Abstraction and The Process of Recognition1

ABSTRACTION AND THE PROCESS O F RECOGNITION' Michael I . Posner UNIVERSITY O F OREGON EUGENE. OREGON

I. Introduction .............................................

A . Levels of Processing ................................... B. Abstraction .......................................... C Generation ........................................... D Recognition .......................................... E Chapter Contents...................................... I1. Stimulus Examination .................................... A . VisualMatching ....................................... B . Role of Familiarity .................................... C . UnitsofProcessing .................................... D Serial and Parallel Processes ............................ I11. Past Experience .......................................... A . Analog Operations ..................................... B . Schema Formation .................................... IV Visual Representation in Memory ........................... A . ChangesoverTime .................................... B . Manipulating Attention ................................ C Rehearsal ............................................ D Generation ........................................... E . Rehearsal and Long-Term Memory ...................... V . Separating the Visual and Name Codes of Prior Stimulation .... A . Multiletter Arrays ..................................... €3 . Manipulating the Name Code ........................... C . Manipulating the Visual Code ........................... D . Searching Visual and Name Codes ....................... E . Summary ............................................ VI . Summary and Conclusions ................................. References ............................................

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44 44 45 46 46 47 47 48 49 53 54 56 56 61 74 74 76 77 80 83 84 85 87 89 92 94 94 96

Research described in this chapter was supported by NSF Grants GI3 3939 and GB 5960 and by the Advanced Research Projects Agency of the Department of Defense monitored by the Air Force Office of Scientific Research under Contract No . F 44620.67.C.0099 . It was written while the author was on a National Science Foundation Senior Postdoctoral Fellowship at the Applied Psychology Research Unit of the Medical Research Council, Cambridge, England . The work described involves collaboration with a number of colleagues and students at the University of Oregon . I am particularly grateful to Dr Steven Keele for his help a t every stage of the research 43

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Michael I. Posner

I. Introduction The full richness of stimulus experieiice is not available in normal memory. Our retention of previous events is not as vivid or complete as the original perception. One reason for this is that selective attention leads to the storage of some aspects of a scene rather than others. Even stimuli that are processed may lose specificity as more general classifications are achieved. As stimuli undergo successive stages of encoding, each stage produces a record which can be read for some period of time later as a memory. Most students of perception consider the ability t o select and to abstract stimuli as an achievement which underlies complex cognitive development (Bruner, 1957 ;Flavell, 1963).The absence of such abstract codings is a deficit frequently found to accompany brain damage (Goldstein, 1948). On the other hand, the inability to recapture the details of stimulus experience has usually been considered as a failure of memory. I n attempting to understand the relationship between perception and memory, it is necessary to emphasize the utility of the abstractive quality of memory for normal cognition, as has been done recently in a remarkable case history of a man with a nearly complete inability to forget (Luria, 1967). This chapter is concerned with the successive stages of processing that are involved in the encoding of simple stimuli and with the record that each stage produces. These issues lie within the areas of perception and memory, respectively. Because the recognition of stimuli is impossible without stored information, it will also be necessary to consider learning of trace systems applicable to the classification of patterns never before seen. The topics discussed in the chapter as a whole are those that might be involved in a task such as recognizing a handwritten “A”. A. LEVELS OF PROCESSING

At one stage, the visual pattern “A” is coded as a set of lines forming a unified but unfamiliar figure which is not different from an infinite number of line combinations of similar complexity that are not letters. It appears possible to isolate this early level of perception by appropriate experiments (Hochberg, 1968 ; Posner & Mitchell, 1967). As encoding proceeds, past experience is brought into contact with the new input. This checking against stored information requires a measurable period of time and can thus be analyzed by experiments (Sternberg, 1967a). The trace system (abstract idea) representing past visual experience with the letter “A” is in turn connected t o the name of the letter (A). There are also superordinate classifications, such as letter or vowel, to which both the name A and the visual pattern “A” logically belong. Figure 1 schematizes these levels of analysis. It must not be assumed that these

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levels are steps in a serial chain or that each successive code obliterates the last. Rather, the analysis of how Ss pass from one code to another and what remains of previous codes are the empirical questions with which this chapter is concerned. Stimulus

Abstract'

idea

Name

Rule tion

FIG.1. A general outline of levels of processing reviewed in this chapter. The

two processes of abstraction and generation are viewed as connecting the different coding levels.

B. ABSTRACTION The process of moving from the top to the bottom of Fig. 1 may be called abstraction. I n psychological research, the term abstraction has been used in two different ways. One sense of abstraction involves the selection of certain portions or aspects of an experience. A second sense refers to the classification of a stimulus into a wider or more inclusive superordinate category. The first sense of abstraction has primarily been applied to the study of visual stimulation (Humphrey, 1951). For example, Kulpe (Humphrey, 1951) studied the abstraction of the attribute size from complex materials which also varied in color, form, and number. This sense of bbstraction is related to the idea of an abstract representation or composite photograph which includes the common elements and eliminates the differences among separate visual experiences (Woodworth, 1938). The second sense of abstraction has been used primarily with the investigation of object names. For example, Pollack (1963) studied classification of the names dog, goat, and so on, into the superordinate category animal. This sense of abstraction does not involve selection of any physical aspect of the stimulus, but rather a relationship between a particular stimulus name and another broader category name. Ribot ( 1 899) called attention to the abstraction that connects visual patterns with their names. He conceived of abstraction as a continuous process which begins with specific visual patterns or scenes and continues

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to complex semantic categories such as “justice” or “liberty.” He saw the name of an object as an intermediate form of abstraction lying between more specific visual experiences and more general abstract words. In recent years, studies of word recognition and short-term memory have discussed the relationship between the visual and acoustic levels of processing. It has been shown in many situations (Conrad, 1964; Hochberg, 1968) that a visual letter is translated into acoustic or articulatory form in the process of representing it in memory. While it now seems unlikely that this is an obligatory transformation (Neisser, 1967 ; Posner, 1967), it certainly appears to be a frequent mode ofprocessing. The codes used at each successive level of Fig. 1 stand for an increasing variety of individual instances at lower levels. In this sense, both selection and classification serve as means of abstraction. More generally, abstraction can be thought of as a process involving information reduction (Posner, 1964a) which produces encodings of increasingly greater generality.

C. GENERATION It is also possible to proceed from a more abstract level of information

to a more specific one. This process will be called generation. One can provide an abstract word and ask for an enumeration of specific instances that are subordinate to it. Experiments of this type were undertaken at Wiirzburg and continued in the work of Otto Selz (Mandler & Mandler, 1964). Recent studies have taken advantage of such generation to account for the ability of Ss to recall a large number of individual words when they are instances of well-learned categories (Cohen, 1963). Just as the process of abstraction can relate a visual pattern to its name, so it may be possible to produce a visual memory code from a letter name. Experiments relating to this question are introduced in Section IV.

D. RECOGNITION The method of studying levels of processing used in this chapter involves the recognition of identity. The recognition task may be as simple as indicating whether or not two simultaneous visual stimuli are physically identical or as complex as deciding whether or not two letters are both consonants. The recognition of identity has considerable intrinsic interest. Locke considered it one of the basic cognitive operations (Reeves, 1965), a view that still has advocates (Miller, Galanter, & Pribram, 1960; Stevens, 1966). Moreover, a recognition procedure has the practical advantage that, regardless of the complexity of the cognitive operations involved in the decisions, the output requirement can be a simple binary choice. I n most of the studies reported here, response

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speed will be used as a basis for inferring the stages involved in accomplishing the task.

E. CHAPTERCONTENTS The experiments presented in this chapter will deal with the processes of abstraction and generation, using the recognition of letter stimuli. The sections correspond roughly t o the levels of analysis shown in Fig. 1. Section TI deals with matching simultaneous visual patterns. The approach is to examine levels of abstraction a t which it would be logically possible for recognition to be free of the effects of past experience concerning the stimulus names. I n Section 111, experiments are presented that seek to explore the development of a trace system relating new visual input to past visual experience. As a result of naming visual letters, Ss are able to develop a record of both the visual input and the name. Section I V explores the visual memory code of a single letter. Consideration is given both to visual codes that result from visual stimulation and to those that are generated from the letter name. Section V presents studies that manipulate separately the visual and the name components of letter arrays. I n the final section, an effort is made t o summarize the findings by considering the general utility of the framework that these experiments provide. The chapter is based primarily upon published studies so that emphasis can be given to speculations concerning integration of the experimental results.

11. Stimulus Examination Neisser and Beller (1965) use the term stimulus examination to refer to a task in which Ss look for a target that has a single physical form, for example, looking €or an “A.” The requirement for Ss t o use stored information concerning the target letter indicates that the task involves memory for the target in addition to stimulus examination. From a theoretical view, there is an even more primitive task. This occurs when a pair of target items are exposed simultaneously and the job of S is merely to indicate whether or not they are identical, basing his judgment upon their physical form. Bruner (1957) suggested that this task differs from other perceptual tasks in that it may be free from familiarity effects. At least it is possible to perform an experiment in which neither target item has been seen before. There are several questions of crucial interest in defining the level of processing involved in this task. First, does the matching proceed prior to naming? Second, is the match affected by the familiarity of the forms and, if so, in what way? Finally, what are the structural details of such matches? What are the elements or units that are being matched? Are

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these units handled serially or in parallel? The remainder of this section is devoted t o studies that bear upon these questions. A. VISUALMATCHING Subjects can establish the identity of pairs of stimuli even when the patterns do not lend themselves to verbal labels. If two nonsense patterns are exposed simultaneously, it is possible for Ss to say rapidly whether or not they are identical. I n a psychophysical test, Ss are able to make hundreds of accurate comparative judgments along a single sensory dimension (Woodworth, 1938), but can identify relatively few stimuli on an absolute basis (Attneave, 1959). Thus, many matching tasks can be based on other than a verbal code. The basis of the match is less obvious when highly familiar letter stimuli are used. 1. Physical and Name Matches

Posner and Mitchell (1967) described several experiments in which Ss were required t o decide as rapidly as possible whether two simultaneous visual letters were the same or different. The response was indicated by pressing one of two keys and latencies were recorded. Experiments were conducted in which “same”was defined either as being physically identical (e.g., AA), or as having only the same name (e.g., Aa). Responses to physically identical pairs were about 70-100 msec faster than t o pairs having only the same name. This was true both when comparisons were made between separate experiments using the two levels of instruction and when the two types of pairs were examined within a single namelevel experiment. Moreover, a “different” response t o a stimulus pair such as AB was about 70-100 msec faster in an experiment using physical identity instruction than in one requiring matches based on the name. Thus, the same stimulus-response combination (AB-different) gave rather different response times (RTs) depending upon the instructions used to define “same.” These studies showed clearly that Ss can match stimuli based upon physical identity faster than those based upon the letter name. 2 . Independence of Matches

Two lines of converging evidence suggest that the physical match is not influenced by the name of the letter. When Ss were instructed t o respond on the basis of physical identity, “different” responses to pairs such as Aa or Bb, which had the same name, were not longer than “different” responses to pairs that did not have the same name. Despite a lifetime of calling “A” and “a” by the same name, there was no interference of that overlearned habit in physical matching.

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The second line of evidence comes from an experiment by Chase and Posner (1965).In one condition of this experiment, Ss received a display consisting of a single visual letter (target)surrounded by a circle containing one to four additional letters (array). They were to respond “yes” as rapidly as possible when the target was contained in the array. Sometimes the letters used in array and target were visually confusable (e.g., OQGD, and so on) and at other times they were visually distinct but had similar names (e.g., BCDEP, and so on). The data showed clearly that visual similarity had a marked affect on matching speed but that auditory similarity did not. The effect of visual similarity was greatly reduced when either the array or target was in memory. Matches in which both array and target are present seem t o depend upon visual factors much more than when either is in memory. This would be the case if the target letter were being matched visually to each array letter, rather than being read first and then matched to the array letters.

