Category use and category learning

Categorization models based on laboratory research focus on a narrower range of explanatory constructs than appears necessary for explaining the structure of natural categories. This mismatch is caused by the reliance on classification as the basis of laboratory studies. Category representations are formed in the process of interacting with category members. Thus, laboratory studies must explore a range of category uses. The authors review the effects of a variety of category uses on category learning. First, there is an extensive discussion contrasting classification with a predictive inference task that is formally equivalent to classification but leads to a very different pattern of learning. Then, research on the effects of problem solving, communication, and combining inference and classification is reviewed.     

Formation of category representations

Many formal models of categorization assume, implicitly or explicitly, that categorization results in the formation of direct associations from representations of the presented stimuli to representations of the experimentally provided category labels. In three categorization experiments employing a polymorphous classification structure (Dennis, Hampton, & Lea, 1973) and a partial reversal,optional shift procedure (Kendler, Kendler, & Wells, 1960), we provide evidence consistent with the hypothesis that learning a new classification problem results in the creation of category representations that mediate between representations of the stimulus and the label. This hypothesis can be instantiated through the AMBRY model (Kruschke, 1996).     

Visual noise reveals category representations

How are categories represented in human memory? Exemplar models assume that a category is represented by individual instances from that category that have been experienced. More generally, a category might be represented by multiple templates stored in memory. A new item is classified according to its similarity to these templates.Prototype models represent a category with a single summary abstraction (i.e., a single template), often the central tendency of the experienced items. A new item is classified according to its similarity to these category prototypes. Here, we show how a technique for correlating observers’ responses with external noise can be used not only to distinguish single- from multiple-template representations, but also to induce the form of these templates. The technique is applied to two tasks requiring categorization of simple visual patterns; the results demonstrate that observers used multiple traces to represent their categories, and thus highlight the procedure’s potential for use in more complex settings.     

The impact of category structure and training methodology on learning and generalizing within-category representations

When interacting with categories, representations focused on within-category relationships are often learned, but the conditions promoting within-category representations and their generalizability are unclear. We report the results of three experiments investigating the impact of category structure and training methodology on the learning and generalization of within-category representations (i.e., correlational structure). Participants were trained on either rule-based or information-integration structures using classification (Is the stimulus a member of Category A or Category B?), concept (e.g., Is the stimulus a member of Category A, Yes or No?), or inference (infer the missing component of the stimulus from a given category) and then tested on either an inference task (Experiments 1 and 2) or a classification task (Experiment 3). For the information-integration structure, within-category representations were consistently learned, could be generalized to novel stimuli, and could be generalized to support inference at test. For the rule-based structure, extended inference training resulted in generalization to novel stimuli (Experiment 2) and inference training resulted in generalization to classification (Experiment 3). These data help to clarify the conditions under which within-category representations can be learned. Moreover, these results make an important contribution in highlighting the impact of category structure and training methodology on the generalization of categorical knowledge.     

Category label and response location shifts in category learning

The category shift literature suggests that rule-based classification, an important form of explicit learning, is mediated by two separate learned associations: a stimulus-to-label association that associates stimuli and category labels, and a label-to-response association that associates category labels and responses. Three experiments investigate whether information–integration classification, an important form of implicit learning, is also mediated by two separate learned associations. Participants were trained on a rule-based or an information–integration categorization task and then the association between stimulus and category label, or between category label and response location was altered. For rule-based categories, and in line with previous research, breaking the association between stimulus and category label caused more interference than breaking the association between category label and response location. However, no differences in recovery rate emerged. For information–integration categories, breaking the association between stimulus and category label caused more interference and led to greater recovery than breaking the association between category label and response location. These results provide evidence that information–integration category learning is mediated by separate stimulus-to-label and label-to-response associations. Implications for the neurobiological basis of these two learned associations are discussed.     

Combining exemplar-based category representations and connectionist learning rules.

Adaptive network and exemplar-similarity models were compared on their ability to predict category learning and transfer data. An exemplar-based network (Kruschke, 1990a, 1990b, 1992) that combines key aspects of both modeling approaches was also tested. The exemplar-based network incorporates an exemplar-based category representation in which exemplars become associated to categories through the same error-driven, interactive learning rules that are assumed in standard adaptive networks. Experiment 1, which partially replicated and extended the probabilistic classification learning paradigm of Gluck and Bower (1988a), demonstrated the importance of an error-driven learning rule. Experiment 2, which extended the classification learning paradigm of Medin and Schaffer (1978) that discriminated between exemplar and prototype models, demonstrated the importance of an exemplar-based category representation. Only the exemplar-based network accounted for all the major qualitative phenomena; it also achieved good quantitative predictions of the learning and transfer data in both experiments.     

