Central tendencies, extreme points, and prototype enhancement effects in ill-defined perceptual categorization

In three perceptual classification experiments involving ill-defined category structures, extreme prototype enhancement effects were observed in which prototypes were classified more accurately than other category instances. Such empirical findings can prove theoretically challenging to exemplar-based models of categorization if prototypes are psychological central tendencies of category instances. We found instead that category prototypes were sometimes better characterized as psychological extreme points relative to contrast categories. Extending a classic and widely cited study (Posner & Keele, 1968), participants learned categories created from distortions of dot patterns arranged in familiar shapes. Participants then made pairwise similarity judgements of the patterns. Multidimensional scaling (MDS) analyses of the similarity data revealed the prototypes to be psychological extreme points, not central tendencies. Evidence for extreme point representations was also found for novel prototype patterns displaying a symmetry structure and for prototypes of grid patterns used in recent studies by McLaren and colleagues (McLaren, Bennet, Guttman-Nahir, Kim, & M ackintosh, 1995). When used in combination with the derived M DS solutions, an exemplar-based model of categorization, the Generalized Context Model (Nosofsky, 1986), provided good fits to the observed categorization data in all three experiments.     

Distinguishing prototype-based and exemplar-based processes in dot-pattern category learning

The authors contrast exemplar-based and prototype-based processes in dot-pattern categorization. In Experiments 1A and 1B, participants provided similarity ratings of dot-distortion pairs that were distortions of the same originating prototype. The results show that comparisons to training exemplars surrounding the prototype create flat typicality gradients within a category and small prototype-enhancement effects, whereas comparisons to a prototype center create steep typicality gradients within a category and large prototype-enhancement effects. Thus, prototype and exemplar theories make different predictions regarding common versions of the dot-distortion task. Experiment 2 tested these different predictions by having participants learn dot-pattern categories. The steep typicality gradients, the large prototype effects, and the superior fit of prototype models suggest that participants refer to-be-categorized items to a representation near the category's center (the prototype), and not to the training exemplars that surround the prototype.     

Array training in a categorization task

Two components of categorization, within-category commonalities and between-category distinctiveness, were investigated in a categorization task. Subjects learned three prototype categories composed of moderately high distortions, by observing arrays containing patterns that belonged either to a common prototype category or to three different categories; a third group learned patterns presented one at a time, mirroring the standard paradigm. Following 6 learning blocks, subjects transferred to old patterns and new patterns at low-, medium-, and high-level distortions of the category prototype. The results showed that array training facilitated learning, especially when patterns in the array belonged to the same category. Transfer results showed a strong gradient effect across pattern distortion level for all conditions, with the highest performance obtained following array training on different category patterns and worst in the control condition. Interestingly, the old training patterns were classified worse than new low and no better than medium distortions. Neither this ordering nor the steepness of the gradient across prototype similarity for each condition could be predicted by the generalized context model. A prototype model better captured the steep gradient and ordinal pattern of results, although the overall fits were only slightly better than the exemplar model. The crucial role played by category commonalities and distinctiveness on categorical representations is addressed.     

Journey to the center of the category: the dissociation in amnesia between categorization and recognition

The authors' theoretical analysis of the dissociation in amnesia between categorization and recognition suggests these conclusions: (a) Comparing to-be-categorized items to a category center or prototype produces strong prototype advantages and steep typicality gradients, whereas comparing to-be-categorized items to the training exemplars that surround the prototype produces weak prototype advantages and flat typicality gradients; (b) participants often show the former pattern, suggesting their use of prototypes; (c) exemplar models account poorly for these categorization data, but prototype models account well for them; and (d) the recognition data suggest that controls use a single-comparison exemplar-memorization process more powerfully than amnesics. By pairing categorization based in prototypes with recognition based in exemplar memorization, the authors support and extend other recent accounts of cognitive performance that intermix prototypes and exemplars, and the authors reinforce traditional interpretations of the categorization-recognition dissociation in amnesia.     

