weisman et al.,1980, Experiment 3). Such early results suggest that there isgood reason to believe that at least the comprehensive aspect ofsyntax is operative in animal behavior. No clear separation ofthe comprehensive and productive aspects of syntax has yetbeen achieved in monkeys (Devine, Burke, & Rohack, 1979)and pigeons (Parker, 1984), each having succeeded in reproduc-ing two-item sequences previously shown to them.8

Obviously, there are many component cognitive skills that areconcatenated in human language. Which individual and com-bined skills appear in the behavior of animals may provideimportant clues in evaluating the uniqueness of human lan-

guage. Real insights may still result from direct efforts to teachhuman communication systems to animals, or they mayemerge from more oblique inquiries into the limits of animalcognition. In either event, comparative cognition should con-tinue to contribute to researchers' understanding the biologicalorigins of this most notable form of human behavior. The re-cent remarks of Gisiner and Schusterman (1992) provide a fit-ting finale for this discussion of language behavior: "It seemshighly implausible that the linguistic abilities of humans havearisen in complete ontogenetic and phylogenetic isolation fromnonlinguistic learning abilities" (p. 90).

Overview

After a long, fallow period, researchers are again exploringthe cognitive processes of animals with renewed vigor. Muchhas been learned from the experimental investigation of ani-mal behavior since Spencer and Darwin first ignited interest inanimal intelligence and its relation to human cognition. Use ofricher and more refined methods of inquiry are now beginningto pay real dividends in disclosing that such cognitive processesas memory, attention, and conceptualization importantly par-ticipate in animal behavior. In addition, as the previous reviewindicates, there are good reasons to believe that at least somecognitive processes may be common to animals and humanbeings (also see Wasserman, 1990).

This rather optimistic evaluation notwithstanding, a few re-marks are in order considering the fact that, just 20 years ago,many had proclaimed comparative psychology to be either ter-minally ill or dead (see Hodos & Campbell, 1969; Lockard,1971; Tobach, Adler, & Adler, 1973, for presentation and dis-cussion of this thesis). Thus, the concluding sections of thisarticle raise and, I hope, answer many questions that havearisen concerning the place of comparative cognition in thebiology of behavior.

fs Comparative Cognition Comparative?

Even a cursory examination of the research reviewed in thisarticle will reveal that only a small fraction of it entails explicitcomparisons of different species within the same study. Howthen can one claim that comparative cognition is truly compara-tive? The answer to this query is that most comparisons amongspecies are conducted across different studies. With a few nota-ble exceptions (see Bitterman, 1975), most researchers of cogni-tion in animals have concentrated on one species. Such concen-

7 Others would also insist that reference is contingent on the effec-tive communication between "speakers" about things that are not nec-essarily present; this additional requirement appears to have beenpassed by chimpanzees (Savage-Rumbaugh, Murphy, Sevcik, & Rum-baugh, in press).

8 Recent research by Greenfield and Savage-Rumbaugh (1990,1991)has reconsidered the issues of grammar and syntax by examining theself-generated sequences of lexigram use by a chimpanzee. They con-cluded that this ape had the potential to invent a rudimentary gram-mar. Gisiner and Schusterman (1992), studying a language-trained sealion, have also made interesting observations on syntactical control.They concluded that this animal can learn a number of syntactic rela-tions from a limited set of standard combinatorial sequences.

222 E. A. WASSERMAN

tration enhances the chances of that research incisively andcomprehensively elucidating the cognitive processes of that spe-cies. Of course, the risk of overspecialization is that rathermuch may be learned about rather few species. Beyond rats,pigeons, monkeys, and apes, researchers know rather littleabout cognition in nonhuman animals. The field welcomes thesystematic study of underrepresented species.

All of this discussion, of course, ignores the most salient ofall comparisons, namely, the comparison of animal and humancognition. Here, the rich empirical literature on cognitive pro-cesses in humans affords countless comparative opportunitiesto investigators of animal behavior. Also, as the present reviewclearly discloses, researchers have frequently evaluated the per-formance of their animal subjects in the context of human cog-nition. This most natural of all comparisons can be expected tocommand a good measure of future research in comparativecognition.

Is Comparative Cognition Cognitive?

Today, the term cognitive psychology has come to denote aparticular domain of human behavior and the term cognitivisma specific approach to investigating cognitive processes in hu-man behavior. Most who advocate this cognitive approach havecuriously found it easier to accept functional and structuralparallels between human beings and digital computers thanbetween human and nonhuman animals (Haugeland, 1978;Lachmanetal., 1979). Indeed, the information-processing anal-ogy of humans to computers has spawned "the computationalview of thought, which sees thinking as the manipulation of aninternal representation ('mental model') of an external domain"(Hunt, 1989, p. 604).

Most workers in comparative cognition do not ascribe to thiscomputational view for fear of substituting what they see as aform of mental ism for behavioral analysis. Thus, as to the roleof internal representations in behavior, Schnaitter (1987) fol-lows Skinner's (1985) lead in observing that

there is no independent and direct way to determine how thisinternal environment works. . . . The behaviorally relevantaspects of the inner environment are neither independently assess-able nor are they directly controllable. Consequently it is impossi-ble to state any constraining generalizations about internal con-text, and without knowledge of constraining generalizations it isimpossible to establish their relationship to performance general-izations. The whole project for an analysis of behavior fails, (p. 10)

Segal (1978) added the following:

There is a great danger of a return to the worst fallacies of mental-ism and dualism in the current rise of cognitive concepts. Aware-ness—or a homunculus within the brain that controls informa-tion processing—is not a necessary part of cognition, (p. 214)

Such concerns with cognitivism have not, however, pre-vented investigators of animal behavior from researching manyof the most complex and challenging aspects of cognition.Within a behavioristic framework (Wasserman, 1981, 1982,1983), researchers have studied such benchmarks of cognitionas memory, attention, conceptualization, and language. One ofthe initiators of modern research on comparative cognition,W K. Honig (1978), has assessed this approach thusly:

The analysis is plausible because it places cognitive process andcognitive behavior within the framework of a functional and exper-imental analysis of behavior. . . . There is nothing magical ormysterious about the relevant experimental or criterion behav-iors, and thus processes remain within the realm of behavioralidentification and analysis. We do not need a new kind of psychol-ogy to deal with cognitive events, (p. 11)

To study cognitive processes in behavior, then, in no way forcesone to follow the theoretical lead of cognitivists, although someresearchers of animal behavior have explored the heuristicvalue of one of its most controversial notions—representation(e.g., Roitblat, 1982).

