Alternative strategies of categorization

Smith, Edward E.; Patalano, Andrea L.; Jonides, John

doi:10.1016/s0010-0277(97)00043-7

Cited by 269 publications

(259 citation statements)

References 55 publications

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“…In addition, relational processing which is taken to underlie pattern-based learning (Gomez and Gerken, 2000) also appears to be a function of the hippocampal system as indicated by a wide range of fMRI studies (Cohen et al, 1999;Schacter and Wagner, 1999). Furthermore, it has been suggested that relational processes based on perceptual similarity can operate in parallel to abstract rule learning (Smith et al, 1998;Strange et al, 2001). Thus, these findings are compatible with our interpretation of the present hippocampal response decreasing with time.…”

Section: Discussionmentioning

confidence: 99%

“…One important view on learning, gaining considerable interest over the past years, proposes two distinct processes (Knowlton and Squire, 1996;Smith et al, 1998). According to this view, individuals either learn item-specific information on the basis of superficial similarity to some exemplar or learn by abstracting a representation of the underlying rules.…”

Section: Introductionmentioning

confidence: 99%

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Interactions of the hippocampal system and the prefrontal cortex in learning language-like rules

2003

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One of the most influential views on the hippocampal function suggests that this brain region is critically involved in relational memory processing, that is, binding converging inputs to mediate the representation of relationships among the constituents of episodes. It has been proposed that this binding is automatic and obligatory during learning and remembering In addition, neuroimaging studies have highlighted the importance of the prefrontal cortex, in learning, memory, and language processing. However, the posited importance of hippocampalprefrontal interaction remains to be empirically tested. In the present study we used functional magnetic resonance imaging to examine in detail this interaction by assessing learning-related changes in hemodynamic activity during artificial language acquisition. It has been shown previously that artificial grammar systems might be learned by evaluating pattern-based relations in word sequences and generalizing beyond specific word order, that is, rule abstraction. During scanning, participants learned an artificial language whose miniature grammar meets the universal principles of a natural language. Increased proficiency level of the artificial language is associated with decreased left hippocampal activity. In contrast, we observed an increased recruitment of the left inferior frontal gyrus (Broca's area), a region that contributes to syntax processing in natural language. The present results, therefore, indicate a learning-related change in brain circuitry underlying relational processes of language learning, with a transition from a similarity-based learning system in the medial temporal lobes to a language-related processing system in the left prefrontal cortex.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Interactions of the hippocampal system and the prefrontal cortex in learning language-like rules

2003

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“…Cognitive psychologists have extensively studied the ways in which people group objects into categories, investigating issues such as whether people represent categories in terms of exemplars or prototypes (J. D. Smith & Minda, 1998;Nosofsky & Zaki, 2002;Minda & Smith, 2002;Storms et al, 2000;Nosofsky, 1988;Nosofsky & Johansen, 2000;Zaki et al, 2003;E. E. Smith et al, 1998;Heit & Barsalou, 1996).…”

Section: Methods For Studying Categoriesmentioning

confidence: 99%

Uncovering mental representations with Markov chain Monte Carlo

Sanborn

Griffiths

Shiffrin

2010

Cognitive Psychology

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A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Richard M. Shiffrin Indiana University, Bloomington Abstract A key challenge for cognitive psychology is the investigation of mental representations, such as object categories, subjective probabilities, choice utilities, and memory traces. In many cases, these representations can be expressed as a non-negative function defined over a set of objects. We present a behavioral method for estimating these functions. Our approach uses people as components of a Markov chain Monte Carlo (MCMC) algorithm, a sophisticated sampling method originally developed in statistical physics. Experiments 1 and 2 verified the MCMC method by training participants on various category structures and then recovering those structures. Experiment 3 demonstrated that the MCMC method can be used estimate the structures of the real-world animal shape categories of giraffes, horses, dogs, and cats. Experiment 4 combined the MCMC method with multidimensional scaling to demonstrate how different accounts of the structure of categories, such as prototype and exemplar models, can be tested, producing samples from the categories of apples, oranges, and grapes.

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“…Theories of categorization can be broadly divided into those based on assessing the similarity between an item that must be classified and known members of a category (exemplar and prototype theories) and those based on applying rules to determine category membership (Hahn & Chater, 1998;Medin & Schaffer, 1978; E. E. Smith, Patalano, & Jonides, 1998; E. E. Smith & Sloman, 1994; J. D. Smith & Minda, 1998). The traditional hallmark of rule use is that application of a fixed set of criteria results in an all-or-none category boundary rather than in graded membership according to degree of similarity to a prototype or other category members.…”

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confidence: 99%

Multidimensional Rule, Unidimensional Rule, and Similarity Strategies in Categorization: Event-Related Brain Potential Correlates.

Folstein¹,

Petten²

2004

Journal of Experimental Psychology: Learning, Memory, and Cogni

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Forty participants assigned artificial creatures to categories after explicit rule instruction or feedback alone. Stimuli were typical and atypical exemplars of 2 categories with independent prototypes, conflicting exemplars sharing features of both categories, and "Others" with only 1 or 2 features of the well-defined categories. Ten feedback-only participants spontaneously adopted a unidimensional rule; 10 used a multidimensional similarity strategy. Event-related potentials (ERPs) recorded during the transfer phase showed a commonality between multidimensional rule and similarity strategies in late frontal brain activity that differentiated both from unidimensional rule use. Multidimensional rule users alone showed an earlier prefrontal ERP effect that may reflect inhibition of responses based on similarity. The authors also discuss the role of declarative memory for features and exemplars.

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Alternative strategies of categorization

Cited by 269 publications

References 55 publications

Interactions of the hippocampal system and the prefrontal cortex in learning language-like rules

Interactions of the hippocampal system and the prefrontal cortex in learning language-like rules

Uncovering mental representations with Markov chain Monte Carlo

Multidimensional Rule, Unidimensional Rule, and Similarity Strategies in Categorization: Event-Related Brain Potential Correlates.

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