Classification of empirically derived prototypes as a function of category experience

In three experiments, subjects learned to classify dot patterns into three categories represented by either three, six, or nine exemplars. Following learning, subjects were tested on an additional set of patterns, which included patterns from the learning phase, the category objective prototypes, and new distortions of the objective prototypes. Also included in the test set were empirical prototypes and distortions of empirical prototypes. Empirical prototypes were derived by averaging feature values of category exemplars in the learning phase. The overall results revealed that empirical prototypes were classified more accurately than were objective prototypes. In addition, a pattern of convergence in error rates was observed for distortions of the objective and empirical prototypes as category set size increased, but this same pattern was not observed for the objective and empirical prototypes themselves. This lack of convergence for the prototypes is inconsistent with explanations of the category set size effect that rely on the central limit theorem.     

Episodic and prototype models of category learning

The question of what processes are involved in the acquisition and representation of categories remains unresolved despite several decades of research. Studies using the well-known prototype distortion task (Posner and Keele in J Exp Psychol 77:353–363, 1968) delineate three candidate models. According to exemplar-based models, we memorize each instance of a category and when asked to decide whether novel items are category members or not, the decision is explicitly based on a similarity comparison with each stored instance. By contrast, prototype models assume that categorization is based on the similarity of the target item to an implicit abstraction of the central tendency or average of previously encountered instances. A third model suggests that the categorization of prototype distortions does not depend on pre-exposure to study exemplars at all and instead reflects properties of the stimuli that are easily learned during the test. The four experiments reported here found evidence that categorization in this task is predicated on the first and third of these models, namely transfer at test and the exemplar-based model. But we found no evidence for the second candidate model that assumed that categorization is based on implicit prototype abstraction.     

The nature and structure of infant form categories

The nature of form categories in 3 to 4-month infants was studied using the visual preference for novelty in the familiarization-novelty paradigm. Novelty preference indicates habituation to and recognition of the familiar. In a series of experiments employing three form categories composed of dot patterns, generalized habituation to new category members was used to assess categorization behavior in the recognition of visual forms. At 3 to 4 months of age, infants did not initially show any systematic preferences for “good” or symmetrical examples of a category relative to “distorted” examples (Experiment 1) and this was true for all three form categories used (i.e., square, triangle, and diamond). Evidence for categorization was seen in the recognition performance of 3- to 4-month infants (Experiment 2). Infants showed generalized habituation to the previously unseen category prototypes following exposure to six exemplars within each of the three form categories. Given evidence that infants could discriminate between the prototype and other category members (Experiment 3), “inability to discriminate” was ruled out as an explanation for this form categorization or generalized habituation effect. Four subsequent experiments were conducted to determine whether infants exhibit a prototypicality structure for their remembered categories and whether certain conditions which have been shown to enhance prototypicality effects with adults have similar effects with infants. No evidence of a prototypicality structure was found for the form categories of infants when the number of exemplars during familiarization was limited to 6 and the test for form recognition followed immediately (Experiment 4). However, a prototypicality structure for the remembered form categories was found when a 3-min delay was introduced between familiarization and tests for form recognition (Experiment 5), when 12 exemplars were presented during familiarization (Experiment 7), or when the prototype was included as one of the six exemplars during the familiarization period (Experiment 6).     

Are there representational shifts during category learning?