Category inference as a function of correlational structure, category discriminability, and number of available cues

Two experiments investigated category inference when categories were composed of correlated or uncorrelated dimensions and the categories overlapped minimally or moderately. When the categories minimally overlapped, the dimensions were strongly correlated with the category label. Following a classification learning phase, subsequent transfer required the selection of either a category label or a feature when one, two, or three features were missing. Experiments 1 and 2 differed primarily in the number of learning blocks prior to transfer. In each experiment, the inference of the category label or category feature was influenced by both dimensional and category correlations, as well as their interaction. The number of cues available at test impacted performance more when the dimensional correlations were zero and category overlap was high. However, a minimal number of cues were sufficient to produce high levels of inference when the dimensions were highly correlated; additional cues had a positive but reduced impact, even when overlap was high. Subjects were generally more accurate in inferring the category label than a category feature regardless of dimensional correlation, category overlap, or number of cues available at test. Whether the category label functioned as a special feature or not was critically dependent upon these embedded correlations, with feature inference driven more strongly by dimensional correlations.     

Psychological-state theories about significant others: implications for the content and structure of significant-other representations

Three studies tested a theory-based approach to significant-other representations. The central hypothesis was that perceivers are especially likely to possess lay theories to explain the responses of their significant others, and this is reflected in the content and structure of significant-other representations. Theories were defined in IF-THEN terms as beliefs about the psychological states (e.g., "IF Bill wants to make a good impression.") that explain others' responses (e.g., ". THEN he acts friendly"). All three studies yielded evidence indicating that the content of significant-other representations is especially likely to include such psychological-state theories (PSTs). Study 3 assessed the internal structure of PSTs-specifically, the strength of the linkages between psychological-state IFs and the THENs they are believed to elicit-and showed that such linkages are particularly strong for PSTs about significant others. Overall, the findings add to the growing literature on the role of explanatory or lay-theoretical forms of knowledge in how perceivers make sense of the social world.     

EEG decoding of semantic category reveals distributed representations for single concepts

Achieving a clearer picture of categorial distinctions in the brain is essential for our understanding of the conceptual lexicon, but much more fine-grained investigations are required in order for this evidence to contribute to lexical research. Here we present a collection of advanced data-mining techniques that allows the category of individual concepts to be decoded from single trials of EEG data. Neural activity was recorded while participants silently named images of mammals and tools, and category could be detected in single trials with an accuracy well above chance, both when considering data from single participants, and when group-training across participants. By aggregating across all trials, single concepts could be correctly assigned to their category with an accuracy of 98%. The pattern of classifications made by the algorithm confirmed that the neural patterns identified are due to conceptual category, and not any of a series of processing-related confounds. The time intervals, frequency bands and scalp locations that proved most informative for prediction permit physiological interpretation: the widespread activation shortly after appearance of the stimulus (from 100 ms) is consistent both with accounts of multi-pass processing, and distributed representations of categories. These methods provide an alternative to fMRI for fine-grained, large-scale investigations of the conceptual lexicon.     

Increased experience amplifies the activation of task-irrelevant category representations

Prior research has demonstrated the benefits (i.e., task-relevant attentional selection) and costs (i.e., task-irrelevant attentional capture) of prior knowledge on search for an individual target or multiple targets from a category. This study investigated whether the level of experience with particular categories predicts the degree of task-relevant and task-irrelevant activation of item and category representations. Adults with varying levels of dieting experience (measured via 3 subscales of Disinhibition, Restraint, Hunger; Stunkard & Messick, Journal of Psychosomatic Research, 29(1), 71–83, 1985) searched for targets defined as either a specific food item (e.g., carrots), or a category (i.e., any healthy or unhealthy food item). Apart from the target-present trials, in the target-absent “foil” trials, when searching for a specific item (e.g., carrots), irrelevant items from the target’s category (e.g., squash) were presented. The ERP (N2pc) results revealed that the activation of task-relevant representations (measured via Exemplar and Category N2pc amplitudes) did not differ based on the degree of experience. Critically, however, increased dieting experience, as revealed by lower Disinhibition scores, predicted activation of task-irrelevant representations (i.e., attentional capture of foils from the target item category). Our results suggest that increased experience with particular categories encourages the rapid activation of category representations even when category information is task irrelevant, and that the N2pc in foil trials could potentially serve as an indication of experience level in future studies on categorization.     

Category structure and created memories

Cued recall of categorized lists was used to examine effects of category structure on the creation of false memories. In three experiments, category members that had not been presented on studied categorized lists were nonetheless recalled by participants. Delaying the category cued recall test (Experiment 1) and priming category members that had been omitted from target lists (Experiment 3) increased the frequency of false recall. All three experiments showed that nonpresented category members that were higher in output dominance were more frequent intrusions. The typicality of category members, however, did not uniquely contribute to the predictability of false recall (or accurate recall) once the contribution of output dominance was taken into account, suggesting that item accessibility (related to output dominance) may be more instrumental than item distinctiveness (related to typicality) in causing certain types of false recall. The results show that created memories in category cued recall are strongly biased by prior category knowledge and can be predicted by the graded structure of categories, particularly in terms of the output dominance of category instances.     