Is Comparative Cognition Relevant to EvolutionaryBiology?

Comparative psychologists have often been criticized fortheir choice of species to study. For instance, Ratner (1970)accused many of engaging in "capricious comparison," an ideamore fully developed by Hodos and Campbell (1969):

Much of the current research in comparative psychology seems tobe based on comparisons between animals that have been se-lected for study according to rather arbitrary considerations andappears to be without any goal other than the comparison of ani-mals for the sake of comparison. This rather tenuous approach toresearch has apparently been brought about by the absence of anybroad theoretical foundation for the field, (p. 337)

Further contributing to confusion over the nature of compari-son in comparative psychology is the claim by King and Nich-ols (1960) that "the concept of evolution, which is basic to thezoological system of classification, is probably not the conceptmost useful for a classification of behavior" (p. 22). How canresearchers inaugurate the field of comparative cognition withDarwin's theory of evolution and not adopt phylogenesis as theframework for classifying behavior and for selecting animals tostudy? One answer is given in a recent article by Gottlieb (1984;also see Campbell & Hodos, 1991; and Yarczower & Hazlett,1977). After reviewing past and present practices in evolution-ary biology, Gottlieb concluded that

the discernment of evolutionary trends has always gone on bothwithin and without strict phylogenetic lineages since the incep-tion of the theory of evolution in the early 19th century and . . .this practice continues with fruitful intellectual results to the pres-ent day. (p. 448)

For Gottlieb, it is not a matter of comparative psychology lack-ing a unifying theory, as some have claimed (Hodos & Camp-bell, 1969); rather, it is the nature of that theory.

There is a theory of comparative psychology and that theory is,and always has been, founded on a psychological concept of ana-genesis; the progressive evolution of adaptive behavior, learningability, or intelligence (pp. 448-449).

Many readers may be familiar with the evolutionary conceptof cladogenesis, the splitting of organisms into distinct and re-productively isolated populations over time. Whereas someevolutionary psychologists have insisted that only the latter isthe appropriate subject matter of comparative psychology,Gottlieb (1984) argued that the former is also a legitimate con-cern for comparative psychology.

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 223

What distinguishes the two classifications—and causes unease insome zoologists and psychologists—is that the grade or levels no-tion [of anagenesis ] deals with the ranking of behavioral organiza-tion (capacity), not kinds of animals. . . ; that is, it is most oftennot a phyletic [or cladistic] ordering, (p. 453)

Thus, behavioral analysis may suggest a particular hierarchi-cal organization of cognitive processes, some being relativelybasic and others being rather more advanced (Razran, 1971;Romanes, 1884/1969). Those different grades or levels of cog-nitive processes may represent a meaningful evolutionary pro-gression, one that might be recapitulated by species in differentand even distant evolutionary lineages. Trying to reconstructsuch behavioral hierarchies, if they exist, is unlikely to succeedby studying a few closely related species, although this phylo-genetic strategy is useful for other evolutionary purposes:

When one reads the biological literature in search of examples ofbiological anagenesis, one finds that the instances recited areusually the readily discerned ones that come from comparinglarger (supraspecific) taxonomic units, as, for example, in the evo-lution of homoiotherms (birds and mammals) from poikilo-therms (reptiles), the evolution of the three-cone retina from thesingle-cone retina, and the like (Gottlieb, 1984, p. 451)

Why?Here, one might suggest that most phylogenetic or cladistic

reconstructions have involved behavioral traits of remarkablenarrowness and inflexibility, such as the reproductive behav-iors of avians (Tinbergen, 1959) and rodents (Dewsbury, 1975).This suggestion is supported by "a wealth of material showingthat interspecies differences in motor patterns of the kind mostcommonly used in comparative [evolutionary] studies are al-most invariably innate (Hinde & Tinbergen, 1958, p. 255).Also, because "most of the studies made hitherto have dealtwith relatively small behavior elements within groups of closelyrelated species. . .[the] conclusions drawn. . . refer at most tomicroevolution" (Hinde & Tinbergen, 1958, p. 253).

Different issues and strategies are bound to arise when one istrying to compare not the behaviors themselves but the adap-tive processes manifested by those behaviors, such as intelli-gence and cognition—the very processes that concerned Dar-win and Spencer and that launched the field of comparativepsychology. This contrast between behavior and process wasnot made by self-serving comparative psychologists but by twoleading experts in ethology, R. A. Hinde and N. Tinbergen(1958):

Ultimately it will be desirable to make comparative studies notonly of overt behavior but also of the causal mechanisms underly-ing it. However, since the motor patterns are directly observable, itis these which have been studied most often, (p. 253)

Whereas Hinde and Tinbergen (1958) surmised that itsgreater ease might make cladistic reconstruction a forerunnerof anagenic reconstruction, there is no reason not to considerthese as two parallel and complementary lines of evolutionaryinquiry. In addition, although they are strong critics of manyinterpretations of anagenesis, even Campbell and Hodos (1991)conceded that

if anagenesis is considered to be a temporal sequence of grades(stages in the improvement of an organic design) exhibited in anumber of different lineages. . . , then this functional anagene-

sis is compatible with what we referred to as the analysis of adapta-tion, which does not confine comparisons to within-lineage com-parisons, . . . such studies [being] both valid and valuable, (pp.216,220)

This discussion thus places comparative cognition squarelywithin the realm of the evolutionary biology of behavior.