Early theories of categorization assumed that either rules, or prototypes, or exemplars were exclusively used to mentally represent categories of objects. More recently, hybrid theories of categorization have been proposed that variously combine these different forms of category representation. Our research addressed the question of whether there are representational shifts during category learning. We report a series of experiments that tracked how individual subjects generalized their acquired category knowledge to classifying new critical transfer items as a function of learning. Individual differences were observed in the generalization patterns exhibited by subjects, and those generalizations changed systematically with experience. Early in learning, subjects generalized on the basis of single diagnostic dimensions, consistent with the use of simple categorization rules. Later in learning, subjects generalized in a manner consistent with the use of similarity-based exemplar retrieval, attending to multiple stimulus dimensions. Theoretical modeling was used to formally corroborate these empirical observations by comparing fits of rule, prototype, and exemplar models to the observed categorization data. Although we provide strong evidence for shifts in the kind of information used to classify objects as a function of categorization experience, interpreting these results in terms of shifts in representational systems underlying perceptual categorization is a far thornier issue. We provide a discussion of the challenges of making claims about category representation, making reference to a wide body of literature suggesting different kinds of representational systems in perceptual categorization and related domains of human cognition.     

Refining the visual-cortical hypothesis in category learning

Participants produce steep typicality gradients and large prototype-enhancement effects in dot-distortion category tasks, showing that in these tasks to-be-categorized items are compared to a prototypical representation that is the central tendency of the participant’s exemplar experience. These prototype-abstraction processes have been ascribed to low-level mechanisms in primary visual cortex. Here we asked whether higher-level mechanisms in visual cortex can also sometimes support prototype abstraction. To do so, we compared dot-distortion performance when the stimuli were size constant (allowing some low-level repetition-familiarity to develop for similar shapes) or size variable (defeating repetition-familiarity effects). If prototype formation is only mediated by low-level mechanisms, stimulus-size variability should lessen prototype effects and flatten typicality gradients. Yet prototype effects and typicality gradients were the same under both conditions, whether participants learned the categories explicitly or implicitly and whether they received trial-by-trial reinforcement during transfer tests. These results broaden out the visual-cortical hypothesis because low-level visual areas, featuring retinotopic perceptual representations, would not support robust category learning or prototype-enhancement effects in an environment of pronounced variability in stimulus size. Therefore, higher-level cortical mechanisms evidently can also support prototype formation during categorization.     

Concept learning,memory and transfer of dot pattern categories

In the first experiment, subjects rated the similarity of a sample of pairs of random dot patterns generated from 3 prototypes consisting of either 4, 6, or 9 dots. The results of the experiment tended to confirm the structure imposed on the patterns by the construction method. In the second experiment, subjects learned to classify random patterns generated from 2 prototypes with either short or long interprototype distance and consisting of either 4, 6, or 9 dots in a traditional concept identification task. After acquisition, memory for old and new distortions and the prototype, which was not presented during learning, was assessed. The tendency to call a pattern “new” increased with the distance between the pattern and its prototype. In a subsequent transfer test, all subjects saw patterns of either 4, 6, or 9 dots. Performance was above chance and the transfer from larger to smaller patterns tended to be greater than the transfer from smaller to larger patterns. This is consistent with a process of schema formation based on features common to most exemplars of the category. The results are discussed in relation to several theories of concept learning and schema abstraction.     

知道与不知道要学多少：类别学习中样例量的预期作用

采用“5/4模型”类别结构探讨了类别学习中样例量的预期作用。设置了两种学习条件(“知道样例量”和“不知道样例量”), 分别探讨两种学习条件下的学习效率、学习策略以及所形成的类别表征。106名大学生参加了实验, 结果表明：在类别学习中, 样例量的预期作用显著, 知道样例量组的学习效率高于不知道样例量组; 样例量的预期作用对类别学习效率的影响是通过影响学习过程中使用的策略来实现的; 样例量的预期作用不影响两种学习条件的学习后形成的类别表征, 且两种学习条件的被试自始至终表现出样例学习的表征模式。     