Putting category learning in order: Category structure and temporal arrangement affect the benefit of interleaved over blocked study

Recent research in inductive category learning has demonstrated that interleaved study of category exemplars results in better performance than does studying each category in separate blocks. However, the questions of how the category structure influences this advantage and how simultaneous presentation interacts with the advantage are open issues. In this article, we present three experiments. The first experiment indicates that the advantage of interleaved over blocked study is modulated by the structure of the categories being studied. More specifically, interleaved study results in better generalization for categories with high within- and between-category similarity, whereas blocked presentation results in better generalization for categories with low within- and between-category similarity. In Experiment 2, we present evidence that when presented simultaneously, between-category comparisons (interleaved presentation) result in a performance advantage for high-similarity categories, but no differences were found for low-similarity categories. In Experiment 3, we directly compared simultaneous and successive presentation of low-similarity categories. We again found an overall benefit for blocked study with these categories. Overall, these results are consistent with the proposal that interleaving emphasizes differences between categories, whereas blocking emphasizes the discovery of commonalities among objects within the same category.     

The symbolic implications of vowels and of their orthographic representations in two natural languages

Ninety-two Hebrew-speaking subjects judged the magnitude, brightness, and hardness symbolism of orthographic characters designating five vowel phonemes in Hindi and in Japanese. For both languages and all three symbolic dimensions, the figural symbolism of the orthographic characters was found to replicate very closely the sound symbolism of their phonemic referents. The ranking of the five vowel characters in order of increasing magnitude and decreasing brightness and hardness was as follows:i, e, a, u, o. The results were interpreted to suggest that sound patterns and visual patterns tend to carry cross-culturally consistent connotations, and that the symbolic implications of sounds have been embodied in the pattern of orthographic characters in natural languages.This study was supported by a grant from the Human Development Center, The Hebrew University.     

Solving anagrams: Category priming and the differential availability of category solutions

An experiment was performed to test the hypothesis that the effect of category name priming on anagram solving varies with the strength of the relationship between the solution word and the priming category. Subjects solved anagrams of taxonomic category instances under primed or unprimed conditions. In the primed condition, the name of the taxonomic category from which the solution word was chosen was provided on each trial. Priming was shown to facilitate anagram solution and the extent of this facilitation was directly related to the instance dominance of the solution word in the priming category. The results were discussed in terms of current models of semantic memory.     

Age-related declines in the fidelity of newly acquired category representations

We present a theory suggesting that the ability to build category representations that reflect the nuances of category structures in the environment depends upon clustering mechanisms instantiated in an MTL-PFC-based circuit. Because function in this circuit declines with age, we predict that the ability to build category representations will be impaired in older adults. Consistent with this prediction, we find that older adults are impaired relative to younger adults at learning nuanced category structures that contain exceptions to the rule. Model-based analysis reveals that this deficit arises from older adults' failure to engage clustering mechanisms to separate exception and rule-following items in memory.     

Stimulus modality interacts with category structure in perceptual category learning

Two experiments were conducted that examined information integration and rule-based category learning, using stimuli that contained auditory and visual information. The results suggest that it is easier to perceptually integrate information within these sensory modalities than across modalities. Conversely, it is easier to perform a disjunctive rule-based task when information comes from different sensory modalities, rather than from the same modality. Quantitative model-based analyses suggested that the information integration deficit for across-modality stimulus dimensions was due to an increase in the use of hypothesis-testing strategies to solve the task and to an increase in random responding. The modeling also suggested that the across-modality advantage for disjunctive, rule-based category learning was due to a greater reliance on disjunctive hypothesis-testing strategies, as opposed to unidimensional hypothesis-testing strategies and random responding.     

Cross-cultural similarities in category structure

Categories, as mental structures, are more than simply sums of property frequencies. A number of recent studies have supported the view that the properties of categories may be organised along functional lines and possibly dependency structures more generally. The study presented here investigates whether earlier findings reflect something unique in the English language/North American culture or whether the functional structuring of categories is a more universal phenomenon. A population of English-speaking Americans was compared to a population of Cantonese-speaking Hong Kong Chinese. The findings clearly support the view that functional influences on category centrality are universal (or at least common to Cantonese-speaking Hong Kong Chinese and English-speaking Americans), albeit with specific cross-cultural/cross-linguistic group differences in the particular properties that are considered central to categories.