Induction and categorization in young children: a similarity-based model

The authors present a similarity-based model of induction and categorization in young children (SINC). The model suggests that (a). linguistic labels contribute to the perceived similarity of compared entities and (b). categorization and induction are a function of similarity computed over perceptual information and linguistic labels. The model also predicts young children's similarity judgment, induction, and categorization performance under different stimuli and task conditions. Predictions of the model were tested and confirmed in 6 experiments, in which 4- to 5-year-olds performed similarity judgment, induction, and categorization tasks using artificial and real labels (Experiments 1-4) and recognition memory tasks (Experiments 5A and 5B). Results corroborate the similarity-based account of young children's induction and categorization, and they support both qualitative and quantitative predictions of the model.     

Linguistic labels: Conceptual markers or object features?

Linguistic labels affect inductive generalization; however, the mechanism underlying these effects remains unclear. According to one similarity-based model, SINC (similarity, induction, naming, and categorization), early in development labels are features of objects contributing to the overall similarity of compared entities, with early induction being similarity based. If this is the case, then not only identical but also phonologically similar labels may contribute to the overall similarity and thus to induction. These predictions were tested in a series of experiments with 5-year-olds and adults. In Experiments 1-5 participants performed a label extension task, whereas in Experiment 6 they performed a feature induction task. Results indicate that phonological similarity contributes to early induction and support the notion that for young children labels are features of objects.     

Disentangling similarity judgments from pragmatic judgments: Response to Sloutsky and Fisher (2012)

Sloutsky and Fisher (2012) attempt to reframe the results presented in Noles and Gelman (2012) as a pure replication of their original work validating the similarity, induction, naming, and categorization (SINC) model. However, their critique fails to engage with the central findings reported in Noles and Gelman, and their reanalysis fails to examine the key comparison of theoretical interest. In addition to responding to the points raised in Sloutsky and Fisher's (2012) critique, we elaborate on the pragmatic factors and methodological flaws present in Sloutsky and Fisher (2004) that biased children's similarity judgments. Our careful replication of that study suggests that, rather than measuring the influence of labels on judgments of perceptual similarity, the original design measured sensitivity to the pragmatics of task demands. Together, the results reported in Noles and Gelman and the methodological problems highlighted here represent a serious challenge to the validity of the SINC model specifically and the words-as-features view more generally. (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

儿童早期分类与基于类别的归纳的一致性

传统的观点认为,儿童早期的分类是基于类别的归纳的基础。根据这种观点,儿童早期的分类与基于类别的归纳是一致的。该研究在不同材料条件下测试了4岁儿童面临知觉相似和概念冲突时的自由分类与归纳推理的一致性。研究结果显示,在照片条件下,4岁儿童的自由分类和基于类别的归纳是不一致的,儿童的分类主要是基于知觉相似的,而基于类别的归纳主要是基于概念的;在线条画条件下,儿童的分类与基于类别的归纳是一致的,都主要是基于知觉相似的。这些结果显示,儿童早期的分类和基于类别的关系是复杂的。     

Holistic processing of shape cues in face identification: Evidence from face inversion,composite faces,and acquired prosopagnosia

According to a classical functional architecture of face processing (Bruce & Young, 1986), sex processing on faces is a parallel function to individual face recognition. One consequence of the model is thus that sex categorization on faces is not influenced by face familiarity. However, the behavioural and neuro-psychological evidences supporting this dissociation are yet equivocal. To test the independence between sex processing on faces and familiar face recognition, familiar (learned) faces were morphed with new faces, generating facial continua of visual similarity to familiar faces. First, a pilot experiment shown that subjects familiarized with one extreme of the face continuum roughly perceive one half of the continuum (60 to 100% of visual similarity to familiar faces) as made of familiar faces and the other part as unfamiliar. In the experiment proper, subjects were familiarized with faces and tested in a sex decision task made on faces at the different steps of the continua. Subjects were significantly quicker at telling the sex of faces perceived as familiar (60-100%), and the effect was not observed in a control (untrained) group. These results indicate that familiar face representations are activated before sex categorization is completed, and can facilitate this processing. The nature of the interaction between sex categorization on faces and familiar face recognition is discussed.     