B. ROLEOF FAMILIARITY A continuing problem in psychology concerns the effect of familiarity upon the process of perception. There can be no doubt that familiarity affects the ability of Ss to name words or letters, since the ability to name is itself a product of learning. Indeed, any time Ss are required to search their memory in order to match an incoming stimulus with stored information, it is logically necessary for past experience to be involved to at least some degree. If the perceptual matching task reviewed in the last section goes on at a level prior to naming, it could be at a stage of perception that is not dependent on past experience. Hochberg (1968) investigated this point in a series of studies. He found that matching upright letters was no faster than matching upside down letters as long as the letters were exposed side by side. When there was a distance between the pair of letters, upright letters were superior. Since in his studies matching physically identical letters (AA)was faster than name matching (Aa) only when the letters were adjacent and not when they were split, it seems fair to argue that under his conditions Ss were using visual information for the adjacent matches and name information when the field was split. From this evidence, he concluded that familiarity did not affect perceptual matches as long as it was unnecessary to place information in memory. Only when the material had to be identified, or when storage of the stimulus was necessary, was familiarity effective. In an even more drastic operation, Posner and Mitchell (1967) compared the physical matches for letter stimuli and Gibson figures. The SS were college students with years of exposure to letters and with 3 days of practice in the letter-matching task. Nevertheless, during the first hour of exposure to Gibson figures,Ss gave physical identity reaction

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times (RTs) which were as fast as for letters. Once again familiarity had no effect upon the speed of physical matches. It would be tempting to conclude from these data that familiarity never affects this early stage of processing and that the physical match is a situation that always occurs prior to the familiarity operation. Such a conclusion, however, seems unwarranted in light of the results obtained in two recent master’s theses. Eichelman (1968) compared the time required to match pairs of letter strings consisting of 1,2, 4,or 6 elements which either were nonsense or formed meaningful words. The strings consisted of uppercase letters typed horizontally with normal spacing and presented one string on top of the other. In the word condition, both stimuli formed familiar English words, even if they were not identical. The nonsense strings were obtained by scrambling the same letters that appeared in the words. The two strings always had exactly the same number of letters. If the strings were not identical, either 1, 2, 4 or 6 letters could be different. The strings subtended a visual angle of less than 2” and were exposed for 1 second. The Ss were instructed to respond “ same” if the two strings were physically identical and “different” if they were not. All responses were to be made as rapidly as possible. The results of the study are shown in Fig. 2. There is a highly significant difference between the two curves which increases with the number of letters. The clear effect of familiarity on multiletter strings seems to conflict with the results for a single letter. Moreover, Hochberg (1968) reported that he obtained no difference in matching speeds between nonsense and meaningful strings. Hochberg’s results, however, come primarily from tasks in which the strings were exposed vertically and thus do not look familiar even when they formed words. Since Mewhort (1966) has shown that even small changes in spacing reduce effects of familiarity in tachistoscopic recognition tasks, it appears that Hochberg’s procedure is not a critical test of this question. Another possible explanation for the Eichelman results could be that Ss read the words and matched at the name level rather than at the physical level. Since he did not have strings that varied in physical form (e.g., one uppercase and one lowercase), it is impossible to eliminate this explanation completely.2 However, Eichelman analyzed the time required to respond “different” as a function of the number of letters that differed between the two strings. RT was a decreasing linear function of the number of different letters and these functions were Eichelman has now run this condition with four letter strings. Physically identical matches both for words and nonsense strings were significantly faster than name matches. This indicates that physica.1 matches in this task were not based upon reading the words and confirms the effect of familiarity upon multiletter arrays.

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nearly identical in form for nonsense and meaningful materials. This finding, together with a lack of any relationship in the data between RT and word familiarity, makes it seem doubtful that the match was being made on the basis of word names. Cox (1967) also studied a visual matching task. I n his case, the stimuli were large complex nonsense patterns which were exposed on slides. Cox measured the time for Ss t o respond “same” or “different” to a pair. Prior to his RT task, he pretrained five of his groups either with the stimulus pairs they were to see or with other pairs. Relevant pretraining

I

2

3

4

5

6

String length (letters)

FIG.2. 1tT for responding that two strings are physically identical. The stimuli are words or nonsense strings made from the same letters. (After Eichelman, 1968.)

improved performance significantly over no pretraining and over irrelevant pretraining controls. The pretraining was equally effective whether or not it involved the use of verbal labels as part of the training. Cox’s study shows once again that familiarization can be effective in visual matches. Two points should be stressed from this study. First, specific training on names was not more effective than mere visual exposure. This finding suggests that matching was not being enhanced by names and agrees with arguments presented previously (Section II,A,1). Second, unlike the small and relatively simple letter stimuli used by Hochberg and Posner, Cox’s stimuli were large, nonfoveal, and complex. His times were quite long. This second point suggests that these stimuli, like

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Eichelman’s letter strings, consisted of a number of more elementary units. So far we have considered only matching tasks that involve a RT measure. A number of investigators have studied the role of familiarity upon recognition in tasks that used thresholds as the dependent variable. Such studies are not always clearly related to the level of stimulus examination. Many of them require S to name or identify the stimulus (e.g., Gibson, Bishop, Schiff, & Smith, 1964),a task that clearly requires the use of past experience in the naming process. One relevant technique, however, is to study “same-different” judgment thresholds. R,obinson, Brown, & Hayes (1964) compared the effects of familiarity on threshold for matching and for naming simultaneous foveal letters. The stimuli were letter pairs presented in the familiar orientation or rotated. The orientation of the letters had no effect upon the threshold for determining whether they were the same or different, but did affect the energy required to name them. This study shows essentially the same results as studies using RT for single letter pairs. Another technique used to study stimulus examination involves informing S of what he is to see and then using his report about the number and clarity of the letters that he does see as a dependent variable (Haber, 1965; Hershenson, 1969). This technique has recently been employed by Hershenson (1969) to investigate the effect of varying the familiarity of sequences of seven letters. Hershenson varied familiarity by increasing the approximation of his letter strings to normal English. He found familiarity had large effects when Ss had t o name the letters. It had a reduced but significant effect upon their reports about the clarity of the letters when they knew what they were to see. It is impossible to tell whether such reports rest entirely on the input, or whether they also involve contact between the input and past experience. Hershenson did attempt to introduce a converging operation t o indicate that the reports were influenced primarily by visual factors. He found that the perceptual reports indicated that letters near the fixation point were seen most clearly, while identification was best for letters on the left. It should be noted that the results of Hershenson’s study are in agreement with those obtained by Eichelman for multiletter strings using the matching task. While comparing procedures involves many difficult problems, there seems to be considerable consistency in what is found. For single letters familiarity has no effect on simultaneous matching. This has been found using a threshold procedure (Robinson et al., 1964) and the RT method (Hochberg, 1968; Posner & Mitchell, 1967). For multiple letter strings, familiarity does affect matching. This is shown by the RT procedure (Eichelman, 1968)and by the method of perceptual report (Hershenson,

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1969). Cox’s study using nonsense forms seems to agree quite well with the letter studies in this regard. Of course, when Ss are actually asked to identify the stimulus there is no doubt that familiarity matters both for single letters (Hochberg, 1968; Robinson et al., 1964) and for letter strings (Hershenson, 1969; Gibson et al., 1964).

C. UNITSOF PROCESSING Familiarity seems to affect matching of letter strings and complex figures but not of single letters or simple forms. If a letter is thought of as a processing unit, it would be possible to argue that familiarity helps the integration of units, but does not change perception of individual units. Of course, the question of a unit of processing is one that is very complex. Neisser (1967) suggests that the units involved in processing visual material can be anything from a small section or segment of a letter to many words, depending upon the task. Some perceptual theorists (e.g., Hebb, 1949) have proposed that line slopes and vertices serve as units within simple line figures. Data from neurophysiological research (Hubel & Wiesel, 1965), disappearance under conditions of fixed retinal position (Hebb, 1963), and the analysis of grouping (Beck, 1966) have all suggested that simple line slants may serve as units which are combined in the analysis of more complex forms. Eichelman (1968) attempted to determine, in a matching task, if a single letter could be thought of as a bundle of slope units. He ran experiments in which S s received pairs of stimuli selected either from four capital letters (ABCE) or from four line slants (horizontal, vertical, and left and right oblique). A small population of items was used in order t o reduce the problem of discriminability. The results of his experiments showed that regardless of whether the stimulus pair was simultaneous or successive and of whether stimulus populations were run in blocks or mixed randomly, the letter stimuli were matched at least as rapidly as the single line slopes. These data seem to indicate that a letter cannot be thought of as an integrated bundle of line slopes for the purpose of simultaneous matching. Moreover, the data from matching strings of letters show that the letter serves as a reasonable unit for multiletter matching tasks, particularly with nonsense material. This is indicated by the high degree of linearity for matching nonsense strings shown in Fig. 2. One might argue that letters are dealt with initially as individual slants and are integrated only with practice. However, the fact that Gibson forms showed performance equal to the letters suggests that compact figures of the complexity of letters are not divided into units in the matching task, even when they are unfamiliar.

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D. SERIAL AND PARALLEL PROCESSES An alternative to considering the letter as a unit in perceptual matches is t o think of the subelements being matched in parallel. I n this case, the line elements would still be separate features of the letter but the various elements would be matched a t the same time. I n the letter matching situation, it is impossible to distinguish between these two hypotheses since there are complex and unspecified correlations between different line slopes which vary with the population of letters in the list. Until recently, there was little reason t o suppose that discriminable attributes of a figure could be dealt with in parallel in a visual matching task. Studies relevant to this proposition have been performed by Egeth (1966), Lindsay and Lindsay (1966), and Nickerson (1967). These studies have compared physical identity matches when only one attribute of the stimulus complex was relevant (e.g., form) with matches when more than one attribute was relevant (e.g., form and color). The attributes used were elements of the overall pattern in the sense that they represented quite discriminable aspects which could easily be separated from the overall configuration (e.g., color, size, and so on). Egeth (1966) showed that the time for “same” matches tended to increase with the number of relevant attributes. It was also shown that “different” RTs were a decreasing function of the number of aspects of the stimuli that were different (Nickerson, 1967). Taken together, these findings led to the view that separate aspects of a figure were processed serially. Lindsay and Lindsay ( 1966) studied matching of some figures that occurred relatively rarely and others that occurred more often. Their findings suggested that relatively unfamiliar patterns were matched serially, attribute by attribute, but when a figure appeared frequently it could be matched as a whole. Thus, they suggested that serial processing was correct, but that the unit of processing changed with experience. Hawkins (1967, 1969) has performed an extensive series of investigations using simultaneous matching of stimuli that could vary in form, size, and color. He eliminated a problem that had arisen in Egeth’s experiments by never having irrelevant attributes. He compared matching of stimuli with only one attribute with matches in which there were two attributes. Moreover, he was careful to eliminate correlations between the attributes so that, in the case of a two-attribute match, uncertainty concerning the state of one attribute was not reduced by information gained about the other attribute. His results are shown in Table I. The left side compares RTs for matching color alone, size alone, and color plus size. The data are shown individually for four Ss. It is clear that the time t o respond “same” to the combined attributes

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is no longer than for the greater of the two individual attributes. Similar data for form and size are shown in Table I (right side). Here there is a small increase in the time required to handle the attributes together, but much less than would be expected by a serial model. Control conditions were run in order to show that the addition of a second attribute did not decrease the discriminability of the individual attributes. Taken by itself. this evidence shows clear support either for considering color plus size as a unit or for parallel processing of the two separate attributes. TABLE I

SAMERTs

AND

ERROR RATESFOR SINGLEAND DOUBLE-ATTRIBUTE SIMULTANEOUS VISUALMATCHING”

I

Attri butc

________-

’S

Color

Size

Color arid sizo

Attribute ~

S

Form

Size

Form and size

1 2 3 4

516 507 490 347 465 2.8

592 532 488 400 503 3.9

606 542 516 402 518 2.8

I

1 2 3 4

x

Porcorit crror

360 381 444 373 390 1.0

467 515 562 479 506 4.4

464 514 567 478 506 2.0

it

Pcrcorit crror I

a Lcft columris are for color arid size while right columns arc for form and size. Values are givcri i n milliseconds. (After Hawkins, 1967.)

Hawkins also found, in agreement with Egeth and Nickerson, that the number of attributes that differ between the two patterns affects the RJ. Hawkins used this fact to indicate that the matches were not performed as a unit since, if they were, the response “different” would depend only on the most difficult attribute. Thus, the separate attributes operate together for a “same” judgment but cannot be considered as a unit for a “different” judgment. If attributes can be matched in parallel, the rate of matching cannof be used to define a unit for all tasks. A letter may give matching RTs no longer than individual slopes, but the slopes may still serve as a subelement of the letter for purposes other than matching. I n terms of matching speed, a letter does appear to serve as a unit, but this need not conflict with the physiological and behavioral evidence, which has been cited, for regarding line slopes as more fundamental constituents in the formation of the letter. Moreover, the parallel processing standpoint makes it less paradoxical that relatively unfamiliar figures (Gibson forms) can

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be matched as fast as much more familiar figures (letters). The elements of these stimuli may, in fact, be identical. Finally, it will be argued in later sections of this chapter that parallel processing is a frequent characteristic of matching tasks at many levels.

111. Past Experience When a letter has to be named, past experience is surely involved. Sternberg (1967a) suggests that there are two separable aspects to the question of contact between present visual stimulation and stored information. The first concerns operations, such as smoothing or normalization, which may be performed upon the input character to prepare it for contact with stored information. The second concerns the type of representation that serves to store past visual experience with the input character. In order to separate these two components, Sternberg presented Ss with a digit superimposed upon a random noise field. The Ss’ task was to determine if the character was one of a small set of positive instances given earlier. It was observed that the presence of noise affected both the slope and intercept of the function relating RT to the size of the positive set. Sternberg made two inferences from this result. First, prior to the match, Ss abstracted the input character from some of the noise provided by the background (intercept effect). Second, the match involved the visual characteristics of the input character rather than merely its name. This second point was inferred from the effect that the noise had upon the slope. The slope effects were rather small and present only early in training. Nonetheless, Sternberg’s elegant experiment does provide a rationale for separating two components of recognition. In this section, these two aspects of recognition are taken as a starting point for the development of experimental techniques to study each in isolation. I n Section III,A, operations relevant to varying input characteristics are reviewed. In order to study operations that might be involved in preparing the input for contact with stored information, rate of matching is observed as a function of the similarity between two simultaneous input characters. I n Section III,B, experiments are presented that attempt to understand the functional characteristics of the representational system that stores information used to identify new visual input. These experiments involve identification of patterns never before seen.