Problem structure and the use of base-rate information from experience

This article is concerned with the use of base-rate information that is derived from experience in classifying examples of a category. The basic task involved simulated medical decision making in which participants learned to diagnose hypothetical diseases on the basis of symptom information. Alternative diseases differed in their relative frequency or base rates of occurrence. In five experiments initial learning was followed by a series of transfer tests designed to index the use of base-rate information. On these tests, patterns of symptoms were presented that suggested more than one disease and were therefore ambiguous. The alternative or candidate diseases on such tests could differ in their relative frequency of occurrence during learning. For example, a symptom might be presented that had appeared with both a relatively common and a relatively rare disease. If participants are using base-rate information appropriately (according to Bayes' theorem), then they should be more likely to predict that the common disease is present than that the rare disease is present on such ambiguous tests. Current classification models differ in their predictions concerning the use of base-rate information. For example, most prototype models imply an insensitivity to base-rate information, whereas many exemplar-based classification models predict appropriate use of base-rate information. The results reveal a consistent but complex pattern. Depending on the category structure and the nature of the ambiguous tests, participants use base-rate information appropriately, ignore base-rate information, or use base-rate information inappropriately (predict that the rare disease is more likely to be present). To our knowledge, no current categorization model predicts this pattern of results. To account for these results, a new model is described incorporating the ideas of property or symptom competition and context-sensitive retrieval.     

Contrasting Cortical Activity Associated with Category Memory and Recognition Memory

We collected functional neuroimaging data while volunteers performed similar categorization and recognition memory tasks. In the categorization task, volunteers first studied a series of 40 dot patterns that were distortions of a nonstudied prototype dot pattern. After a delay, while fMRI data were collected, they categorized 72 novel dot patterns according to whether or not they belonged to the previously studied category. In the recognition task, volunteers first studied five dot patterns eight times each. After a delay, while fMRI data were collected, they judged whether each of 72 dot patterns had been studied earlier. We found strikingly different patterns of brain activity in visual processing areas for the two tasks. During the categorization task, the familiar stimuli were associated with decreased activity in posterior occipital cortex, whereas during the recognition task, the familiar stimuli were associated with increased activity in this area. The findings indicate that these two types of memory have contrasting effects on early visual processing and reinforce the view that declarative and nondeclarative memory operate independently.     

The modulating influence of category size on the classification of exception patterns

Generalization gradients to exception patterns and the category prototype were investigated in two experiments. In Experiment 1, participants first learned categories of large size that contained a single exception pattern, followed by a transfer test containing new instances that had a manipulated similarity relationship to the exception or a nonexception training pattern as well as distortions of the prototype. The results demonstrated transfer gradients tracked the prototype category rather than the feedback category of the exception category. In Experiment 2, transfer performance was investigated for categories varying in size (5, 10, 20), partially crossed with the number of exception patterns (1, 2, 4). Here, the generalization gradients tracked the feedback category of the training instance when category size was small but tracked the prototype category when category size was large. The benefits of increased category size still emerged, even with proportionality of exception patterns held constant. These, and other outcomes, were consistent with a mixed model of classification, in which exemplar influences were dominant with small-sized categories and/or high error rates, and prototype influences were dominant with larger sized categories.     

The modulating influence of category size on the classification of exception patterns

Generalization gradients to exception patterns and the category prototype were investigated in two experiments. In Experiment 1, participants first learned categories of large size that contained a single exception pattern, followed by a transfer test containing new instances that had a manipulated similarity relationship to the exception or a nonexception training pattern as well as distortions of the prototype. The results demonstrated transfer gradients tracked the prototype category rather than the feedback category of the exception category. In Experiment 2, transfer performance was investigated for categories varying in size (5, 10, 20), partially crossed with the number of exception patterns (1, 2, 4). Here, the generalization gradients tracked the feedback category of the training instance when category size was small but tracked the prototype category when category size was large. The benefits of increased category size still emerged, even with proportionality of exception patterns held constant. These, and other outcomes, were consistent with a mixed model of classification, in which exemplar influences were dominant with small-sized categories and/or high error rates, and prototype influences were dominant with larger sized categories.     

Similarity-scaling studies of dot-pattern classification and recognition.