Exemplar-based accounts of "multiple-system" phenomena in perceptual categorization

We demonstrate that a wide variety of recently reported "rule-described" and "prototype-described" phenomena in perceptual classification, which have led to the development of a number of multiple-system models, can be given an alternative interpretation in terms of a single-system exemplar-similarity model. The phenomena include various rule- and prototype-described patterns of generalization, dissociations between categorization and similarity judgments, and dissociations between categorization and old-new recognition. The alternative exemplar-based interpretation relies on the idea that similarity is not an invariant relation but a context-dependent one. Similarity relations among exemplars change systematically because of selective attention to dimensions and because of changes in the level of sensitivity relating judged similarity to distance in psychological space. Adaptive learning principles may help explain the systematic influence of the selective attention process and of modulation in sensitivity settings on judged similarity.     

Category-based induction from similarity of neural activation

The idea that similarity might be an engine of inductive inference dates back at least as far as David Hume. However, Hume’s thesis is difficult to test without begging the question, since judgments of similarity may be infected by inferential processes. We present a one-parameter model of category-based induction that generates predictions about arbitrary statements of conditional probability over a predicate and a set of items. The prediction is based on the unconditional probabilities and similarities that characterize that predicate and those items. To test Hume’s thesis, we collected brain activation from various regions of the ventral visual stream during a categorization task that did not invite comparison of categories. We then calculated the similarity of those activation patterns using a simple measure of vectorwise similarity and supplied those similarities to the model. The model’s outputs correlated well with subjects’ judgments of conditional probability. Our results represent a promising first step toward confirming Hume’s thesis; similarity, assessed without reference to induction, may well drive inductive inference.     

Exemplar accounts of blending and distinctiveness effects in perceptual old-new recognition

Recent findings from the perceptual old-new recognition literature indicate that observers have extremely high false-alarm rates to new items that are "blends" of old ones. In addition, evidence suggests that "distinctive" old items--that is, those located in isolated regions of the similarity space--are recognized with higher probability than are typical old items. Both types of phenomena challenge the predictions of global-familiarity exemplar models of perceptual old-new recognition, which posit that the probability that an observer judges an item as old is based on its summed similarity to previously presented exemplars. In the present research the authors pursued these blending and distinctiveness effects by testing paradigms in which similarity relations among objects are highly controlled and in which the variables of blending and distinctiveness are not confounded with other properties associated with the individual objects themselves. In contrast to previous results, the authors found effects of blending and distinctiveness that are compatible with the predictions of a pure summed-similarity exemplar model.     

Predicting similarity and categorization from identification.

In this article, the relation between the identification, similarity judgment, and categorization of multidimensional perceptual stimuli is studied. The theoretical analysis focused on general recognition theory (GRT), which is a multidimensional generalization of signal detection theory. In one application, 2 Ss first identified a set of confusable stimuli and then made judgments of their pairwise similarity. The second application was to Nosofsky's (1985b, 1986) identification-categorization experiment. In both applications, a GRT model accounted for the identification data better than Luce's (1963) biased-choice model. The identification results were then used to predict performance in the similarity judgment and categorization conditions. The GRT identification model accurately predicted the similarity judgments under the assumption that Ss allocated attention to the 2 stimulus dimensions differently in the 2 tasks. The categorization data were predicted successfully without appealing to the notion of selective attention. Instead, a simpler GRT model that emphasized the different decision rules used in identification and categorization was adequate.     