What Is the Relation Between Comparative Cognitionand Cognitive Ethology?

From the foregoing, one might define comparative cognitionas the comparative analysis of cognition in human and animalbehavior. Researchers in this field generally adopt experimen-tal methods of investigation, thereby allowing careful controland manipulation of relevant variables, precise and unbiasedmeasurement of behavior, and replicability of experimental re-sults. They endeavor to abide by Morgan's (1894/1896) canon inexplaining the processes of cognition with a small number ofoperationally defined theoretical notions.

Set apart from comparative cognition is cognitive ethology, aself-proclaimed antibehavioristic approach to problems of cog-nition in behavior. Initiated by D. R. Griffin (1976), the princi-pal reason for creating this field of inquiry is "to learn as muchas possible about the likelihood that nonhuman animals havemental experiences, and insofar as these do occur, what theyentail and how they affect the animals' behavior, welfare, andbiological fitness" (Griffin, 1978, p. 528).

Recalling previous discussion of interpretation in the earlyhistory of comparative psychology, Griffin's (1978) call for acognitive ethology appears to be a throwback to a prescientificanalysis of behavior in terms of conscious experience. Writingin 1928, Warden (Warden, 1928) described the influence thatthe emergence of behaviorism had on comparative psychology:"Since that time, comparative psychology has been attemptingto readjust itself to a strictly natural science position as thelogical outcome of the Darwinian conception of psychology asa biological science" (p. 508). It is evident that the adjustmentprocess is far from complete if researchers are still debating theusefulness of such notions as mind, mental experience, aware-ness, consciousness, and other ideas Griffin believes can beproper subjects for scientific study (see Ristau, 1991, for furtherdiscussion of cognitive ethology).9

That one can imagine animal behavior to be accompanied bysubjective experiences cannot be the issue, for it is equally possi-ble to imagine those behaviors to be performed withoutconscious accompaniments, a point recognized nearly a cen-tury ago by Jennings (1904/1976; see his earlier quotation).There is simply no clear or necessary role for subjective experi-ence to play in behavior, as has been observed by Segal (1978):

9 Concern with mental experience, although it might not be a fittingtopic for scientific inquiry, may nevertheless be an important source ofinvestigable hypotheses. Thus, within the experimental analysis of ani-mal psychophysics, numerous studies have been conducted to confirmthe existence of various perceptual illusions in humans and animals;for an excellent recent example, see Fujita, Blough, and Blough (1991),who reported that pigeons see the Ponzo illusion.

224 E. A. WASSERMAN

Animal cognition does not imply awareness. To say that an animallearns about environmental relationships or relationships be-tween its behavior and its consequences and then acts on thatknowledge is not to say that the animal knows it has knowledge, orknows what it is doing. It may simply be that organisms with com-plex brains react to stimulus input in complex ways. At no time isit necessary that the organism be an active, conscious participantin its information-processing functions; biological matter may besufficient to do the job—as physical matter is sufficient to docomparable problem-solving tasks in the digital computer, (pp.213-214)

One possible reason for the resurrection of mental istic termsat this particular time is the keen public and scientific interestthat surrounds many of the animal language projects men-tioned earlier. Because those projects have succeeded in estab-lishing two-way communication between a human and an ani-mal, Griffin (1978) saw a possibility for using such a communi-cation system as a "window" on the minds of animals, throughwhich they might themselves make known their thoughts, feel-ings, and emotions.

This idea is indeed enchanting; but can it achieve its objec-tive? How can researchers be sure that this and other so-calledwindows on the minds of animals are not in reality mirrors,reflecting back the thoughts, feelings, and emotions of the hu-mans? In addition, if researchers must resort to anthropomor-phism to interpret the behaviors of animals (see Burghardt,1985), must not researchers also now solve the persistent prob-lems of introspectionism, whose intractability spurred the riseof behaviorism?

Perhaps it is best to conclude this discussion of comparativecognition and cognitive ethology with these sobering reflec-tions of Mason (1976):

What has been achieved [by behavioristic investigations of animalcognition] may seem pale in comparison with the vision of sittingdown like Dr. Doolittle for an informal and revealing chat with ananimal friend. But even if this were possible, how much wouldnecessarily remain unsaid? If we have learned one thing fromyears of effort devoted to the problem, it is that there is no "win-dow" that will allow us to gaze directly on another mind, eventhat of another human being, and to see its workings clearly and tosee them whole. Mind, after all, lacks "thing quality"; it is but aconstruct, hardly more than a label, really, for complex processesand functions that we are still far short of understanding in anycreature, including ourselves. We have learned what is perhaps thehardest lesson of all: There is no royal road to mind; we are forcedto approach along the only paths that are open to us, through thetortuous byways of analysis, inference, hypothesis, and recon-struction, (p. 931)

Prospectus

From the preceding review and discussion, it is clear thatresearch on the comparative psychology of cognition is enteringa period of real growth and accomplishment. As research in thearea of comparative cognition continues, there is likely to bemuch greater contact with the areas of cognitive science, on theone hand, and behavioral neuroscience, on the other. Fullerelucidation of the similarities and differences between humanand animal cognition plus greater appreciation of the biologicalmechanisms of cognition will surely come from these contacts.Also underway is an important effort to investigate the role ofecological factors in the evolution of adaptive behavior and cog-

nition (e.g., Kamil & Roitblat, 1985), thus connecting the studyof naturalistic contingencies with complex and modifiable pat-terns of action.10 These increased interactions and interdisci-plinary efforts should also reduce the intellectual isolation thathas heretofore characterized the field.