Classification performance in the dot-pattern, prototype-distortion paradigm (e.g., Posner & Keele, 1968) was modeled within a multidimensional scaling (MDS) framework. MDS solutions were derived for sets of dot patterns that were generated from prototypes. These MDS solutions were then used in conjunction with exemplar, prototype, and combined models to predict classification and recognition performance. Across 3 experiments, an MDS-based exemplar model accounted for the effects of several fundamental learning variables, including level of distortion of the patterns, category size, delay of transfer phase, and item frequency. Most important, the model quantitatively predicted classification probabilities for individual dot patterns in the sets, not simply general trends of performance. There was little evidence for the existence of a prototype-abstraction process that operated above and beyond pure exemplar-based generalization.     

Perceptual fluency can be used as a cue for categorization decisions

Learning in the prototype distortion task is thought to involve perceptual learning in which category members experience an enhanced visual response (Ashby & Maddox. Annual Review of Psychology, 56, 149-178, 2005). This response likely leads to more-efficient processing, which in turn may result in a feeling of perceptual fluency for category members. We examined the perceptual-fluency hypothesis by manipulating fluency independently from category membership. We predicted that when perceptual fluency was induced using subliminal priming, this fluency would be misattributed to category membership and would affect categorization decisions. In a prototype distortion task, the participants were more likely to judge stimuli that were not members of the category as category members when the nonmembers were made perceptually fluent with a matching subliminal prime. This result suggests that perceptual fluency can be used as a cue during some categorization decisions. In addition, the results provided converging evidence that some types of categorization are based on perceptual learning.     

Prototypes in category learning: the effects of category size, category structure, and stimulus complexity

Although research in categorization has sometimes been motivated by prototype theory, recent studies have favored exemplar theory. However, some of these studies focused on small, poorly differentiated categories composed of simple, 4-dimensional stimuli. Some analyzed the aggregate data of entire groups. Some compared powerful multiplicative exemplar models to less powerful additive prototype models. Here, comparable prototype and exemplar models were fit to individual-participant data in 4 experiments that sampled category sets varying in size, level of category structure, and stimulus complexity (dimensionality). The prototype model always fit the observed data better than the exemplar model did. Prototype-based processes seemed especially relevant when participants learned categories that were larger or contained more complex stimuli.     

A high-distortion enhancement effect in the prototype-learning paradigm: Dramatic effects of category learning during test

Recent research suggests that exemplar models of classification are disconfirmed by the finding of extreme prototype-enhancement effects and steep typicality gradients in a version of the prototype-learning paradigm. We argue that these results are due to learning-during-transfer effects and not to the abstraction of a prototype from the training instances. In the standard version of the paradigm, observers are flooded with multiple presentations of the prototype and its low distortions during transfer. In a modified transfer condition, we instead present multiple instances of an arbitrary high distortion and low distortions of that high distortion. An extreme "high-distortion enhancement effect" is observed. Also, there is a flattening of the typicality gradient associated with the standard patterns (prototype, low distortions, and standard high distortions). The results provide dramatic evidence of the role of learning during transfer in this task and force a reevaluation of the dominant current interpretation of the steep typicality gradient.     

Prototypes are attractive because they are easy on the mind

People tend to prefer highly prototypical stimuli--a phenomenon referred to as the beauty-in-averageness effect. A common explanation of this effect proposes that prototypicality signals mate value. Here we present three experiments testing whether prototypicality preference results from more general mechanisms-fluent processing of prototypes and preference for fluently processed stimuli. In two experiments, participants categorized and rated the attractiveness of random-dot patterns (Experiment 1) or common geometric patterns (Experiment 2) that varied in levels of prototypicality. In both experiments, prototypicality was a predictor of both fluency (categorization speed) and attractiveness. Critically, fluency mediated the effect of prototypicality on attractiveness, although some effect of prototypicality remained when fluency was controlled. The findings were the same whether or not participants explicitly considered the pattern's categorical membership, and whether or not categorization fluency was salient when they rated attractiveness. Experiment 3, using the psychophysiological technique of facial electromyography, confirmed that viewing abstract prototypes elicits quick positive affective reactions.