A. ANALOG OPERATIONS In Section 11,it was argued that Ss could match two identical letters prior to obtaining their names. The same seems to apply to two letters that are not identical but highly similar. such as Cc. The name of the letter C is no more familiar than is the name of the letter A. Accordingly,

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it would not be expected that RTs for Cc would be faster than for Aa unless the match were based on something other than the name. Experiments (Posner & Mitchell, 1967) show that Xs instructed t o respond “same” t o two letters having the same name respond much faster to a highly similar pair (e.g., Cc) than to one that is not very similar (e.g., Aa). Moreover, the time t o respond t o a pair like Cc is reliably longer than for its physically identical controls (e.g., CC and cc). This might be explained by supposing that a similar pair is matched sometimes as if it were identical and sometimes as if it had only the same name. However, the distribution of RTs appear to rule this out. Since pairs like Cc seem to be matched slower than physically identical pairs and faster than those having oniy the name in common, they have been called analog matches (Posner & Mitchell, 1967). The idea is that analog matching depends upon operations like size variation or rotation, which can be performed within the visual system and need not require contact with past experience. With letters it is not possible to vary similarity systematically. However, by substituting nonsense material for letters, one can show that the speed of visual matching is a function of the degree of similarity between members of the stimulus pair. Posner and Mitchell (1967) illustrated this with a study using Gibson forms. Gibson forms are simple figures which have the general characteristics of letters, but are not familiar (Gibson, 1965). The 8 s were taught to call pairs of Gibson forms by the same name. Three stimulus pairs were similar, differing in continuity, size, or rotation, respectively, while the fourth pair was unrelated. I n the case of differences in size and rotation and the unrelated pair, the “same” RTs were significantly longer than their physically identical controls. I n general, the “same” RTs seemed t o increase as the similarity within the pair decreased. This suggests that the “same” R T for a pair of figures to which X has learned t o give a common name is a function of their degree of physical similarity. In order to obtain a quantitative relationship between similarity and RT, Posner (1964a) taught 8 s to call pairs of nonsense dot patterns by the same name. The patterns varied systematically in similarity. They were created by applying a statistical rule to one member of the pair in order to create distortions 01 varying degrees from the original (Posner, 1964b).3After Ss had learned the names t o a rigid criterion, The prototypes consisted of eight randomly placed dots in a 64-cell matrix. The distortions ranged from exact similarity (0 bits/dot) to unrelated ( 6 bits/dot). The distortion rules resembled a random walk. The uncertainty calculations are based upon the probability of a dot moving to each cell and are related to the logarithm of the average distance moved by a dot over a sample of distortions (see Posner, 1964b; Posner et al., 1967).

Michael I. Posner

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pairs of patterns were presented simultaneously in a “same-different’’ R T task. The degree of similarity was linearly related to RT in the range from 0 to 4 bits/dot, and then leveled off. This relationship is indicated in Fig. 3. Why are patterns that are similar matched more rapidly? One reason might be that the names are learned better during the learning

OEXP I EXP II

0

I

2

3

4

5

6

Level of distortion(bits/dot)

FIG.3. RT for responding that two dot patterns have the “same” name as a function of the similarity (level of distohon) of the two patterns. The test follows a learning procedure in which Ss are taught to associate a common name with pairs of patterns. (After Posner, 1964a.)

task. This is plausible in the dot pattern study, but must be viewed in light of the data obtained with Cc in the experiments cited above. It would be hard to argue that forms C and c are better learned than A and a. Yet the same relationship between RT and similarity is present as in the dot patterns. It seems reasonable, therefore, t o suppose that the similar patterns are matched by an analog process like that discussed for letters. This process is performed on the present input rather than upon stored material. Presumably, the criterion for accepting two

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59

patterns as “same” depends upon the general similarity between members of pairs assigned a common response during learning. Next consider the patterns that are completely distorted ( 6 bitsldot). These patterns are no more similar to each other than patterns forming pairs for which “different” would be the correct response. How can they be matched? One possibility is that through the learning process they come to look alike. This was checked by having Ss make psychophysical ratings of the similarity of patterns which either were or were not given the same name during the prior learning task. There was no difference between the ratings, indicating that patterns given the same name did not come to appear more similar. Thus, if the patterns are not matched on the basis of similar appearance, they must be identified first and the identifications matched. It is not clear a t exactly what level the identification is made. However, since it must rest on material that has been stored in memory, it will be considered as equivalent to a “name” match although it might be based upon some association other than the name (Sternberg, 1967a). It seems necessary, therefore, to separate two processes that are used to match nonidentical patterns. The analog processes involve operations on the input information only, while the name matches depend upon stored information. It remains to be determined how these two processes operate. One possibility is that Ss always attempt to match by an analog process first and only then turn to identification (serial model). Another possibility is that both proceed simultaneously (parallel model). Many sub-versions of each model are possible. The parallel model is rather attractive because it helps to explain why Fig. 3 levels off a t an intermediate degree of similarity. Suppose Ss attempt both analog and name matches. As the patterns become less similar the analog matches increase in RT, but they have as an upper limit the time necessary for Ss t o perform a name match. It is not clear why the function should appear to go down, but the down turn is not significant. The criterion used earlier to support a parallel model of simultaneous matching was that two attributes could be matched as fast as a single attribute. In Section II,D, it was shown that this could occur in some simultaneous matching tasks (Hawkins, 1967). Applying this logic t o physical and name matches. Posner and Mitchell (1967) have shown that elimination of the name matches has relatively little effect on the physical identity matches. The effect that was present might be explained on the basis of a general increase in RTs when the overall task is increased in difficulty (Gottsdanker, Broadbent, & Van Sant, 1963). Either a serial or parallel model could accommodate this result. Recently, however, an experiment was designed to test the reverse. The time to make a name match was measured, using lists that either contained or did not contain

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physical identity pairs. The results shown in Table I1 indicate that the average time to respond “same” at the name level was only 12 msec faster for a list that had no physical matches than for one in which there was an equal number of physical and name matches. The 12-msec difference was not significant. Moreover, the “different” trials which were identical in the two lists were actually somewhat longer in the pure name list. Error rates for the “different” responses were 8% for the pure list and 8.4% for the mixed list. TABLE I1

MEANRTs

FOR

SAMEAND DIFFERENT RESPONSES“ Mixed list Same

Pure list

s

Same

Different

Physical

Name

Different

619 626 612 575 626 624 499 690 609

652 716 658 625 607 672 502 692 640

564 536 585 502 536 548 425 570 533

615 663 687 557 591 662 52 1 674 621

622 665 650 600 563 656 490 672 615

Pure lists contain only name identity trials. Mixed lists contain half physical identity and half name identity “sames.” Each RT is based on the mean of a t least 20 trials. Values are given in milliseconds.

I n the study reported above, the mixed list contained only physically identical and name pairs. I n an earlier study (Posner & Mitchell, 1967), lists were used with and without analog matches (e.g., Cc). The results also showed no effect of the presence of analog matches on the name RTs. These studies indicate that physical and analog matches are not a serial stage through which Ss much pass prior to name matching. It seems reasonable to conclude that the two kinds of matching are essentially parallel processes with their own time constants. This conclusion will have important applications in Sections IV and V. We have now considered two processes of recognition which go beyond the matching of identical patterns. The analog matches involve two physically present forms which are equated entirely on the basis of their visual similarity. The name matches require that a form be identified on the basis of past experience. The latter task presumably involves

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matching the input form with stored information acquired from past experience with letters. The stored visual information is in turn associated with a name. The next section considers studies of the way in which such stored information is obtained and represented in memory. B. SCHEMA FORMATION People are exposed t o dozens of different visual letter patterns that have the same name. When they encounter any of them, or a new version never before experienced, they can usually provide the name. This human capacity poses two related problems. First, how can man store so many different experiences in a way that will provide economic use of what must be a finite memory capacity (Oldfield, 1954)?Second, how do people use this stored information in the process of pattern recognition (Uhr, 1966)? Attempts to answer questions of this general type have a long history in philosophy (Price, 1953) and psychology (Reeves, 1965). John Locke speculated on the capacity of the mind to abstract from separate experiences a composite representation which stood for the individual instances. This doctrine of abstract ideas has frequently been criticized. For example, Bishop Berkeley criticized this notion based on his inability to imagine a triangle that was neither equilateral, isosceles, nor scalene, but all of these and none a t once. Berkeley’s argument challenged the position that there is an image that serves t o represent the abstract idea. Nevertheless, the idea of abstract representation in some form has persisted. The neurologist, Henry Head, was among the first to recognize the importance of a representational system for storing information that took account of individual perception but was not identical with it. Head’s notion was based primarily upon evidence from mechanisms of postural adjustment and was not subject t o the criticism Berkeley had raised. Nevertheless, it seems that Head’s notion had its origin in the philosophical doctrine of abstract ideas (Riese, 1965). Head named his abstractive construct a “schema” and Sir Frederic Bartlett introduced the idea of schema formation into psychology in his classic book, Remembering (1932). Many writers have attempted to work within the general framework that Bartlett developed. Prominent among them was Oldfield (1954), who clarified the idea of schema formation and provided an account of how its use would provide an economical system for storage of information. Oldfield proposed that the schema represented the commonalities among successive presentations of stimuli and that retention involved storage of these commonalities plus the departures that were characteristic of the individual instances. Thus, those aspects of experience in

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common among separate percepts need not be stored on each occasion. Despite the importance of this notion, Oldfield himself remarked upon the difficulty of converting it into laboratory operations. Only in the last several years have there been any concerted efforts to do so. 1. Evidence for Schema Formation Most studies of schema formation have used some form of random visual patterns. The basic pattern can be called a prototype. A number of transformations of the prototype are constructed, either by applying systematic operations (e.g.,rotation, reversal) or by some form of random walk of the points that deforms the original. I n the latter case, the prototype represents the central tendency of a set of distortions with which S may actually be presented. This basic method has employed nonsense polygons (Attneave, 1957), metric figures (Fitts, Weinstein, Rappoport, Anderson, & Leonard, 1956), and dot patterns (Posner, Goldsmith, & Welton, 1967). A number of studies have shown that Ss can learn to discriminate patterns that are distortions of one central tendency from sets that are distortions of another. For example, Evans and his colleagues have shown that Ss are able to learn to separate patterns of one central tendency from those of another and can do this even without receiving knowledge of results (Evans, 1967; Edmonds, Mueller, & Evans, 1966). I n order to obtain a quantitative analysis of the learning of sets of distortions, Posner et al. (1967) used nonsense and meaningful dot patterns varying in level of distortion from an original prototype pattern. As the level of distortion increased, the similarity of the patterns to the prototype and to each other d e c r e a ~ e d Figure .~ 4 shows two nonsense prototypes (upper row), two 5-bits/dot (middle row) and two 7.7-bitsIdot (lower row) distortions of prototype A. The 7.7 distortions are more dissimilar to the prototype and to each other than are the Level-5 distortions. I n order to obtain some idea of the perceived distance between a prototype and its distortions, psychophysical scales were obtained relating the level of distortion to magnitude estimates of perceived distance. The solid line in Fig. 5 indicates the relationship between level of distortion and perceived distance of the distorted pattern from the prototype. The scale shown on the abscissa of Fig. 5 includes the range from complete identity (0 bits/dot) to complete lack of relation (9.6 bits/dot).The 7.7-bit distortions have a mean distance of nearly 75 units. A good estimate of the distance between any two distortions of the same prototype can be obtained simply by using the perceived distance of the more distorted member of that pair from the prototype (Posner, 1966). Thus a 7.7-bit distortion will be about 75 units distance both from the The prototypes consisted of nine dots randomly located in a 900-cell matrix.

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origin and from the mean of other 7.7-bit distortions of the same prototype. These patterns can be used to compare the rate of learning of tight concepts, in which the patterns are highly similar (low levels of distortion from the prototype), with the learning of loose concepts, in which the patterns are quite different in appearance (high levels of distortions). I n one such experiment (Posner et al., 1967), Ss learned to classify three distortions of each of four different prototypes. Each distortion of a

L

I

Prototype A

Prototwe B

. I " =.

I

5 A

.