Thus, the second century of work in comparative cognition isoff to a fast start. Its strong commitment to carefully controlledexperimental methods and its clear focus on objectively verifi-able processes of cognition should help the field avoid the meth-odological and interpretive traps that hampered progress dur-ing its first century of inquiry. The debt to the early evolution-ists can be no better paid than by advancing the field ofcomparative cognition in accordance with the best methods ofbehavioral science.

10 Within this area of inquiry, there has been a great deal of interestin adaptive specializations of intelligence: Are the processes of learn-ing, memory, and cognition strongly shaped by the specific ecologicalniche an animal occupies? Although opinions differ dramatically onthis question, the research it has spawned is of considerable interestand importance. See Balda and Kamil (1989) and Shettleworth (1992)for evidence on the remarkable spatial memories of food-storingavians; see Macphail (1985) for a critical introduction to the generalquestion of adaptive specialization; and reexamine the initial quota-tion by Lachman et al. (1979) for a presentation of this thesis withregard to human intelligence (one that seems diametrically opposed toMorgan's, 1894/1896, canon).

References

Astley, S. L., & Wasserman, E. A. (1992). Categorical discriminationand generalization in pigeons: All negative stimuli are not createdequal. Journal of Experimental Psychology: Animal Behavior Pro-cesses, 18, 193-207.

Atkinson, R. C, & Shiffrin, R. M. (1968). Human memory: A pro-posed system and its control processes. In K. W Spence & J. T.Spence (Eds.), The psychology of learning and motivation (pp. 89-195). San Diego, CA: Academic Press.

Balda, R. P., & Kamil, A. C. (1989). A comparative study of cacherecovery by three corvid species. Animal Behaviour, 38, 486-495.

Bhatt, R. S. (1988). Categorization in pigeons: Effects of category size,congruity with human categories, selective attention, and secondarygeneralization. Unpublished doctoral dissertation, University ofIowa.

Bhatt, R. S., & Wasserman, E. A. (1987). Choice behavior of pigeons onprogressive and multiple schedules: A test of optimal foragingtheory. Journal of Experimental Psychology: Animal Behavior Pro-cesses, 13, 40-51.

Bhatt, R. S., Wasserman, E. A., Reynolds, W E, Jr., & Knauss, K. S.(1988). Conceptual behavior in pigeons: Categorization of both fa-miliar and novel examples from four classes of natural and artificialstimuli. Journal of Experimental Psychology: Animal Behavior Pro-cesses, 14, 219-234.

Bitterman, M. E. (1975). The comparative analysis of learning: Are thelaws of learning the same in all animals? Science, 188, 699-709.

Bjork, R. A. (1972). Theoretical implications of directed forgetting. InA. W Melton & E. Martin (Eds.), Coding processes in human memory(pp. 217-235). Washington, DC: Winston.

Blough, D. S. (1959). Delayed matching in the pigeon. Journal of theExperimental Analysis of Behavior, 2, 151-160.

Boysen, S. J., & Capaldi, E. J. (Eds.). (1992). The development of numeri-cal competence: Animal and human models. Hillsdale, NJ: Erlbaum.

Brown, M. E, & Morrison, S. K. (1990). Element and compound

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 225

matching-to-sample performance in pigeons: The roles of informa-tion load and training history. Journal of Experimental Psychology:Animal Behavior Processes, 16, 185-192.

Buchanan, J. P., Gill, T. V, & Braggio, J. T. (1981). Serial position andclustering effects in a chimpanzee's "free recall." Memory & Cogni-tion, 9,651-660.

Burghardt, G. M. (1985). Animal awareness: Current perceptions andhistorical perspective. American Psychologist, 40, 905-919.

Campbell, C. B. G., & Hodos, W (1991). The Scala Naturae revisited:Evolutionary scales and anagenesis in comparative psychology. Jour-nal of Comparative Psychology, 105, 211-221.

Cohen, G. (1989). Memory in the real world. Hillsdale, NJ: Erlbaum.Cook, R. S., Wright, A. A., & Kendrick, D. F. (1990). Visual categoriza-

tion by pigeons. In M. L. Commons & R. J. Herrnstein (Eds.), Quan-titative analyses of behavior: Pattern recognition, Vol. VIII (pp. 187-214). Hillsdale, NJ: Erlbaum.

Crowder, R. G. (1976). Principles of learning and memory. Hillsdale,NJ: Erlbaum.

DAmato, M. R., & Salmon, D. P. (1984). Processing of complex audi-tory stimuli (tunes) by rats and monkeys (Cebus apella). AnimalLearning and Behavior, 12, 184-194.

DAmato, M. R., Salmon, D. P., Loukas, E.,&Tomie, A. (1986). Process-ing of identity and conditional relations in monkeys (Cebus apella)and pigeons (Columba livia). Animal Learning and Behavior, 14,365-373.

Darwin, C. (1920). The descent of man, and selection in relation to sex(2nd ed.). New York: Appleton. (Original work published 1871)

Davis, H., & Albert, M. (1986). Numerical discrimination by rats usingsequential auditory stimuli. Animal Learning and Behavior, 14, 57-59.

Davis, H., & Perusse, R. (1988). Numerical competence in animals:Definitional issues, current evidence, and a new research agenda.Behavioral and Brain Sciences, 11, 561-615.

Devine, J. V, Burke, M. W, & Rohack, J. J. (1979). Stimulus similarityand order as factors in visual short-term memory in nonhuman pri-mates. Journal of Experimental Psychology: Animal Behavior Pro-cesses, 5, 335-354.

Dewsbury, D. A. (1975). Diversity and adaptation in rodent copulatorybehavior. Science, 190, 947-954.

Dreyfus, L. R., Fetterman, J. G, Smith, L. D., & Stubbs, D. A. (1988).Discrimination of temporal relations by pigeons. Journal of Experi-mental Psychology: Animal Behavior Processes, 14, 349-367.

Edwards, C. A., & Honig, W K. (1987). Memorization and "featureselection" in the acquisition of natural concepts in pigeons. Learn-ing and Motivation, 18, 235-260.