Memory storage and retrieval processes in category learning

The detailed course of learning is studied for categorization tasks defined by independent or contingent probability distributions over the features of category exemplars. College-age subjects viewed sequences of bar charts that simulated symptom patterns and responded to each chart with a recognition and a categorization judgment. Fuzzy, probabilistically defined categories were learned relatively rapidly when individual features were correlated with category assignment, more slowly when only patterns carried category information. Limits of performance were suboptimal, evidently because of capacity limitations on judgmental processes as well as limitations on memory. Categorization proved systematically related to feature and exemplar probabilities, under different circumstances, and to similarity among exemplars of categories. Unique retrieval cues for exemplar patterns facilitated recognition but entered into categorization only at retention intervals within the range of short-term memory. The findings are interpreted within the framework of a general array model that yields both exemplar-similarity and feature-frequency models as special cases and provides quantitative accounts of the course of learning in each of the categorization tasks studied.     

Feature sampling in categorization and recognition of objects

This article presents an overview of some recent work on the time course of perceptual categorization and recognition memory. First, The EGCM-RT, which is a feature-sampling model of the time course of categorization, is described. It is shown that the model explains a wide range of categorization data. Second, an overview is given of a feature-sampling model of the time course of recognition that is derived from the EGCM-RT. This model explains results that have been interpreted in the past as evidence for dual-process models of recognition, and it provides a single-process alternative to dual-process accounts.     

Attention, similarity, and the identification-categorization relationship

A unified quantitative approach to modeling subjects' identification and categorization of multidimensional perceptual stimuli is proposed and tested. Two subjects identified and categorized the same set of perceptually confusable stimuli varying on separable dimensions. The identification data were modeled using Shepard's (1957) multidimensional scaling-choice framework. This framework was then extended to model the subjects' categorization performance. The categorization model, which generalizes the context theory of classification developed by Medin and Schaffer (1978), assumes that subjects store category exemplars in memory. Classification decisions are based on the similarity of stimuli to the stored exemplars. It is assumed that the same multidimensional perceptual representation underlies performance in both the identification and categorization paradigms. However, because of the influence of selective attention, similarity relationships change systematically across the two paradigms. Some support was gained for the hypothesis that subjects distribute attention among component dimensions so as to optimize categorization performance. Evidence was also obtained that subjects may have augmented their category representations with inferred exemplars. Implications of the results for theories of multidimensional scaling and categorization are discussed.     

Perceptual development and categorization: I. An investigation of task demands, stimulus set similarity, and age

This research addressed the apparent inconsistency in the literature between perceptual development as a progression of increasing separability (Shepp, 1978; Smith & Kemler, 1977, 1978) and categorization as a process based on overall similarity relations across development (Mervis, 1980; Mervis & Rosch, 1981). The influence of task demands, stimulus set similarity, and age on organizing principles of perceptual similarity were examined. Findings suggest that stimulus set similarity is an important factor in determining organizing principles of similarity for both nursery school children and adults.     

Dissociations Between Categorization and Recognition in Amnesic and Normal Individuals: An Exemplar-Based Interpretation

In recent work, the finding of dissociations between categorization and recognition in amnesic and normal individuals has been taken as evidence of multiple memory systems mediating these tasks. The present research provides support for the alternative idea that these dissociations can be interpreted in terms of a single-system exemplar-memory model that makes allowance for parameter differences across groups. In one experiment, a parameter change in memory sensitivity was induced by testing classification and recognition at varying delays; the results closely matched the ones observed by Knowlton and Squire (1993) for normal and amnesic participants. The exemplar model also yielded good quantitative predictions of the categorization-recognition dissociation. A second analysis demonstrated that dissociations between early versus late probabilistic classification learning and memory sensitivity were also well predicted by the single-system exemplar model. Limitations of the exemplar interpretation and future research directions are also discussed.     