FIG.4. Two random-dot pattern prototypes (upper row), together with Level 5 bits/dot (middle row) and Level 7.7 bits/dot (lower row) distortions. These patterns are formed by use of distortion rules (Posner et al., 1967) and are similar to those used in studies described in the text.

prototype was associated with the same overt response in a pairedassociate learning task. The dotted line in Fig. 5 gives the number of errors to criterion during learning as a function of the level of distortion of the patterns that S saw. When the patterns were a t low levels of distortion, so that they looked similar to each other, learning was fast but it became increasingly difficult as the level of distortion increased. It is of interest to contrast the linear relationship between level of distortion and perceived distance with the positively accelerated learning

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64

function (both shown in Fig. 5). Small differences in similarity can be noted and enter into similarity ratings, but they have little effect when Ss are trying to learn the classification. The ability of human subjects to learn to identify patterns that are instances of different central tendencies does not it,self provide evidence that the learning of such classifications involves the abstraction of a schema. Somewhat more direct evidence in favor of the unique role of

I40

120

100

-Similarity ratings o--* Leorning a r e s

8o

s

._ 8 c ._ b 60 ,o

e e

40

5

20

0 I

0

I I I 2 4 6 Level of distortion (bitsldot)

I

8

)

FIG.5 . Median estimates of perceived distance from the prototype (solid line and left ordinate),and rate of classification learning (broken line and rignt ordinate) as a function of the level of distortion. (After Posner et al., 1967.)

the schema or central tendency has been shown in studies by Attneave (1957) and Hinsey (1963). They demonstrated that pretraining on the schema (prototype) of a set of patterns could facilitate later pairedassociate learning of those patterns. Hinsey (1963) further showed that pretraining on the prototype pattern is superior to pretraining on one of the peripheral patterns. Thus, in these studies there appears t o be something unique about prototype or schema patterns which facilitates learning the entire set.

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One series of studies (Posner & Keele, 1968, 1969) has sought to investigate this question rather directly. The stimuli were nonsense pattterns consisting of nine dots of the same type as those shown in Fig. 4. Subjects learned t o associate four different distortions of each prototype with a single key-press. This was done by a standard paired-association technique (Posner & Keele, 1968). The Ss were then transferred to a list of patterns which consisted of the following : prototypes they had never seen before, old distortions which they had just finished learning, and control patterns which were within the learned category. Some of the control patterns (Level 5 ) were selected so that their distances from the stored patterns were approximately equal to the distance of the prototype from the stored patterns. If one considers the stored patterns as the circumference of a circle, the prototype would be TABLE I11 PERCENT ERRORS AND RT TO CLASSIFYTRANSFER PATTERNS OF VARYING TO CLASSIFYA SET OF DISTORTIONS TYPESAFTER LEARNING

Percent error RT (seconds)

Memorized patterns

Schema

New level 5

New level 7.7

New patterns

13 2.01

14.9 2.28

26.9 2.53

38.3 2.87

3.21

in the center of that circle. Since the patterns differ from one another in many ways, the space is actually multidimensional. It is possible, therefore, to find patterns that have the same mean distance from the four stored patterns, as does the prototype, but which are not themselves the prototype. These patterns serve as controls. Thus, in terms of similarity to each of the four stored instances taken one at a time, the control patterns are equal to the prototype. The difference between the control patterns and the prototype is that the prototype tends to share the particular features that are common to the set of individual instances. Thus, it represents commonalities among the memorized patterns which comprise, in Oldfield’s terms, the “schema.” The results of the transfer task obtained in our study are shown in Table 111.Two features of these data are particularly striking. Of primary importance is the fact that the prototype patterns are correctly classified significantly more than any of the control patterns, even those that have been selected to represent, the same distance relationships. Thus, whatever process underlies the classification of the prototype patterns seems to be unique to the prototype and is not characteristic of every pattern

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within the learned categories. This indicates that the process of classifying patterns does not rely solely upon the distance of the new pattern from a particular stored exemplar. Instead, it depends upon the distance of the new pattern from the category of stored information that represents all the exemplars. I n this. study, the prototypes are classified, on the whole, about as well as the patterns that S actually has memorized. This last point has not been true in all studies using these materials and seems to depend heavily upon the learning process and upon the particular set of patterns sampled. The data show that the prototype or schema pattern has a higher probability of correct classification than other new patterns within the learned concept. While this suggestion is consistent with the idea of stimulus generalization, it is more explicit. It singles out the prototype of the pattern as unique. There are a t least two ways to explain the superior classification of the prototype. One possibility is quite consistent with the theoretical notion of schema formation. It suggests that the abstraction process that underlies classification of the schema occurs during learning. The second process is more consistent with the storage of individual traces. It proposes that the schema is recognized through the mediation of the individual stored patterns. One way of distinguishing between these two theoretical positions is to observe what happens to the memorized patterns and to the schema classification over time. Experiments of this type have been run (Posner & Keele, 1969; Strange, Keeney, Kessel, & Jenkins, 1968). These studies were carried out exactly as described above, except that some groups were returned to the experiment after a I-week delay between learning and pattern recognition. The results of these studies indicated that after 1 week's delay the schema pattern was recognized at least as well as the particular stored patterns that the S had learned. This was true in all the studies. Moreover, while the stored patterns underwent a significant loss over the week's delay, correct classification of the schema showed no loss and, in some cases, there was a slight gain. Since this experiment involved both classification of the schema and also remembering which switch is associated with a particular category, it is remarkable that schema classification showed no decline in accuracy over the interval. I n order t o explain why a delay increases classification errors for the memorized patterns but not the schema, it could be argued that Ss classify the schema based upon information from the whole series of stored exemplars. Even if each stored exemplar were noisier as a result of decay during the interval, the overall judgment based on the set could

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still be reliable. However, analysis of the RTs for classification of the schema does not support the view that such classification is more complex. It seems reasonable that the extraction of information concerning the central tendency takes place during learning and that schema classification is not mediated by individual patterns. Additional evidence on this point is provided in Section III,B,3. Another approach to the study of schema formation has used systematic transformation rules (Gibson, 1965; Pick, 1965). These studies have a different methodology from those described above. The general requirement is that Ss be able to determine whether a pattern is a prototype or a transformation of it (rotation, size change, and so on), Pick (1965) found that transfer of the same transformations with different prototypes was superior to transfer of the prototype with new transformations. Two things should be borne in mind about her results. First, prototype transfer was usually positive when the classification task required memory, but not when a simultaneous condition was used. This is similar t o the distinction made earlier between analog matches based on simcltaneous visual information and identifications that require access to memory. If a match does not require S to identify the pattern there is little reason to expect that familiarity with the prototype will matter. Second, the use of systematic distortion rules (transformations) gives Ss a cue that is not present in the random distortions introduced in the studies cited above. The importance of learning to utilize different rules of transformation is emphasized in the Pick study, but cannot be used to explain the results obtained with random distortions.

2. Role of Variability

The preceding section attempted to show that information concerning the schema pattern is abstracted during the process of learning. However, it is clear that information concerning individual patterns must be stored as well. Otherwise, it would be impossible to explain why old distortions which had been memorized are classified better than new 7.7-bits/dot distortions, although both are the same distance from the prototype. Therefore, it would be improper to characterize the processes going on during learning of sets of distortions as merely the abstraction of the prototype or schema. What beside the schema is involved in pattern recognition? Attneave (1957) suggested that Ss learn the relative variability or distribution of the exemplars as well as the schema. Recently, Dukes and Bevan (1967)

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compared a group that was given four repetitions of a single facial pose with one that saw four different poses of the same face. They found that the repetition condition fostered recognition of the learned pose, but the high variability group did better in recognizing new poses. This study suggests that variability aids in pattern recognition. However, since there was no control of the distance of the new poses from the learned pose, this could have resulted from an increased probability of being shown a pose similar to one of those previously learned. The variability of instances during the learning task may have two quite different effects. First, it may vary the efficiency with which the common features are abstracted. Second, it may vary the criterion concerning which patterns should be classified as instances of the category. Podell (1958) tried to separate the role of variability in these two processes. She taught Ss to classify stimuli varying around a single prototype. Her conditions included high variety (12 patterns) and low variety ( 2 patterns), and two sets of instructions. I n the active instructions, Ss were told to look for common features so they could classify new patterns. In the unintentional instructions, they were told to rate the pattern on the basis of aesthetic appeal. After learning, S s were required to write out a definition of the common elements. With the unintentional instructions, low variety led to more recall of common elements than high variety, but the reverse was true with the active set. In addition, low variety led to a good discrimination between old and new patterns, but high variety did not. In the Dukes and Bevan (1 967) and Podell ( 1 958) studies, variety was manipulated by the number of different stimuli presented. There was no control of the degree of similarity among the instances, or between the stored instances and the prototype or the new patterns. Perhaps this helps to explain conflicts involving the role of variety in subsequent pattern recognition. Posner and Keele (1968) manipulated variety by changing the level of distortion from prototype dot pattJerns. The prototypes were in the form of a triangle, the letters F and M, and a nonsense pattern. Subjects were taught either a low variety (tight concept) or a high variety (loose concept). After learning, they were transferred to new, severely distorted patterns and required to classify them into one of the four previously learned categories. The new patterns had the same overall distance from the memorized instances regardless of the variety condition. The results of this study showed that the high-variety (loose concept) group did significantly better in transfer than the low-variety (tight concept) group, but it was not clear exactly how the superior performance occurred. It could be argued that the advantage of the loose concept was primarily in the kinds of criteria that Ss set for the admission of a par-

Abstraction and the Process of Recognition

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ticular pattern into one of the meaningful categories. The use af three familiar prototypes and one random category within the same list could have contributed to this. There was a strong tendency for Ss with the tight concepts to classify patterns about which they were unsure into the nonsense category. This factor may have led Ss learning the tight category to appear less able to make classifications based on their previous learning than in fact they really were. A recent unpublished study (Keele, Fentress, & Posner, 1968) has suggested that one can separate the question of discriminability from that of criterion. In this study, nonsense dot patterns were used as stimuli. Subjects were exposed to four successive distortions of the same pattern. These distortions could be at a high level of variability (7.7 bitsldot) or at a moderate level of variability (5 bitsldot). After exposure to the four distortions, the S received a single test pattern from the same category as the presented patterns or from a new category. His task was to say whether or not the test pattern was a member of the same class as the four instances just seen. The average similarity between the test pattern and the presented patterns was constant regardless of variability condition. The results showed a significant tendency for higher variability patterns to lead to more “yes” responses regardless of whether the test pattern was a member of the class or was not. Higher variability led to a less strict criterion for considering a test pattern as a member of the class. On the other hand, the overall sensitivity of judgments (d’) was greater for the low-variability condition. The value of d’ was 1.13 for patterns of moderate variability (Level 5 ) and only .68 for those of high variability (Level 7.7). This difference was also significant. These results suggest that a major function of increased variability is in changing the criterion for acceptance of a new pattern as a member of the category. I n some situations high variability leads to more correct classifications, but the low-variability learning may still be superior in terms of overall discriminability. One interesting possibility is that the d‘ measure could be related primarily to the ability ofSs t o extract and retain the central tendency, while B (criterion) would be more related to the dispersion of the individual patterns. If this were the case, the experiment outlined above would suggest that low variability aided Ss in abstracting the prototype, but led to a conservative criterion. This agrees with Podell’s data €or the unintentional instructions, but not for the active-search set. It does not seem possible to reconcile all of the data available. However, the use of d’ and B parameters to separate the role of variability in abstracting the schema from its role in setting concept boundaries may provide an opportunity to understand more of the functional details of the trace system involved in pattern recognition.