Edwards, C. A., Miller, J. S., & Zentall, T. R. (1985). Control of pigeons'matching and mismatching performance by instructional cues. Ani-mal Learning and Behavior, 13, 383-391.

Fernandes, D. M., & Church, R. M. (1982). Discrimination of the num-ber of sequential events by rats. Animal Learning and Behavior, 10,171-176.

Fletcher, H. J. (1965). The delayed response problem. In A. M. Schrier,H. F Harlow, & F. Stollnitz (Eds.), Behavior of nonhuman primates(pp. 129-165). San Diego, CA: Academic Press.

Fujita, K., Blough, D. S., & Blough, P. M. (1991). Pigeons see the Ponzoillusion. Animal Learning and Behavior, 19, 283-293.

Gallistel, C. R. (1989). Animal cognition: The representation of space,time, and number. Annual Review of Psychology, 40, 155-189.

Gardner, R. A., & Gardner, B. T. (1984). A vocabulary test for chim-panzees (Pan troglodytes). Journal of Comparative Psychology, 98,381-404.

Gisiner, R., & Schusterman, R. J. (1992). Sequence, syntax, and seman-tics: Responses of a language-trained sea lion (Zalophus california-

nus) to novel sign combinations. Journal of Comparative Psychology,706,78-91.

Gluck, M. A., & Bower, G. H. (1988). From conditioning to categorylearning: An adaptive network model. Journal of Experimental Psy-chology: General, 117, 227-247.

Gottlieb, G. (1984). Evolutionary trends and evolutionary origins: Rele-vance to theory in comparative psychology. Psychological Review,91 _ 448-456.

Grant, D. S. (1981). Stimulus control of information processing in pi-geon short-term memory. Learning and Motivation, 12,19-39.

Grant, D. S. (1984). Rehearsal in pigeon short-term memory. In H. L.Roitblat, T. G. Bever, & H. S. Terrace (Eds.), Animal cognition (pp.99-115). Hillsdale, NJ: Erlbaum.

Grant, D. S., & MacDonald, S. E. (1990). An evaluation of the role ofdual coding in mediating the effect of incorrectly cuing the compari-son dimension in delayed matching in pigeons. Animal Learningand Behavior, 18,151 -156.

Greenfield, P. M., & Savage-Rumbaugh, E. S. (1990). Grammaticalcombination in Pan paniscus: Processes of learning and interven-tion in the evolution and development of language. In S. T. Parker &K. R. Gibson (Eds.), Language and intelligence in monkeys and apes:Comparative developmental perspectives (pp. 540-578). Cambridge,England: Cambridge University Press.

Greenfield, P. M., & Savage-Rumbaugh, E. S. (1991). Imitation, gram-matical development, and the invention of protogrammar by an ape.In N. A. Krasnegor, D. M. Rumbaugh, R. L. Schiefelbusch, & M.Studdert-Kennedy (Eds.), Biological and behavioral determinants oflanguage development (pp. 235-258). Hillsdale, NJ: Erlbaum.

Griffin, D. R. (1976). The question of animal awareness: Evolutionarycontinuity of mental experience. New York: Rockefeller UniversityPress.

Griffin, D. R. (1978). Prospects for a cognitive ethology. Behavioral andBrain Sciences, 1, 527-538.

Guttenberger, V T, & Wasserman, E. A. (1985). Effects of sample dura-tion, retention interval, and passage of time in the test on pigeons'matching-to-sample performance. Animal Learning and Behavior,13,121-128.

Haugeland, J. (1978). The nature and plausibility of cognitivism. Behav-ioral and Brain Sciences, 2, 215-226.

Herman, L. M., & Gordon, J. A. (1974). Auditory delayed matching inthe bottlenose dolphin. Journal of the Experimental Analysis of Be-havior, 21, 19-26.

Herman, L. M., Morrel-Samuels, P., & Pack, A. A. (1990). Bottlenoseddolphin and human recognition of veridical and degraded videodisplays of an artificial gestural language. Journal of ExperimentalPsychology: General, 119, 215-230.

Herrnstein, R. J. (1985). Riddles of natural categorization. Philosophi-cal Transactions of the Royal Society of London, B308, 129-144.

Herrnstein, R. J. (1990). Levels of stimulus control: A functional ap-proach. Cognition, 37, 133-166.

Herrnstein, R. J., & de Villiers, P. A. (1980). Fish as a natural categoryfor people and pigeons. In G. Bower (Ed.), The psychology of learningand motivation (pp. 59-95). San Diego, CA: Academic Press.

Hinde, R. A., & Tinbergen, N. (1958). The comparative study of spe-cies-specific behavior. In A. Roe & G. G. Simpson (Eds.), Behaviorand evolution (pp. 251-268). New Haven, CT: Yale University Press.

Hinrichs, J. V, & Grunke, M. E. (1975). Control processes in short-termmemory: Use of retention interval information. Journal of Experi-mental Psychology: Human Learning and Memory, 104, 229-237.

Hodos, W, & Campbell, C. B. G. (1969). Scala naturae: Why there is notheory in comparative psychology. Psychological Review, 76, 337-350.

Homa, D, Burrel, L., & Field, D. (1987). The changing composition ofabstracted categories under manipulations of decisional change,

226 E. A. WASSERMAN

choice difficulty, and category size. Journal of Experimental Psychol-ogy: Learning, Memory, and Cognition, 13, 401-412.

Honig, W K. (1978). On the conceptual nature of cognitive terms: Aninitial essay. In S. H. Hulse, H. Fowler, & W K. Honig (Eds.), Cogni-tive processes in animal behavior (pp. 1-14). Hillsdale, NJ: Erlbaum.

Honig, W K., & Dodd, P. W D. (1986). Anticipation and intention inworking memory. In D. F. Kendrick, M. E. Rilling, & M. R. Denny(Eds.), Theories of animal memory (pp. 77-100). Hillsdale, NJ: Erl-baum.