Similarity Judgment Within and Across Categories: A Comprehensive Model Comparison

Similarity is one of the most important relations humans perceive, arguably subserving category learning and categorization, generalization and discrimination, judgment and decision making, and other cognitive functions. Researchers have proposed a wide range of representations and metrics that could be at play in similarity judgment, yet have not comprehensively compared the power of these representations and metrics for predicting similarity within and across different semantic categories. We performed such a comparison by pairing nine prominent vector semantic representations with seven established similarity metrics that could operate on these representations, as well as supervised methods for dimensional weighting in the similarity function. This approach yields a factorial model structure with 126 distinct representation-metric pairs, which we tested on a novel dataset of similarity judgments between pairs of cohyponymic words in eight categories. We found that cosine similarity and Pearson correlation were the overall best performing unweighted similarity functions, and that word vectors derived from free association norms often outperformed word vectors derived from text (including those specialized for similarity). Importantly, models that used human similarity judgments to learn category-specific weights on dimensions yielded substantially better predictions than all unweighted approaches across all types of similarity functions and representations, although dimension weights did not generalize well across semantic categories, suggesting strong category context effects in similarity judgment. We discuss implications of these results for cognitive modeling and natural language processing, as well as for theories of the representations and metrics involved in similarity.     

Attention and learning processes in the identification and categorization of integral stimuli

The relationship between subjects' identification and categorization learning of integral-dimension stimuli was studied within the framework of an exemplar-based generalization model. The model was used to predict subjects' learning in six different categorization conditions on the basis of data obtained in a single identification learning condition. A crucial assumption in the model is that because of selective attention to component dimensions, similarity relations may change in systematic ways across different experimental contexts. The theoretical analysis provided evidence that, at least under unspeeded conditions, selective attention may play a critical role in determining the identification-categorization relationship for integral stimuli. Evidence was also provided that similarity among exemplars decreased as a function of identification learning. Various alternative classification models, including prototype, multiple-prototype, average distance, and "value-on-dimensions" models, were unable to account for the results.     

特征相似性、类别标签与因果关系在归纳推理中的作用

采用人工材料,比较类别标签、特征相似性与因果关系对归纳推理强度的影响。包括两个实验,实验1比较类别标签与特征相似性对归纳推理的影响,结果表明,当类别标签对归纳推理的影响显著强于特征相似性时,不能将类别标签等同于一个相似性特征。实验2进一步探讨类别标签与因果关系对归纳推理的作用,结果表明,因果关系作用明显强于类别标签的作用。综合两个实验的结果并整合前人相关研究,提出了不同关系影响归纳推理的强度假想。     

Great apes’ capacities to recognize relational similarity

Recognizing relational similarity relies on the ability to understand that defining object properties might not lie in the objects individually, but in the relations of the properties of various object to each other. This aptitude is highly relevant for many important human skills such as language, reasoning, categorization and understanding analogy and metaphor. In the current study, we investigated the ability to recognize relational similarities by testing five species of great apes, including human children in a spatial task. We found that all species performed better if related elements are connected by logico-causal as opposed to non-causal relations. Further, we find that only children above 4 years of age, bonobos and chimpanzees, unlike younger children, gorillas and orangutans display some mastery of reasoning by non-causal relational similarity. We conclude that recognizing relational similarity is not in its entirety unique to the human species. The lack of a capability for language does not prohibit recognition of simple relational similarities. The data are discussed in the light of the phylogenetic tree of relatedness of the great apes.     

Do development and learning really decrease memory? On similarity and category-based induction in adults and children

In a recently published study, Sloutsky and Fisher [Sloutsky, V. M., & Fisher, A.V. (2004a). When development and learning decrease memory: Evidence against category-based induction in children. Psychological Science, 15, 553-558; Sloutsky, V. M., & Fisher, A. V. (2004b). Induction and categorization in young children: A similarity-based model. Journal of Experimental Psychology: General, 133, 166-188.] demonstrated that children have better memory for the items that they generalise to than do adults. On the basis of this finding, they claim that children and adults use different mechanisms for inductive generalisations; whereas adults focus on shared category membership, children project properties on the basis of perceptual similarity. Sloutsky & Fisher attribute children's enhanced recognition memory to the more detailed processing required by this similarity-based mechanism. In Experiment 1 we show that children look at the stimulus items for longer than adults. In Experiment 2 we demonstrate that although when given just 250ms to inspect the items children remain capable of making accurate inferences, their subsequent memory for those items decreases significantly. These findings suggest that there are no necessary conclusions to be drawn from Sloutsky & Fisher's results about developmental differences in generalisation strategy.