70 3. Recognition

Michael I. Posner

The data introduced thus far in this section suggests that Ss abstract a representation that is sensitive to the commonalities among the patterns they have classified. They are also able to develop, from experience, a notion of the criterion for acceptance into the category. The abstract idea refers t o the level of processing (see Fig. 1)which serves as a description of previous visual experience with a pattern. It may be characterized by a schema (central tendency) as well as by information from the separate experiences. I n one sense it is similar to what others have meant by a “pattern recognizer” (Selfridge & Neisser, 1960; Uhr, 1966), since it serves as the basis for establishing the identity of new input. On the other hand, it may also serve as an internal representation, which can be activated centrally as well as by new input (see Generation, Section IV,D). I n a functional sense the abstract idea is like the visual gnostic units postulated by Konorski (1967), since this level of processing may serve as a stage both in abstraction and in generation. I n the case of a letter the abstract idea would be tied to the name of the letter, and activation of the abstract idea would serve to produce the associated letter name. I n the absence of a name, activation of the abstract idea may itself serve as “recognition,” as for example, when we “recognize” a face for which we cannot produce the name. What happens when the visual stimulus is something that has never been seen before! Studies of pattern recognition bear on this question. Earlier (Section III,B,l), it was pointed out that the time to classify a prototype that S had never seen before was about the same as the time t o classify an instance that he had memorized. This finding suggests that the prototype is classified directly, rather than being mediated by a series of individual stored patterns. As the distance of the new pattern from the prototype increases, so does the RT. Thus, for patterns that have never been experienced, the efficiency of classification is a function of distance from the schema. A recent unpublished study (Frost, 1968) supports the view that the schema pattern, even though it has not been seen before, is classified directly rather than being mediated by memorized patterns. Frost used the same random-dot patterns that have been discussed previously. The experiment was a recognition memory study (Shepard & Teghtsoonian, 1961). When a pattern was first shown the correct classification was “new” while if repeated the correct response was “old.” Since it is difficult to assimilate the complex random patterns, particularly a t a rate of presentation of 2 seconds per pattern, the number of errors in correct recognition was relatively high. Sets of from 6 to 12 patterns were -,elected from the same prototype and shown consecutively. The prototype pattern was presented only once within its set. Over

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71

all conditions the proportion of correct “old” responses was .67. The proportion of “old” responses to new patterns was .27 and to prototypes .66. The prototypes were identified incorrectly as ‘‘old’’with the same frequency (and the same confidence) as patterns that had been presented previously in the list. I n fact, only if the pattern had been presented in the immediately preceding trial was its probability of eliciting an “old” response greater than for the prototype. The recognition memory task requires S to say whether or not he has seen this particular pattern, rather than to classify the pattern into a category. I n the classification task, it is possible that S’s response to the prototype is mediated by information concerning individual memorized instances which fell within that category. I n that case, he would not “recognize” the stimulus in the sense of having a feeling of familiarity. If S could discriminate between a stimulus which was actually familiar and one he knew how to classify, he would have rated the prototype pattern as “new” even though he recognized that it fell within a common category. However, the data indicate that Ss were not able t o make such a discrimination and that the prototype was seen as having occurred before. It should be possible to provide a more detailed analysis of the structural basis of the process relating new input to information abstracted from past experience. A preliminary effort t o do this was included as part of the pattern recognition studies discussed earlier in this section (Posner & Keele, 1968, 1969). Subjects in these studies had learned four categories, each consisting of four 7.7-bitsIdot distortions of random prototypes. After learning and pattern recognition, they were presented with partial information from one of the four prototypes. The partial information consisted of one, three, five, seven, or all nine dots of a prototype. The dots presented were a random sample of the possible combinations. It was hoped that this would provide some insight into the cues that Ss used in obtaining the correct classification. The overall results are shown in Fig. 6. There is a strong linear trend between the number of dots exposed and the probability of correct classifications. The linear relation indicates that Ss can use partial cues to obtain some information about the correct category. This suggests that not all of the information involved in classifying the stimulus is configurational. Some of it must be related t o the position of individual dots, as well as to their configurations. It was somewhat surprising that Ss could do better than chance (25%) when presented with only a single dot. Presumably, this indicates that the density of dots within certain sections of the slide serves as a useful cue in making the classification. Sokolov (1963) has presented a probablistic theory of the process of perception. He suggests that perception can be viewed as a sequential

Michael I. Posner

72

decision process in which each cue serves to reduce the Ss uncertainty about the correct classification. I n his model, each dot can be considered t o be independent. The data obtained from the partial information study are more-or-less consistent with this view. However, if each dot were truly independent the curve shown in Fig. 6 would be negatively accelerated. Inspection 70

65

60

v)

0

55

c

0

-=-

5

50

0

c

?

i2

45

t

0

E

a

40

35

30 25

I

0

I

2

I

I

4 6 Number of dots

I

8

I

10

FIG.6. Correct classification of the prototype as a function of amount of partial information (number of dots). This test follows learning and pattern recognition procedures described in the text. (The line is fitted by eye.)

of the graph indicates that the departure from linearity is in the opposite direction from what would be expected if the function were negatively amelerated. This study is probably too crude to give more than the roughest indication of the cues used in classification. A more thorough analysis would probably have to formulate specific hypotheses about the critical features in recognition and select partial cues to represent such features.

Abstraction and the Process of Recognition 4. Type of Representation

73

The level of processing that represents the central tendency and variability of past visual experience is called in this chapter an “abstract idea.” The philosopher, H. H. Price (1940), has written that the word idea is one of the most pernicious sources of confusion in the literature of western philosophy, for it has meant, among other things, either a concept or a mental image. The term “idea” is used in this chapter in a neutral sense. What is not clear from the data is the form of representation of this information. The description that S stores about the dot patterns is a description of his visual experience, and it can be used to recognize visual information. However, this does not mean that the information is stored in terms of a visual image, that S could see or visualize the sets of dots that represent the central tendency of the pattern, or that the formation of the abstract representation was free from verbalization. Extensive questioning of Ss who ran in these experiments did not reveal anything specific about these issues. Many 8 s reported using verbal rules that were related to the patterns. The rules tended to emphasize position of dots, center of gravity, overall orientation of the figure, familiar subgroups and association with objects. The rules were highly idiosyncratic and some Ss verbalized no rules at all. Ribot (1899) faced almost the same question posed here. He argued that “general ideas,” in his terms, did not require verbal processes for their formation. The basis of his evidence was that animals, idiots, and deaf mutes were able to abstract invariances from their visual environment, as when a dog responds to his “master” in very different contexts. He thus argued that this level of abstraction was simpler than the levels required by language. Recently, Konorski (1967) presented the view that complex pattern recognition units are present within the visual system and can function in isolation from speech units. Perhaps studies of abstraction under speeded conditions can help determine the importance of the verbal processes that accompany learning. It does not appear likely, however, that experiments with the dot patterns will tell us much about the form of representation in memory. I n Section I1 it was argued that, performance experiments can isolate levels of processing in letter recognition which are prior to the naming operations. The letter-matching techniques discussed in Section I1 seem to provide more information concerning the functional system that stores visual information immediately after presentation. I n the next two sections, we return to this technique in order to separate the visual and name levels of representation in memory. These experiments bear, at least indirectly, upon the form of stored representation that may be involved in schema formation.

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Michael I. Posner

IV. Visual Representation in Memory Section I1 introduced a method for studying letter matching at the physical and a t the name level. The results led to the view that physical matches were not influenced by the letter name. I n this section, experiments are introduced which involve presentation of two letters successively. The difference in RT between physical (e.g., AA) and name (e.g., Aa) matches is used to infer’that a visual memory code of the stored letter is used in making the match.

A. CHANGESOVER TIME I n several experiments (Boies, 1969; Posner & Keele, 1967; Posner, Boies, Eichelman, & Taylor, 1969), a single visual letter was presented and followed from 0 to 2 seconds later by a second letter. The two letters could be physically identical, have only the same name, or be different. The Ss were instructed to respond “same” if the two letters had the same name, or if otherwise, “different.” In the first two studies, S had to move his eyes from the first letter t o the second letter. The time he spent viewing the first letter was up to him, although the instructions encouraged a brief glimpse. In the third experiment, no eye movement was required and the time of exposure was constant at .5 second. The first two studies used a memory drum and normal reading illumination, while later studies used inline displays which produced a bright field. In two of the studies, the time intervals were blocked so that S always knew the delay he would receive on a given trial, while in the other study the interval was randomized. I n still other studies, the interval between the letters was filled with a random black-and-white pattern or with a field of luminance equal to the original exposure. These various manipulations often affected the absolute RTs. For example, the use of an eye movement or interpolated pattern field increased RT, but had little influence on the function relating the difference between physical and name matches to the interval. Figure 7 shows this function for three different studies which represent a wide range of conditions but give highly similar results. The three studies summarized in Fig. 7 were the only ones that covered the range between 0 and 1.5 or 2 seconds with at least three intervals. Studies using only two intervals or a less extensive range gave similar results, but the quantitative agreement was not always as complete as in these three studies. For example, the left side of Fig. 8 presents resulk from a study using intervals of 0, .5, and 1 second and the differences between physical and name matches are somewhat smaller than those shown in Fig. 7. Analyses of “different” RTs show them t o be somewhat similar but longer than the name “same” responses. These are outlined fully in Posner et al. ( 1969).

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Immediately after presentation of the letter, the match appears to be based on a fully adequate visual code. A physical match is about 90 msec faster than a name match. This result is similar to that obtained with a simultaneous letter pair. This difference declines to nearly 0 after an interval of 2 seconds. Unlike previous studies of visual memory for letters (Sperling, 1960,1963; Keele & Chase, 1967), in these experiinentsss have already extracted the letter name at the start of the retention interval. The presence of a visual code must be inferred from the efficiency of a physical match.

O t

I

I

0

I 5

I

I

15 Interval (seconds) I

I

2

FIG.7. Difference in RT between name and physical identity ‘kame” responses as a function of IS1 between twp successive letters. The solid and open circles involve studies using a memory drum, normal room illumination, and an eye movement between letters. The solid triangles represent a study using an iriline display, .5-st:cond exposure of the first letter, and appearance of the sceond letter in the same spatial position. (After Posner 8: Keele, 1967; Posner et al., 1969.)

Unfortunately, it is not possible to interpret the absence of a difference between physical and name matches as meaning that Ss have no visual information. It indicates only that the visual information is not aiding the match. This could be because it is lost, because it is less accessible, or because it has become too noisy for an efficientmatch. While the difference between physical and name matches shows roughly the same time course as the loss of visual information from tachistoscopic exposures (Sperling, 1960, 1963; Keele & Chase, 1967),the lack of luminance, noise field, and exposure duration effects argues that the visual code studied by the RT method may be quite different than the decaying visual trace.

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Michael I. Posner

If this visual code is at a higher level of processing than the stimulus trace, its maintenance might require active attention (Posner, 1967). B. MANIPULATINGATTENTION The studies cited above indicated that the presence of a visual noise field during the retention interval did not affect the difference between physical and name matches. Previous work on a different visual memory task produced a similar result. This task involved the ability of Ss to preserve the position of a point on a line (Posner & Konick, 1966). If Ss had to read and record numbers in the interval between observation and recall, performance was little worse than with an unfilled interval. However, if they were required to operate on the numbers by addition or classification, retention was greatly reduced. This finding suggested that the maintenance of a visual code can be closely related to the degree of attention available during the retention interval. An experiment was conducted (Posner et al., 1969) to compare the effects of visual noise and mental processing on the visual code inferred from the RT task. The first letter was present for 1 second. This was followed by a .5-second delay, during which Ss were randomly presented with a blank field, a mask field, or two visual digits. On the trials in which the visual digits appeared, Ss were required to add them and report the sum. The .5-second delay was followed by a second letter, to which Ss responded “same” or “different” as quickly as possible. The results showed that both the mask and the addition task increased the absolute RTs. However, the addition task abolished the difference between physical and name identity, while the noise field did not affect this difference. In a subsequent experiment, Boies (1969) presented a single auditory digit within the .&second delay interval. Subjects were instructed t o add three and report the sum after completing the RT task. On the first experimental day (second day of practice), Ss showed a pattern of results similar t o those obtained with the visual digit. With no interpolated digit, the difference between physical and name matches was about 44 msec. When the digit was interpolated, there was a significant increase in absolute RT, and the difference between the matches dropped to 20 msec. The reduction in difference between physical and name matches approached but did not reach statistical significance (.l >I, > .05). On the second experimental day, the interpolated auditory digit caused no increase in absolute time and no decrease in the difference between physical and name matches. I n this study, Ss reported that they stored the digit and actually performed the addition task after their response to the second letter. Visual noise alone does not affect the visual code. A single auditory

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digit also may have no effect, at least after practice, while adding visual digits has a clear effect. The critical variable could be the modality to which the interpolated digit is presented, or the overall difficulty of the interpolated task. I n any case, it is clear that a processing task, a t least when the input is over the visual modality, can selectively reduce the efficiency of a match based on the visual code. More research will be necessary to make certain of the mechanisms involved. C. REHEARSAL Are there conditions €or which S is able to maintain visual information more effectively than those that have been shown in previous experiments? Because of the results obtained from studying the retention of position along a line (Posner & Konick, 1966), it was surprising to find that the physical match efficiency was lost so quickly in the matching tasks. One possible reason is that S had relatively little incentive to preserve the visual aspect of the letter as distinct from the name. On one-quarter of the trials, the two letters had only the name in common and on one-half they were different. Thus, only on one-quarter of the trials was the visual code a sufficient basis for making the match. These conditions may have encouraged Ss to attend primarily t o the acoustic level, that is, to rehearse the letter names rather than attend to their visual form. In fact, that explanation corresponded closely to introspective reports. In an effort to find conditions for efficient maintenance of the physical match, pure and mixed lists were compared. I n these conditions, the first letter was always uppercase and the second letter was either always uppercase (pure list) or mixed upper- and lowercase (mixed list).6Physical matches in mixed lists could be compared with physical matches in pure lists. If the pure list provided more incentive for S to attend to the visual level, the physical match RTs for pure lists ought to be better after a delay interval than physical match RTs for mixed lists. The data from two different experiments are shown in Fig. 8. I n both studies, the physical matches in the mixed condition show a rapid increase in RT over time. The name condition is relatively flat over the interval. The physical matches in the pure lists also increase over time, but less than those in the mixed list. The divergence between the two types of physical match is significant. The results of these studies suggest Our experiments have shown little difference in RT for physical matches consisting of uppercase and lowercase letters (Posner et al., 1969, Experiment I). Moreover, within each study it is possible t o use data from delayed physical matches and “different” RTs to determine any systematic bias in favor of upperor lowercase. I n the studies, such differences are small with respect to the effects reported.