Honig, W K., & Thompson, R. K. R. (1982). Retrospective and pro-spective processing in animal working memory. In G. Bower (Ed.),The psychology of/earning and motivation (pp. 239-283). San Diego,CA: Academic Press.

Hull, C. L. (1943). Principles oj behavior. New York: Appleton-Century-Crofts.

Hulse, S. H., Fowler, H., & Honig, W K. (1978). Cognitive processes inanimal behavior. Hillsdale, NJ: Erlbaum.

Hulse, S. H., & O'Leary, D. K. (1982). Serial pattern learning: Teachingan alphabet to rats. Journal of Experimental Psychology: Animal Be-havior Processes, 8, 260-273.

Hunt, E. (1989). Cognitive science: Definition, status, and questions.Annual Review of Psychology, 40, 603-629.

Hunter, W S. (1913). The delayed reaction in animals and children.Behavior Monographs, 2, 1-86.

Jennings, H. S. (1976). Behavior of the lower organisms. Bloomington:Indiana University Press. (Original work published 1904)

Kamil, A. C, & Roitblat, H. L. (1985). Foraging theory: Implicationsfor animal learning and cognition. Annual Review of Psychology, 36,141-169.

Kendrick, D. F., & Rilling, M. E. (1986). AIM: A theory of active andinactive memory. In D. F. Kendrick, M. E. Rilling, & M. R. Denny(Eds.), Theories of animal memory (pp. 129-152). Hillsdale, NJ: Erl-baum.

Kendrick, D. F, Rilling, M. E., & Denny, M. R. (Eds.). (1986). Theoriesof animal memory. Hillsdale, NJ: Erlbaum.

Kesner, R. P., & Jackson-Smith, P. (1992). Neurobiology of an attributemodel of memory: Role of prefrontal cortex. In I. Gormezano &E. A. Wasserman (Eds.), Learning and memory: The behavioral andbiological substrates (pp. 251-273). Hillsdale, NJ: Erlbaum.

King, J. H., & Nichols, J. W (1960). Problems of classification. In R. H.Waters, D. A. Rethlingshafer, & W E. Caldwell (Eds.), Principles ofcomparative psychology (pp. 18-42). New York: McGraw-Hill.

Konorski, J. (1959). A new method of physiological investigation ofrecent memory in animals. Bulletin de VAcademic Polonaise desSciences Serie des Sciences Biologiques, 7, 115-117.

Lachman, R., Lachman, J. L., & Butterfield, E. R. (1979). Cognitivepsychology and information processing. Hillsdale, NJ: Erlbaum.

Lea, S. E. G. (1984). In what sense do pigeons learn concepts? In H. L.Roitblat, T. G. Bever, & H. S. Terrace (Eds.), Animal cognition (pp.263-276). Hillsdale, NJ: Erlbaum.

Lockard, R. B. (1971). Reflections on the fall of comparative psychol-ogy: Is there a message for us all? American Psychologist, 26, 168-179.

Lombardi, C. M., Fachinelli, C. C, & Delius, J. D. (1984). Oddity ofvisual patterns conceptualized by pigeons. Animal Learning andBehavior, 12, 2-6.

MacDonaid, S. E., & Grant, D. S. (1987). Effects of signaling retentioninterval length on delayed matching-to-sample in pigeons. Journalof Experimental Psychology: Animal Behavior Processes, 13, 116-125.

Macphail, E. M. (1985). Vertebrate intelligence: The null hypothesis.Philosophical Transactions of the Royal Society of London, B308, 37-51.

Macphail, E. M., & Reilly, S. (1989). Rapid acquisition of a noveltyversus familiarity concept by pigeons (Columba livid). Journal of Ex-perimental Psychology: Animal Behavior Processes, 15, 242-252.

Maki, W S. (1981). Directed forgetting in animals. In N. E. Spear &R. R. Miller (Eds.), Information processing in animals: Memory mech-anisms (pp. 199-225). Hillsdale, NJ: Erlbaum.

Maki, W S., & Hegvik, D. K. (1980). Directed forgetting in pigeons.Animal Learning and Behavior, 8, 567-574.

Mason, W A. (1976). Windows on other minds. Science, 194, 930-931.Morgan, C. L. (1896). An introduction to comparative psychology. Lon-

don: Scott. (Original work published 1894)Nelson, K. R., & Wasserman, E. A. (1978). Temporal factors influenc-

ing the pigeon's successive matching-to-sample performance: Sam-ple duration, intertrial interval, and retention interval. Journal of theExperimental Analysis of Behavior, 30, 153-162.

Oden, D. L., Thompson. R. K. R., & Premack, D. (1988). Spontaneoustransfer of matching by infant chimpanzees (Pan troglodytes). Jour-nal of Experimental Psychology: Animal Behavior Processes, 14,140-145.

Parker, B. K. (1984). Reproduction memory of two-event sequences inpigeons. Journal of the Experimental Analysis of Behavior, 41, 135-141.

Pearce, J. M. (1987). Introduction to animal cognition. Hillsdale, NJ:Erlbaum.

Pepperberg, I. M. (1981). Functional vocalizations by an African greyparrot (Psittacus erithacus). Zeitschrift fur Tierpsvchologie, 55,139-160.

Premack, A. J., & Premack, D. (1972). Teaching language to an ape.Scientific American, 227, 92-99.

Premack, D. (1978). On the abstractness of human concepts: Why itwould be difficult to talk to a pigeon. In S. H. Hulse, H. Fowler, &W K. Honig (Eds.). Cognitive processes in animal behavior (pp. 423-451). Hillsdale, NJ: Erlbaum.

Ratner, S. C. (1970). Comparative psychology. In A. Gilgen (Ed.), Con-temporary scientific psychology (pp. 115-146). San Diego, CA: Aca-demic Press.

Razran, G. (1971). Mind in evolution. New York: Houghton-Mifflin.Reed, P., Chih-Ta, T, Aggleton, J. P., & Rawlins, J. N. P. (1991). Pri-

macy, recency, and the von Restorff effect in rats' nonspatial recogni-tion memory. Journal of Experimental Psychology: Animal BehaviorProcesses, 17, 36-44.

Riley, D. A., & Brown, M. F. (1991). Representation of multidimen-sional stimuli in pigeons. In G. Lockhead & J. R. Pomerantz (Eds.),The perception of structure (pp. 227-245). Washington, DC: Ameri-can Psychological Association.

Riley, D. A.. & Roitblat, H. L. (1978). Selective attention and relatedcognitive processes in pigeons. In S. H. Hulse, H. Fowler, & W K.Honig (Eds.), Cognitive processes in animal behavior (pp. 249-276).Hillsdale, NJ: Erlbaum.

Rilling, M. (1992). Invisible counting animals: A history of contribu-tions from comparative psychology, ethology, and learning theory.In S. T. Boysen & E. J. Capaldi (Eds.), The development of numericalcompetence: Animal and human models. Hillsdale, NJ: Erlbaum.

Rilling, M., Kendrick, D. F, & Stonebraker, T. B. (1984). Directedforgetting in context. In G. Bower (Ed.), The psychology of learningand motivation (pp. 175-198). San Diego, CA: Academic Press.

Ristau, C. A. (Ed.). (1991). Cognitive ethology: The minds of other ani-mals. Hillsdale, NJ: Erlbaum.

Roberts, W A., & Grant, D. S. (1976). Studies of short-term memory inthe pigeon using the delayed matching-to-sample procedure. InD. L. Medin, W A. Roberts, & R. T. Davis(Eds.), Processes of animalmemory (pp. 79-112). Hillsdale, NJ: Erlbaum.

COMPARATIVE COGNITION AND ANIMAL INTELLIGENCE 227

Roberts, W A. Mazmanian, D. W, & Kraemer, P. J. (1984). Directedforgetting in monkeys. Animal Learning and Behavior, 12, 29-40.

Roitblat, H. L. (1982). The meaning of representation in animal mem-ory. The Behavioral and Brain Sciences, 5, 353-406.

Roitblat, H.L. (1987). Introduction to comparative cognition. New\brk:Freeman.

Roitblat, H. L, Bever, T. G., & Terrace, H. S. (Eds.). (1984). Animalcognition. Hillsdale, NJ: Erlbaum.

Romanes, G. J. (1969). Mental evolution in animals. New York: AMSPress. (Original work published 1884)

Romanes, G. J. (1977). Animal intelligence. New York: Appleton. (Re-printed in D. N. Robinson [Ed.], Significant contributions to the his-tory of psychology 1750-1920 [Series A: Orientation, Vol. H. G. J.Romanes]. Washington, DC: University Publications of America.)(Original work published 1883)

Rosch, E., & Mervis, C. B. (1975). Family resemblances: Studies in theinternal structure of categories. Cognitive Psychology, 7, 573-605.

Rumbaugh, D. M. (1977). Language learning by a chimpanzee: TheLana project. San Diego, CA: Academic Press.

Santi, A., Musgrave, S., & Bradford, S. A. (1988). Utilization of cuessignaling different test stimulus dimensions in delayed matching tosample by pigeons. Learning and Motivation, 19, 87-98.

Santiago, H. C, & Wright, A. A. (1984). Pigeon memory: Same/differ-ent concept learning, serial probe recognition acquisition, and probedelay effects on the serial-position function. Journal of ExperimentalPsychology: Animal Behavior Processes, 10, 498-512.

Savage-Rumbaugh, E. S., Murphy, J., Sevcik, R. A., & Rumbaugh, D. M.(in press). Language comprehension in ape and child. Monographs ofthe Society for Research in Child Development.

Schnaitter, R. (1987). Behaviorism is not cognitive and cognitivism isnot behavioral. Behaviorism, 15, 1-11.

Segal, E. F. (1978). Where behavioral psychology and cognitive psychol-ogy meet. Revista Mexicana de Analisis de la Conducta, 4, 203-216.

Shettleworth, S. J. (1992). Spatial memory in hoarding and nonhoard-ing tits (Paraded). In I. Gormezano & E. A. Wasserman (Eds.), Learn-ing and memory: The behavioral and biological substrates (pp. 25-44). Hillsdale, NJ: Erlbaum.

Sidman, M. (1986). Functional analysis of emergent verbal classes. InT. Thompson & M. D. Zeiler (Eds.), Analysis and integration of behav-ioral units (pp. 213-245). Hillsdale, NJ: Erlbaum.

Sidman, M., Rauzin, R., Lazar, R., Cunningham, S., Tailby, W, &Carrigan, P. (1982). A search for symmetry in the conditional dis-criminations of rhesus monkeys, baboons, and children. Journal ofthe Experimental Analysis of Behavior, 37, 23-44.

Skinner, B. F. (1950). Are theories of learning necessary? PsychologicalReview, 57,193-216.

Skinner, B. F. (1977). Why I am not a cognitive psychologist. Behavior-ism, 5, 1-10.

Skinner, B. F. (1985). Cognitive science and behaviorism. British Jour-nal of Psychology, 76, 291-301.

Smith, E. E., & Medin, D. L. (1981). Categories and concepts. Cam-bridge, MA: Harvard University Press.

Spear, N. E., Miller, J. S., & Jagielo, J. A. (1990). Animal memory andlearning. Annual Review of Psychology, 41,169-211.

Stenhouse, D. (1973). The evolution of intelligence: A general theory andsome of its implications. Winchester, MA: Allen & Unwin.

Sternberg, R. J. (1986). What is intelligence? Contemporary viewpointson its nature and definition. Norwood, NJ: Ablex.

Stonebraker, T. B., & Rilling, M. (1981). Control of delayed matching-to-sample performance using directed forgetting techniques. Ani-mal Learning and Behavior, 9, 196-201.