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Michael I. Posner

that Ss can maintain the physical match more efficiently if given incentive. Attention to the visual level serves to maintain the efficiency of a physical match either by improving the clarity of the visual code or by keeping it accessible for a later match. It should be noted that the RT for the physical match in the pure list condition is not flat. It tends to turn up slightly in the first experiment, and more sharply so in the second study. The upswing cannot be attributed t o temporal uncertainty alone since the name match RTs are much flatter but have the same temporal uncertainty. There appears to be a genuine difficulty in maintaining the eficiency of the visual code even when the conditions encourage S t o do so.

550

1

EXP I

EXP II

(name)

400L /

0

5

I

I

0

/

I

5

I I

I 2

Interval (seconds1

FIG.8. R T as a function of IS1 for physical and name matches in mixed lists and physical matches in pure lists. The two experiments were highly similar except that in Experiment I1 longer ISIs were used and these were run in blocks. Both studies used inline displays and .5-second exposure of the first letter. (After Posner et al., 1969; Boies, 1968.)

This difficulty is pointed up by another experiment (Boies, Posner,

& Taylor, 1968). One group was instructed t o respond “same” only if

the stimuli were physically identical. Another group was given the usual instructions to respond “same” if the letters had the same name. Inter-

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stimulus intervals of 0 and 2 seconds were used. It was expected that Ss who could use the physical form as a reliable cue would show a much smaller increase over the delay interval in RT for physical matches. This expectancy was not met. Both groups showed a similar increase in physical matches over time, while the name match RTs for the second group were virtually flat. These experiments indicate that a variety of operations can influence the relative efficiency of visual and name matches during the 2 seconds immediately following presentation of a letter stimulus. With the standard mixed-list condition, the relative advantage of matches based upon physical information declines systematically over a 2-second interval. This decline does not seem to be influenced much by the length of exposure of the first stimulus or by the presence of visual noise during the interval. The decline is affected by the relative attention the Ss can give to the two levels of processing. An interpolated visual addition task which presumably reduces the available capacity for attending to the visual code appears to have more affect upon the visual level than upon the name level. This would be expected if the visual information were extremely susceptible to interruption. When S’s attention is focused upon the visual information by giving him a pure list, he is better able to maintain the visual information in the accessible store at least over 1-13 seconds. The difficulty of maintaining the visual information, even for a period of 2 seconds, suggests that the visual code is highly susceptible to interruption and shows relatively little evidence of consolidation. The differential effects of delay on the various matches argue strongly against any temporal uncertainty explanation of these findings. Moreover, the significant divergenqe of physical matches in mixed and pure lists argues against any interpretation based upon the number of different visual forms (event uncertainty) since event uncertainty differences are fully present at time zero. Another possible explanation for these effects is that Xs set themselves to deal with either the physical or name level. The extreme susceptibility of these effects to interruption and the difficulty of maintaining the relative efficiency of a physical match argues against a generalized “set” mechanism. Two reasons for the difficulty in maintaining the efficiency of a physical match suggest themselves. One possibility is that Ss have difficulty in maintaining attention over a %second interval, and even a brief disruption of attention serves to reduce the efficiency of the visual code. Another possibility is that whatever system preserves the visual code is resistant to continuous activity. This might be somewhat similar to the tendency of a stopped image to disappear from view after a few seconds (Riggs, Ratliff, Cornsweet, & Cornsweet, 1963). Indeed, if one accepts a view like Konorski’s

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(1967), the properties of neural systems involved in perception and imagination ought to be similar. More experiments are necessary to determine exactly what happens to the visual code over time. One speculation is that the visual code is represented in great detail a t the moment immediately following visual stimulation. However, over a period of seconds it is assimilated into information about the same letter which makes up the stored abstract idea (Section 111,B). As the information is assimilated, it loses the detail and accuracy of the original visual stimulus and instead becomes part of general past experience with stimuli of that type. Attention to the visual information during this critical period may serve to increase the length of the process (Talland, 1965). Perhaps the interval observed in these experiments involves the activity, not of the trace of the particular letter presented on a trial, but of the whole trace system representing the abstract idea of the letter. If this is the case, it should be possible to obtain similar results by presenting the letter name and allowing S to activate the abstract level centrally. This is the topic of the next section.

D. GENERATION The concept of generation (see Fig. 1)refers to S’s ability t o go from a more general code to one of greater specificity. A particularly interesting example is the generation of a visual code from the letter name. The matching task can be used as a means of determining the efficiency with which such a visual code can be generated by S. In order to do this, a comparison is made between auditory and visual presentation of the first letter (Posner et al., 1969). When both letters are visual, Ss can perform matches at either the physical or name level. The extent to which RTs following auditory presentation resemble physical rather than name matches provides an index of the efficiency of generation. I n general, the methodology of these studies was similar to that described in the preceding section. In the first experiment (Posner et al., 1969), the first letter could be either visual (always uppercase) or auditory, and was present for about .5 second. This was followed by a delay interval of about .75 second. The second letter was always visual and could be either mixed, with respect to case (mixed list), or always uppercase (pure list). Some data from the experiment are shown in Fig. 9. I n the visual mixed conditions, the difference between visual and name identity is about 30 msec. This corresponds roughly to values shown in Fig. 7 for delays of .75 second. Moreover the difference between pure and mixed lists for physical matches agrees with the previous rehearsal experiments (Fig. 8). These two findings confirm the presence of a visual code when the first letter is visual.

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The first evidence related to generation is obtained by comparing the “same” RTs in the pure condition following visual and auditory presentation of the first letter. Figure 9 shows that there was a small difference (about 10 msec) in favor ofthe visual condition, but this is not significant. Moreover, in the mixed conditions, auditory-visual matching is as fast as the physical identity matches. This occurs whether the second letter is upper- or lowercase and despitJeinstructions given to consider the first auditory letter as a capital. Since the visual mixed condition provides evidence in favor of a visual code, it seems proper to suggest that the Ss base their matches upon some kind of visual code in the auditory condition rather than matching at the name level.

420

I

400

-

440

-

300 -

P

>

Different

Visual (name)

-

-

/

/

)Same

/

(physical)

-AuditoryVisual /Visual

0-

360 -

340

’/

/

-

~

Pure

Second list

Mixed

FIG.9. RTs for matching a visual probe letter, following .75-second after visual (dotted line) or auditory (solid line) presentation of the first letter as a function of the type of list. (After Posner et al., 1969.)

It was surprising, however, that in the auditory-visual mixed condition Ss were able to produce the match with equal speed regardless of the case of the second letter. To obtain a better idea of what was happening during the interval, the same experiment was run with 0, .5, and 1 second between the first auditory letter and the second visual letter (Posner

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Michael I. Posner

et al., 1969).As before, the pure lists showed no difference between visual and auditory conditions after a delay of 1 second. For the mixed lists at time zero, both auditory matches are longer than the physical identity visual matches. However, after the I-second interval the auditory conditions are faster than the visual match at the name level, and at least as fast as the visual physical identity match. These experiments indicate that Ss are able to operate upon auditory information to produce highly efficient matches. We have called this process the generation of a visual code. Such generation is accompanied by subjective reports from some Ss that they “expect” or “are looking for,” or, more rarely, “see” some specific visual information in the interval following presentation of the letter name. Perhaps this production of visual information is related to the operation of lower-level visual analyzers, such as those proposed in the pattern recognizer “Pandemonium” (Selfridge & Neisser, 1960).Such models suggest that Ss are able to switch in analyzers which can detect features in visual information, i.e., Ss are able to activate past descriptors which have been built up about the visual information from letters they have experienced. Perhaps this is equivalent to the level of abstract ideas presented in this chapter. From our present data, it is not possible to determine the details of the visual code available as the result of generation. For example, it would be possible for Ss to generate only certain features which would allow them t o distinguish between different letters of the alphabet. These data do not indicate whether the generated visual information has a distinct size or particular color, and so on. The failure to find much difference between upper- and lowercase letters following auditory stimulation indicates that the generated code might be general enough to include both cases for some letters (e.g., Ff). One problem connected with the concept of generation as applied to these studies is the difficulty of obtaining generation under some conditions. IfSs are able to generate, why do they not generate the lowercase when they are stimulated by a visual capital letter? If this were done, one would expect to have no decay function in studies of the type presented in Fig. 7. Whether, under particular conditions, Ss choose to attend to the visual code, or choose to generate it, seems to be something that changes with test conditions. Presumably, the presentation of an auditory stimulus and the necessity for matching it against a new visual input does incline S t o activate his visual code. However, when visual information is presented, Ss do not appear to be inclined either to maintain that visual representation in a mixed list or to produce a visual representation of the other case. A recent study by Boies (1969) indicates that evidence for generation can be found with visual stimulation when S has help in maintaining

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the letter already received. This study varies the duration of the first visual stimulus rather than the time between the presentation of the two. The time between offset of the first letter and presentation of the second letter is always zero. Boies found that presenting the first letter for .5-1 second gave the usual difference between physical and name identity. However, as the length of the visual presentation is increased beyond 1 second, RT for name identity matches declines markedly while RT for physical identity matches increases slightly. One explanation of this is that in the presence of the visual information about one case, S begins to produce a visual code of the opposite case. These conditions may allow S t o free his processing capacity from maintaining the visual representation in order to allocate attention to development of the code of the opposite case.

E. REHEARSAL AND LONG-TERM MEMORY In this section a series of studies has been presented which indicate that immediately after the presentation of a visual letter Ss have a relatively complete representation of the stimulus that includes visual and name components. For a short period of time, the visual components are sufficiently accessible that Ss can match more quickly when incoming input is physically identical to the stored item than when they have only the name in common. It has been shown that the effects obtained in such experiments vary greatly, depending upon the direction of S’s limited processing capacity attentional system. If his attention is directed to the visual aspects of the stimuli, he shows better ability to maintain the visual representation. If his attention is distracted, the visual representation tends to be more affected than does the name representation. If presentation is auditory, S tends to produce a visual representation by the process of generation. What level of representation is activated both by presentation of a visual letter and by the presentation ofthe letter name? It seems reasonable to speculate that this level of analysis is similar to the abstract idea discussed in the preceding section. The activation of the abstract idea may be by means of current visual input, or may depend upon learned connections from the name level. In either case, the product is an internal representation which is, in some sense, a description of past experience with related visual forms. The properties of this representation would be those attributed to the abstract idea in Section I1,B. Konorski (1967) suggests that the difference between perception and imagination is the occurrence of sensory orientation in the former but not the latter. Activation of the abstract idea by a visual stimulus may also be qualitatively somewhat different than activation from the name.

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Michael I. Posner

When a new visual input is presented, its full detail might be represented initially. Any small change in the letter would be expected to lead to an increase in RT over an exact match control. However, as the new input is incorporated into the abstract representation, it would lose specificity; thus many patterns of the same general form might be matched with equal facility. When activation is from the name level, the specificity of representation should be equivalent to an already assimilated input. These speculations receive some support from data. The generated representation never does provide matches as efficient as a physical match that follows immediately after visual stimulation (Posner et al., 1969). It is as efficient, however, as physical matches that follow a visual stimulus after a 1 second delay. The first 1-2 seconds seem to be the crucial period during which the details of the prior visual stimulus are assimilated into the overall abstract representation. This does not mean that they are entirely lost, since the abstract idea carries with it data not only on the schema but also on individual patterns (Section 111,B).Regardless of the source of stimulation, activation of the abstract idea is difficult to maintain for longer than a few seconds. These ideas are extremely speculative. However, they do produce some interesting consequences. First, the visual representation of a Ietter is not necessarily a passively decaying trace, but may be an actively created code which requires attention. This is suggested by the role that attention seems to play in the activation and maintenance of efficient visual matches. Second, visual and name components of a prior visual stimulus coexist within the memory system. If a t the time of presentation of a letter the abstract idea of that letter has already been activated, Ss may respond “same” without going to the name level. If the abstract idea is no longer active, they must then go t o the name level. The next section explores the possibility of gaining experimental control over these two components of the memory code. V. Separating the Visual and Name Codes of Prior Stimulation

Some recent studies have attempted to separate characteristics of newly presented visual stimuli from those that have been memorized. Chase and Posner (1965) compared searching a visual array of four letters for a single stored probe with searching a stored array for a single visually presented probe. They found differences both in search rate and in the effects of visual confusability between the conditions. Sternberg (1967b),in a more complete study, found that searching a memorized list was about equal in speed to searching the visual image of an immediately