Stonebraker, T. B., & Rilling, M. (1984). Retrospective versus prospec-

tive processes in delayed matching to sample. Bulletin of the Psy-chonomic Society, 22, 372-375.

Terrace, H. S. (1991). Chunking during serial learning by a pigeon: I.Basic evidence. Journal of Experimental Psychology: Animal Behav-ior Processes, 17, 81-93.

Terrace, H. S., Petitto, L. A., Sanders, R. J., & Bever, T. G. (1979). Canan ape create a sentence? Science, 206, 891-902.

Thomas, R. K., & Noble, L. M. (1988). Visual and olfactory odditylearning in rats: What evidence is necessary to show conceptualbehavior"? Animal Learning and Behavior, 16,157-163.

Tinbergen, N. (1959). Comparative studies of the behavior of gulls(Laridae): A progress report. Behaviour, 15,1-70.

Tobach, E., Adler, H. E., & Adler, L. L. (Eds.). (1973). Comparativepsychology at issue. Annals of the NewYork Academy of Sciences, 223,1-197.

Vaughan, W, Jr. (1988). Formation of equivalence sets in pigeons. Jour-nal of Experimental Psychology: Animal Behavior Processes, 14, 36-42.

Vaughan, W, Jr., & Greene, S. L. (1984). Pigeon visual memory capac-ity. Journal of Experimental Psychology: Animal Behavior Processes,70,256-271.

Warden, C. J. (1928). The development of modern comparative psychol-ogy. The Quarterly Review of Biology, 3, 486-522.

Washburn, D. A., & Rumbaugh, D. M. (1991). Ordinal judgments ofnumerical symbols by macaques (Macaco mulatto). PsychologicalScience, 2, 190-193.

Wasserman, E. A. (1976). Successive matching-to-sample in the pi-geon: Variations on a theme by Konorski. Behavior Research Meth-ods and Instrumentation, 8, 278-282.

Wasserman, E. A. (1981). Comparative psychology returns: A reviewof Hulse, Fowler, and Honig's Cognitive processes in animal behavior.Journal of the Experimental Analysis of Behavior, 35, 243-257.

Wasserman, E. A. (1982). Further remarks on the role of cognition inthe comparative analysis of behavior. Journal of the ExperimentalAnalysis of Behavior, 38, 211-216.

Wasserman, E. A. (1983). Is cognitive psychology behavioral? The Psy-chological Record, 33, 6-11.

Wasserman, E. A. (1984). Animal intelligence: Understanding theminds of animals through their behavioral "ambassadors." In H. L.Roitblat, T. G. Bever, & H. S. Terrace (Eds.), Animal cognition (pp.45-60). Hillsdale, NJ: Erlbaum.

Wasserman, E. A. (1986). Prospection and retrospection as processesof animal short-term memory. In D. F Kendrick, M. Rilling, &M. R. Denny (Eds.), Animal memory (pp. 53-75). Hillsdale, NJ:Erlbaum.

Wasserman, E. A. (1990). Attribution of causality to common anddistinctive elements of compound stimuli. Psychological Science, 1,298-302.

Wasserman, E. A., DeLong, R. E., & Larew, M. G. (1984). Temporalorder and duration: Their discrimination and retention by pigeons.Annals of the New York Academy of Sciences, 423,103-115.

Wasserman, E. A., DeVolder, C. L., & Coppage, D. J. (1992). Nonsimi-larity-based conceptualization in pigeons via secondary or me-diated generalization. Psychological Science, 3, 374-379.

Wasserman, E. A., Grosch, J., & Nevin, J. A. (1982). Effects of signalledretention intervals on pigeon short-term memory. Animal Learningand Behavior, 10, 330-338.

Wasserman, E. A., Kiedinger, R. E., & Bhatt, R. S. (1988). Conceptualbehavior in pigeons: Categories, subcategories, and pseudocategor-ies. Journal of Experimental Psychology: Animal Behavior Processes,14, 235-246.

Wasserman, E. A., Nelson, K. R., & Larew, M. B. (1980). Memory for

228 E. A. WASSERMAN

sequences of stimuli and responses. Journal of the ExperimentalAnalysis of Behavior, 34, 49-59.

Watson, J. B. (1913). Psychology as the behaviorist views it. Psychologi-cal Review, 20, 158-177.

Weiner, B., & Reed, H. (1969). Effects of the instructional sets to re-member and to forget on short-term retention: Studies of rehearsalcontrol and retrieval inhibition (repression). Journal of ExperimentalPsychology, 79, 226-232.

Weiskrantz, L. (1985). Animal intelligence. Oxford, England: OxfordUniversity Press.

Weisman, R. G., Wasserman, E. A., Dodd, P. W D., & Larew, M. B.(1980). Representation and retention of two-event sequences in pi-geons. Journal of Experimental Psychology: Animal Behavior Pro-cesses, 6, 312-325.

Wright, A. A., Santiago, H. C, & Sands, S. F. (1984). Monkey memory:Same/different concept learning, serial probe acquisition, and probe

delay effects. Journal of Experimental Psychology: Animal BehaviorProcesses, 70,513-529.

Wright, A. A., Santiago, H. C, Sands, S. E, Kendrick, D. E, & Cook,R. G. (1985). Memory processing of serial lists by pigeons, monkeys,and people. Science, 229, 287-289.

Yarczower, M., & Hazlett, L. (1977). Evolutionary scales and anagene-sis. Psychological Bulletin, 84, 1088-1097.

Zentall, T. R., Steirn, J. N., Sherburne, L. M., & Urcuioli, P. J. (1991).Common coding in pigeons assessed through partial versus totalreversals of many-to-one conditional and simple discriminations.Journal of Experimental Psychology: Animal Behavior Processes, 17,194-201.

Received November 13,1991Revision received March 17,1992

Accepted March 17,1992 •

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