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prior stimulus list. In his situation, the search through the image was self-terminating, while the search of the list was exhaustive. These studies suggest that there may be some differences in handling lists stored as visual arrays and lists stored as letter names. This section reports some experiments which seek to use the methods developed earlier in this chapter to understand differences between visual and name codes. I n this technique a visual array is used. Consider the presentation of a four-letter array for 1 second. The S has time to see and name the four letters. He can, therefore, be considered to have a list of the letter names. Previous data presented in this chapter indicate that he may also have a representation of a visual code of some or all of these letters, at least for a brief period. What happens when a probe letter occurs? It is possible that S refers the probe letter t o his visual code, to his name list, or perhaps both. The following experiments use the RT technique in order to separate the visual and name codes. A. MULTILETTERARRAYS The first experiment along this line (Posner & Taylor, 1969) involved the presentation of one-, two-, or four-letter arrays. The letters were always uppercase and were selected from B, H, M, Q , R, and Z. The stimulus arrays were thought to be relatively neutral with respect to visual and acoustic confusability. After presentation of the array, S received a random black-and-white pattern during a delay interval of either 10. 500, or 1500 msec. At the conclusion of that interval a single letter appeared, in the position of one of the letters in the array. The S’s task was to say whether that single letter had the same or a different name than the letter in the array that it had replaced. I n other words, it was necessary for the S to store all of the array in order to be correct, but he needed only to interrogate the array letter in the position of the probe to make his response. The four-letter positions were centered in the visual field and subtended a visual angle of about 2’. If the positions of the four-letter array were numbered from left to right, the single-letter array would always lie in Position 2 and the two-letter array in Positions 2 and 3. The design of the experiment was such that the letters presented at Position 2 were completely balanced over conditions. Thus, a relatively clean comparison could be made between one-, two-, and four-letter arrays with respect to Position 2 . The first question asked of the data was : Does the visual information at Position 2 vary as a function of the number of other letters that had

Michael I. Posner

86

MEAN RTs 2

FOR

AS A

TABLE IV PHYSICAL AND NAME“SAME” RESPONSES AT ARRAYPOSITION FUNCTION OF THE NUMBER OF LETTERS IN THE ARRAY Array length 1

2

4

Interval (msec)

P

N

N-P

P

N

N-P

P

N

N-P

10 500 1500 Percent error”

388 408 453 2

448 446 457 2.5

60 38 4 -

387 403 446 6.8

441 440 460 8.1

54 37 14 -

532 528 557 8.1

587 540 570 8.9

55

12 13 -

Error rates are collapsed over all array positions. P, physical; N, name.

to be stored? The answer to this question is contained in Table IV. The results show that at a 10-msecdelay the difference between physical and name identity RTs for Position 2 is about 50 msec ( p < .01). This is somewhat less than we normally obtain for single letters at time zero. This value declines with the delay interval ( p < .01) but does not vary as a function of the array length. I n Table V, the information from other positions in the array is shown. If one looks for evidence of visual information at these positions, the picture is quite different. The third and fourth letters in the four-letter array show little, if any, visual information as measured by the difference between physical and name identity. This has the effect of reducing the overall advantage of physical matches in the four-letter arrays over that found in the one- and two-letter arrays. For all positions, the difference between physical and name identity declines significantly with the number of letters ( p c: .01). So far, emphasis has been primarily upon the difference between physical and name identity. There is some hint that the number of letters in the array may have differential effects upon the name and visual codes. (See Table IV.) Physical matches tend to be fastest at the shortest delay interval regardless of the number of letters in the array. For name matches, however, increases in array length seem to delay the interval that gives the optimal RT. This could mean that with four letters in the array 1 second is not quite long enough to finish extracting and storing the letter names. If this explanation were correct it would imply that the visual and name codes could be manipulated separately.

Abstraction and the Process of Recognition

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TABLE V

MEAN RTs

FOR

PHYSICAL AND NAMESAME RESPONSES AT OTHERARRAY POSITIONS‘ Array length

2 Probe position 1 3 4

P

4

N

N-P

P

N

-

-

-

496

560 -

64 -

438 521 535

486 495 550

-

N-P 50 -26 15

Values are given in milliseconds. All data are from 10-msec-delayinverval. P, physical ; N, name.

B. MANIPULATINGTHE NAMECODE

In a study by Boies (1969) a single-letter array was used in the matching task. An operation was performed that could be expected to increase RTs based on the name code, while making relatively little difference for RTs based on the visual code. Prior to the presentation of each pair of visual letters, S heard a list of eight letters which he was to recall subsequent to making the match. After speaking these letters, E exposed a single visual uppercase letter for .5 second. Following that, there was a delay of either 0 or 2 seconds, during which a random checkerboard pattern was exposed. At the end of the delay, a single upper or lowercase probe letter was presented. The dependent variable was the time to respond whether or not the two visual letters had the same name. The results are shown in Fig. 10. The dotted lines in the figure represent trials on which there were no letters read prior to the matching task. Notice that the difference between physical and name identity RTs declines over the two intervals from about 75 msec to almost 0. The name match RTs are nearly flat, while the physical identity match RTs show a marked upswing. This confirms the pattern for the individual components of physical and name matches that have been found in most of the other studies in this series. (See Figs. 7 and 8.) The solid lines, however, are quite different. These come from trials in which S’s shortterm memory was filled with eight letter names. Physical identity matches are not affected by this operation. The name identity responses, however, do show a marked upswing.

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Michael I. Posner

It seems reasonable to describe these results as showing selective interference with matching at the name level. I n accordance with previous sections, it is possible to speculate on the process involved. The first letter activates the abstract representation corresponding to its visual form. This in turn produces the associated letter name which is stored in an auditory short-term memory. When the second letter occurs, it also contacts the abstract idea corresponding to its visual characteristics. If this representation is already active, because of the previous letter, S can make the match a t this level. There is no reason that a match at this level should be affected by storage of the letter names. However, if the probe letter makes contact with an unactivated abstract idea, the letter name must be located and matched with the previously stored name. Since this match must take place within a crowded short-term store, one would expect interference after a short interval.

-I

480

-

460

-

440

-

---4

Memory Nom/ load

0

E

420-

p Physical

k

400

IcaI

-

380 -

360

IIT"

0

2 lntervol (seconds)

FIG.10. RTs for physical and name matches when Ss had to retain eight letter names given prior to the match (memory load) as against normal conditions (no memory load). (After Boies, 1969.)

One important consequence of this finding is the demonstration that the lack of a difference between physical and name RTs cannot, by itself, be taken to mean that the visual code is entirely lost. In the study just reported, increasing the time for a name match produces evidence for

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the presence of a visual code (physical matches are significantly faster than name matches). This suggests that in the normal situation the visual code must be present after 2 seconds, but provides a less efficient basis for the match than the name code. Other techniques will be necessary to determine the full time course of activation of the abstract level. When one interferes with the name level there is little, if any, effect upon matches based on the visual code. It is of even more interest to ask the reverse question. What happens to the efficiency of name matches when one interferes with the visual code?

C. MANIPULATINGTHE VISUALCODE Two experiments were conducted in order to vary the visual and name codes separately (Posner & Taylor, 1969). An array of three letters was presented for either 1 second (Experiment I) or .5 second (Experiment 11). After termination of the array there was a delay interval filled with a checkerboard pattern. The delay ended with the presentation of the probe letter. The letters which are of interest in this study (target letters) were always an uppercase G, C, or D in the middle of the array. I n Experiment I, these target letters were embedded in either a visually similar context (0 and Q) or an acoustically similar context (Z and V). In Experiment 11, a neutral context (M and R ) was also used. The Ss were not informed of the special status of the target letters, and probes involved both the target and context letters. Each experiments involved 16 Ss working for 4 days, and were similar in all other ways except that in Experiment I1 the percentage of “same” responses was .67 while in Experiment I it was only .50. The trials of interest were the correct “same” RTs to the three target letters when the probe was physically identical and when it had only the same name. The results of both studies are shown in Table VI. It is clear that the RTs for physical identity responses are increased when the array is visually similar. This is shown both by the small difference between physical and name RTs for these arrays and by the increased time for the physical identity responses over their times in acoustic and neutral contexts. These effects are most striking at time zero, when normally a physical match is fastei than a name match. It should also be noted that the RTs for name responses are not longer in the visually similar arrays than in other arrays. There is a tendency for the name RTs to increase over time more with the acoustic context. However, this effect was observed only in the first experiment and is by no means clear from the data. The main result of these experiments indicates that when the letters G, C, and D are embedded in visually confusing arrays, Ss are not able to make an efficient physical identity match. This means either that Ss

Michael I. Posner

90

TABLE VI

MEAN RTs

FOR

PHYSICAL AND NAME SAMERESPONSES AS A FUNCTION OF ARRAY CONTEXT" Context Visual

Delay (msec)

P

N

Acoustic

N-P

P

N

Neutral N-P

P

N

N-P

-

-

-

-

-

-

-

-

-

377 402

409 425

32 23

Experiment I 0

500 1000

561 568 570

576 585 581

15 16 11

524 536 563

562 583 602

38 47 39

Experiment I1 0 500

401 418

408 423

7 5

373 408

406 419

33 11

Values are given in milliseconds. P, physical; N, name.

are not storing the visual code of the target letters as adequately when they are in the similar visual context, or that they are not able to retrieve information as efficiently from the visually confusing array. The latter view seems less likely because we conducted a control experiment in which both array and probe were presented simultaneously. The visually confusing context had no effect on RTs for either physical or name matches in this situation. Thus, it appears that visual confusion acts on the registration or maintenance of the visual code. Since the effects are fully present at time zero (see Table VI), it is not possible to separate the registration of the code from its maintenance. For example, the poorer visual code of the target letter in the visual confusion context could be the result of S's tendency to concentrate more closely on the difficult discrimination between 0 and Q. These results do show that it is possible to manipulate the adequacy of the visual code without disturbing the time for a name match. It follows from this that the stored codes are separate. Otherwise, anything that disturbed the visual code would also affect the time to obtain the names. How do these findings fit with previous data? The presence of the visual code for only a very limited number of letters seems to argue against an interpretation of this code as a passively decaying trace of the letters

Abstraction and the Process of Recognition

91

(Sperling, 1960). It has previously been suggested that the lack of effect of luminance, exposure duration, and noise, and the presence of rehearsal also serve as evidence that this visual code is at a higher level of processing. On the other hand, the data might be consistent with the speculation that this visual code represents act,ivation of the abstract level. (See Fig. 1.) I n order to determine the letter names, all array items must have activated the abstract level. However, the adequacy of the visual code, even shortly after presentation of the array, seems to depend upon a number of factors. In four-letter arrays, Positions 3 and 4 show no evidence of a visual code efficient enough to aid the match. The same is true of the middle letter in a visually confusing array. If the visual code corresponds to activation of an abstract idea, such activation cannot guarantee that it will provide an efficient match, even for the brief period indicated by the decay function (see Fig. 7 ) . Rather, the maintenance of this activity would have to depend upon the number and similarity of other items in the array. One way to conceptualize this is to suppose that formation and/or maintenance of the visual code requires active attention (processing capacity). When only a single letter is present, enough attention is usually available to extend the life of the code for at least a few seconds. As the number of letters increases, attention must be spread over more items and the rate of decay is increased. Similarly, the encoding of visually confusing items might tend to absorb more of the processing capacity than when the items are distinct. A physically identical probe letter would activate the same abstract representation as the array letter. When the activation of the abstract representation by the first letter ends, the efficiency of a physical match is lost. When the probe letter is not physically identical, it activates an abstract representation which is different from any array letter. I n this case, RT would always require retrieval of the name and would, therefore, be unaffected by anything that varied the period of activation of the abstract ideas. This view agrees with the finding that name matches are unaffected by a visually similar context. One finding that raises problems for this explanation is that “different” RT is faster if the probe letter is uppercase than if it is lowercase (Posner & Taylor, 1969). This occurs only with arrays oftwo or more items; thus it cannot result from differences in the discriminability of upper- and lowercase letters. It is possible that uppercase “different” responses rest primarily on the visual code, while lowercase “different” responses rest on the name code. This could indicate that Ss first decide on the case of the letter before making the match, but such a possibility would be inconsistent with the levels of processing outlined in Fig. 1. Another possibility is that the decision about the letter case goes on in parallel with the

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process of matching. If an uppercase letter fails to obtain a physical match, the “different” response can be made directly, while a lowercase letter would have to be subjected to name retrieval as well.

VISUALAND NAMECODES D. SEARCHING Previous studies of memorized lists of letter names and lists which might be represented as visual codes (Chase & Posner, 1965; Sternberg, 1967b) have involved a comparison of search rates. In the experiments discussed in this chapter, the probe letter was presented in the position of one of the items in the array. While there was a distinct bias toward the left side of the list, this cannot be viewed as a search process in the usual sense. It is more closely related to the difficulty of locating various spatial positions. The relation between number of items in the array and RT is positively accelerated with this technique (see Table IV), while in almost all search studies it is either linear (Sternberg, 1966) or negatively accelerated (Chase & Posner, 1965). Recently, Taylor and Posner (1968)reported a study designed to compare characteristics of searching the visual and name components of previous visual arrays. Their interest was less in search rate than in the order of search. The arrays always consisted of three uppercase letters centered in the field. The letters were either in alphabetical order (ordered arrays, e.g. BCD), or not in alphabetical order (unordered arrays, e.g. DBF). The array was present for 300 msec. After delays of .7, 1.2, or 3.2 seconds, during which the field was dark, a single probe letter appeared. The probe letter was either at the left or right side of the field and either upper- or lowercase. The S’s task was to respond “same” if the probe had the same name as any of the letters in the previous array. The data in Table V I I are RTs from the shortest delay interval only. The data from the longer delays are consistent with these, but less striking. Those trials using an uppercase probe (physical identity) are on the left while those using a lowercase probe (name identity) are on the right. When the probe is physically identical to an array letter, the RTs are fastest when the matching letter is adjacent to the probe. That is, a left probe is fastest when it matches the left-hand array letter, while a right probe is fastest when it matches a right-hand array letter. This effect occurs regardless of whether the arrays are ordered or not, and appears as a significant interaction between probe and array positions ( p < .01). When the probe matches the array letter only in name, a very different picture is observed. For the ordered array, the fastest times are always obtained when the match is to the left array letter (first in the alphabet), regardless of the position of the probe. Thus, only the effect of target position is significant ( p < .01). With the unordered array, there are no

93

Abstraction and the Process of Recognition

significant effects of probe or array position. The S appears to search from left to right when the probe is on the left, but there is no systematic order when the probe is on the right. These results suggest another difference between visual and name codes. The order of search through a stored array is quite different depending upon whether it involves the visual code or the letter names. The tendency for letter names to be searched in alphabetical order is not surprising. However, the finding that RTs based on the visual code increase with physical distance from the probe letter is more difficult to MEAN RT AS

A

TABLE VII FUNCTION OF ARRAY

AND

PROBE POSITION"

Target position

Target position

Ordered Storage Arrays

Probeposition

L

R

ii

L

569

645

607

R

643

588

ii

606

616

L

R

X

L

625

714

669

615

R

608

697

652

611

x

616

705

661

L

R

x

Unordered Storage Arrays

Probeposition

L

R

x

L

588

676

632

L

609

674

641

R

698

633

665

R

689

681

685

x

643

654

649

x

649

677

663

Left column represents physical same RTs while right column represents name same RTs. Upper blocks (ordered)are for arrays in alphabetical order, while lower blocks are for unordered arrays. Values are given in milliseconds. (I

explain. On the one hand, this seems to fit with the idea of a visual code that can be searched in any order. On the other hand, if the probe letter excites an already activated abstract idea, there is no reason to predict that RT will depend upon physical distance from the probe. In previous studies, the position of the probe letter could have been confounded with the efficiency of the visual code for that letter since left array letters

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might be coded more efficiently. However, in the current study, these are separated. The results appear to mean that the visual representation of the array not only preserves the visual descriptions of the individual letters, but also their spatial arrangement. This finding seems more in accord with a “passive trace” view than an LLabstractidea” account. Whether this finding is unique to an experiment which, like this one, uses a dark interpolated field, or whether it is a general feature of multiletter arrays is still unclear. E. SUMMARY The data introduced in this section support three propositions indicated by the theory outlined in the previous section. First, the visual and name components of the array are stored separately and may be interrogated and manipulated separately. Second, the visual code is not apassive trace, but can be maintained only for a limited number of letters. Third, the time period for which the abstract representation of the visual code can mediate efficient matches is short. This time is briefer for multiletter arrays than for a single letter, since Ss limited attentional capacity is divided in the multiletter task. On the other hand, the data indicate that the coding of a letter array may be more extensive than the visual description (abstract idea) and letter names. It may include the spatial arrangement of the letters as well.

VI. Summary and Conclusions The general structure outlined in Fig. 1 provides a framework for different levels of processing involved in simultaneous and successive matching tasks. Posner and Mitchell (1967) have shown that physical and name identity stages appear as components when Ss are instructed to classify letter pairs as “same” if they are both vowels or both consonants. Thus, the processes discussed in this chapter may be observed as parts of more complex classification tasks. I n the vowel-consonant case, Ss appear to derive the letter name before deciding whether the stimulus is a vowel or a consonant. However, this may not always be the case. For example, we may know that a face is female before we know who it is. Even with letters some classifications may be performed without obtaining the letter name.’ It is clear that the most specific name for a stimulus is not always derived before names that are logically superordinates. The techniques developed in this chapter may be able to throw more light on the psychological organization of such classifications. Studies currently being completed suggest that in the case of the classification letter-digit,Ss proceed to the category classificationwithout first having identified the letter name.

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Even within the domain of physical and name matches the simple structure of Fig. 1 may be deceptive. I n the course of this chapter, it has been shown that the levels are not joined in a serial chain by obligatory transformations. Rather, Ss can be matching the visual aspects of simultaneous letter pairs and at the same time referring them to past experience in order to obtain the name (Section 111,A). Nor does the construction of a code at one level necessarily obliterate the previous codes. After naming a letter, Ss may still show evidence of having a visual description present. These codes are separately stored, have their own time courses, and can be interrogated independently. (Section IV,V.) Given the lack of a determinate serial linkage, what is the value of the structural levels provided by Fig. 12 Perhaps the main advantage comes in studying the role of independent variables upon the perceptual process. I n Section 11,the effect of familiarity was reviewed. It was found that familiarity did affect the matching task a t the visual level, but only in the integration of successive units, not in the matching of a single unit. Visual confusability among letters in an array affects the eBciency of matches based upon a visual memory code, but not those that require identification of the letter name. Only a detailed account of the structure of perceptual and memory codes within the context of a particular task can provide a reasonable answer to questions concerning the effect of a some variable upon the perceptual process. The failure to provide such a structure leads to the conflicts that have so often attended such questions. The separation of visual memory codes from retention of letter names is an important aspect of current work. Much recent research has focused upon the fate of the visual trace of a letter (Sperling, 1960,1963; Neisser, 1967). A major issue has been whether the trace (icon) is a brief code whose fate was either erasure by visual input or replacement by the letter name, or whether it could serve as the basis of a more permanent visual memory. The status of the visual code studied by the RT method is not completely clear. The rapid decay function (see Fig. 7) and the ability t o search the code as a spatial array (Section V,D) seem to agree with the view that the physical match is based upon the passive trace of the immediate past stimulus. On the other hand, the lack of effects of luminance, duration and visual noise, the importance of attention, and the ability to rehearse and generate the visual code argue that the basis of a physical match is not the trace of the stimulus, but the activation of an abstract code which serves as an internal representation (abstract idea) of that class of prior visual experience. Perhaps some resolution of this conflict is obtained by the view that matching based upon the trace is replaced by matching based upon the abstract code as the prior stimulus is absorbed into the schema of previous experiences.

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Recent studies (Bahrick & Bouchee, 1968; Dallett, Wilcox, & D’Andrea, 1968) argue that there is a visual component to long-term memory (LTM). Moreover, there is evidence (Brooks, 1968; DeSoto, London, & Handel, 1965) that Ss can generate a visual code that has important objective consequences upon their performance. This evidence indicates that the visual aspects of a stimulus must be represented in LTM in addition to the stimulus name. The experiments reported in this chapter have used letters because of their convenient feature of providing common names to perceptually distinct forms, but the visual storage of information is likely to be of much more importance for pictorial and spatial information without ready verbal labels. For this reason, the studies of dot patterns were introduced to provide evidence about the functional system used to store information concerning past visual input. The abstract idea (Section II1,B) is a means for combining present and past input. It serves t o summarize the visual aspect of experience in the same way that a name summarizes experience a t another level. Having stored the name 2,S may no longer be able to tell whether the past stimulus was “a’) or “A.” I n the same way, having strengthened the abstract idea of “A,” he has lost information concerning the detailed shape of this particular example of-the letter. The idea of a visual memory does not require that Ss store the full details of every visual stimulus; rather, they can be combined and summarized. Section 1113 outlines the functional characteristics of this abstract level of representation. The schema preserves the central tendency of past visual experience and the individual exemplars define a category boundary. However, the dot pattern experiments were unable to provide much detail concerning this system. If experiments on generation of visual codes from letter names tap the same system, they may offer more promise of providing detailed information on the perceptual qualities of the abstract level. For example, it is possible to ask whether a generated visual representation has determinate size, color, orientation, or spatial position. The question can be considered by varying properties of the probe letter and observing their effects upon RT. It remains to be seen if such studies can provide a vehicle for analysis of the abstract level. REFERENCES Attneave, F. Transfer of experience with a class-schema to identification learning of patterns and shapes. Journal of Experimental Psychology, 1957, 54, 81-88. Attneave, F. Applications of i n f o m t i o n theory to psychology. New York: Holt, 1959. Bahrick, H. P., & Bouchee, B. Retention of visual and verbal codes of the same stimuli. Journal of Experimental Psychology, 1968, 78, 417-422.

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Bartlett, F. C. Remembering: A study in experimental and social psychology. London & New York: Cambridge University Press, 1932. Beck, J. Effect of orientation and of shape similarity on perceptual grouping. Perception & P s y c h o p h y s k , 1966, 1, 300-302. Boies, S. J. Rehearsal of visual codes of single letters. Unpublished master’s thesis, University of Oregon, 1969. Boies, S. J., Posner, M. I., & Taylor, R. L. Rehearsal of visual information from a single letter. Paper presented a t the meeting of the Western Psychological Association, San Diego, May, 1968. Brooks, L. R. Spatial and verbal components of the act of recall. Canadian Journal Of Psychology, 1968, 22, 349-368. Bruner, J. On perceptual readiness. Psychological Review, 1957, 64, 123-152. Chase, W. G., & Posner, M. I. The effect of visual and auditory confusability on visual and memory search tasks. Paper presented a t the meeting of the Psychonomics Society, Chicago, 1965. Cohen, B. H. Recall of categorized word lists. Journal of Experimental Psychology, 1963,65, 368-376. Conrad, R. Acoustic confusion in immediate memory. British Journal of P q chology, 1964, 55, 75-84. Cox, N. Effect of familiarization pretraining with random shapes on same-different judgment times. Unpublished master’s thesis, Carleton University, 1967. Dallett, K., Wilcox, S. G., & D’Andrea, L. Picture memory experiments. Journal of Experimental Psychology, 1968, 76, 312-320. DeSoto, C., London, M., & Handel, S. Social reasoning and spatial paralogic. J . of Personality a d Social Psychology, 1965, 4, 515-521. Dukes, W. F., & Bevan, W. Stimulus variation and repetition in the acquisition of naming responses. Journal of Experimental Psychology, 1967, ?4, 178-181. Edmonds, E. M., Mueller, M. & Evans, S. H. Effects of knowledge of results on mixed schema discrimination. Psychonomic Science, 1966, 6, 377-378. Egeth, H. E. Parallel versus serial processes in multidimensional stimulus discrimination. Perception & Psychophysics, 1966, 1, 245-252. Eichelman, W. H. Letters as units of processing in a visual matching task. Unpublished master’s thesis, University of Oregon, 1968. Evans, S. H. A brief statement of schema theory. Psychonomic Science, 1967, 8, 87-88. Fitts, P. M., Weinstein, M., Rappoport, M., Anderson, N., &Leonard,J. A. Stimulus correlates of visual pattern recognition : A probability approach. Journal of Experimental Psychology, 1956, 51, 1-11. Flavell, J. H. The developmental psychology of J e a n Piaget. Princeton, N.J. : Van Noatrand, 1963. Frost, R. Recognition of prototypes in running recognition memory experiments. Unpublished experiments, University of Oregon, 1968. Gibson, E. J. Learning to read. Science, 1965, 148, 1066-1072. Gibson, E. J., Bishop, C. H., Schiff, W., & Smith, J. Comparison of meaningfulness and pronounceability as grouping principles in perception and retention of verbal material. Journal of Experimental Psychology, 1964, 67, 173-182. Goldstein, K. Language and language disturbance. New York: Brune & Stratton, 1948. Gottsdanker, R., Broadbent, L., & Van Sant, C. Reaction time to single and to first signals. Journal of Experimental Psychology, 1963, 66, 163-167. Haber, R. N. Effect of prior knowledge of the stimulus on word-recognition processes. Journal of Experimental Psychology, 1965, 69, 282-286.

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Strange, W., Keeney, T., Kessel, F., & Jenkins, J. J. The abstraction over time of the prototype from distortions of random dot patterns. Paper presented at the meeting of the Midwestern Psychological Association, Chicago, May, 1968. Talland, G. Deranged memory. New York: Academic Press, 1965. Taylor, R. L., & Posner, M. I. Retrieval from visual and verbal memory codes. Paper presented at the meeting of the Western Psychological Association, San Diego, 1968. Uhr, L. Pattern recognition. New York: Wiley, 1966. Woodworth, R. S. Experimental psychology. New York: Holt, 1938.