Learning rule-described and non-rule-described categories: A comparison of children and adults.

Minda, John Paul; Desroches, Amy S.; Church, Barbara A.

doi:10.1037/a0013355

Cited by 75 publications

(177 citation statements)

References 48 publications

(156 reference statements)

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“…Lieberman et al, 2004). According to the COVIS model, for the hypothesis-testing system to operate, an intact/developed prefrontal cortex is required (Minda et al, 2008). TBI typically results in localized and diffuse prefrontal cortex damage and it was confirmed that all TBI patients in this study had suffered contusional injury to the prefrontal cortex and exhibited problems in executive functioning.…”

Section: Discussionsupporting

confidence: 65%

“…Note that other AGL researchers have employed patient populations, but never before has a TBI sample been used in the context of AGL or the implicit-explicit distinction (Knowlton & Squire, 1994Smith & McDowall, 2005. Also, note that results from Minda et al (2008) support the conclusion that a deficit in the prefrontal cortex impairs the function of the hypothesis-testing system. In Minda et al's study, children were impaired, relative to adults, in a categorization task which required the explicit development of complex rules, a finding which was explained in terms of the fact that the prefrontal cortex develops later than other areas.…”

Section: Introductionmentioning

confidence: 97%

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Separate influences in learning: Evidence from artificial grammar learning with traumatic brain injury patients

Pothos

Wood

2009

Brain Research

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractArtificial grammar learning (AGL) is one of the most extensively employed paradigms for the study of learning. Grammaticality is one of the most common ways to index performance in AGL. However, there is still extensive debate on whether there is a distinct psychological process which can lead to grammaticality knowledge.An application of the COVIS model of categorization in AGL suggests that grammaticality might arise from a hypothesis-testing system (when grammaticality is appropriately balanced with other knowledge influences), so that prefrontal cortex damage should be associated with impaired grammaticality and intact chunk strength performance. This prediction was confirmed in a study of traumatic brain injury (TBI) patients and matched controls. The TBI patient cohort had diffuse prefrontal cortex damage as evidenced by the history of their injury, CT scans, and severe executive functioning problems. Our results allow a novel interpretation of grammaticality and AGL in general. Section: 7. Cognitive and Behavioral Neuroscience

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Section: Discussionsupporting

confidence: 65%

Section: Introductionmentioning

confidence: 97%

Separate influences in learning: Evidence from artificial grammar learning with traumatic brain injury patients

Pothos

Wood

2009

Brain Research

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“…For example, COVIS predicts that learning of an overall similarity category structure is less affected by time pressure or concurrent load than learning of a singledimension category structure (Minda et al, 2008;Waldron & Ashby, 2001;Zeithamova & Maddox, 2006). 6…”

Section: Differentiation Theorymentioning

confidence: 99%

Combination or Differentiation? Two theories of processing order in classification

Wills

Inkster

Milton

2015

Cognitive Psychology

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Does cognition begin with an undifferentiated stimulus whole, which can be divided into distinct attributes if time and cognitive resources allow (Differentiation Theory)? Or does it begin with the attributes, which are combined if time and cognitive resources allow (Combination Theory)?Across psychology, use of the terms analytic and non-analytic imply that Differentiation Theory is correct -if cognition begins with the attributes, then synthesis, rather than analysis, is the more appropriate chemical analogy. We re-examined four classic studies of the effects of time pressure, incidental training, and concurrent load on classification and category learning (Kemler Nelson, 1984;Smith & Kemler Nelson, 1984;Smith & Shapiro, 1989;Ward, 1983). These studies are typically interpreted as supporting Differentiation Theory over Combination Theory, while more recent work in classification (Milton, Longmore & Wills, 2008, et seq.) supports the opposite conclusion. Across seven experiments, replication and re-analysis of the four classic studies revealed that they do not support Differentiation Theory over Combination Theory -two experiments support Combination Theory over Differentiation Theory, and the remainder are compatible with both accounts. We conclude that Combination Theory provides a parsimonious account of both classic and more recent work in this area. The presented data do not require Differentiation Theory, nor a Combination-Differentiation hybrid account.

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“…Kemler, 1983;Minda, Desroches & Church, 2008). COVIS (see Ashby et al, 1998) and a variant of GCM (Smith, 1989) has been applied to a subset of these data, SUSTAIN to a different subset .…”

Section: Defining Domains Through Ivsmentioning

confidence: 99%

On the adequacy of current empirical evaluations of formal models of categorization.

Wills

Pothos

2012

Psychological Bulletin

124

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This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent repository link: AbstractCategorization is one of the fundamental building blocks of cognition, and the study of categorization is notable for the extent to which formal modeling has been a central and influential component of research. However, the field has seen a proliferation of divergent, non-complementary models with little consensus on the relative adequacy of these accounts.Progress on assessing relative adequacy of formal categorization models against these criteria has, to date, been limited because (a) formal model comparisons are narrow in the number of models and phenomena considered, and (b) models do not often clearly define their explanatory scope. Progress is further hampered by the practice of fitting models with arbitrarily variable parameters to each data set independently. Reviewing examples of good practice in the literature, we conclude that model comparisons are most fruitful when relative adequacy is assessed by comparing well-defined models on the basis of the number and proportion of irreversible, ordinal, penetrable successes (principles of minimal flexibility, breadth, good-enough precision, maximal simplicity, and psychological focus).Keywords: categorization; cluster; exemplar; model selection; modeling; prototype. EMPIRICAL EVALUATION OF CATEGORIZATION MODELS 2The study of categorization is a fascinating endeavor. The process of constructing and using categories underpins our capacity to encode and apply information in the world in an efficient and competent manner but also, ultimately, our ability to think in terms of abstract kind of categorization models should we aim to develop? The lack of consensus regarding such key issues has resulted in categorization research being carried out in increasingly independent strands and this has been inhibiting overall progress in the field. Nosofsky, Gluck, Palmeri, McKinley and Glauthier (1994) wrote, "Recent years have seen an avalanche of newly proposed models of category learning and representation. As such models grow increasingly more sophisticated, there is a need to develop increasingly more rigorous testing grounds so that one may choose among them" (p. 352). Almost 20 years later, progress towards this goal remains limited.In the current article, we first provide a definition of the term formal model, consider the principal advantages of formal modeling over other forms of theorizing, briefly summarize some of the leading formal models of categorization, and assess progress to date on the empirical evaluation and comparison of these models. We then set out the approaches EMPIRICAL EVALUATION OF CATEGORIZATION MODELS 3 we believe are most likely to lead to progress in the future. We organize our conclusions in terms of a set of criteria for assessing the relative adequacy of models, and a list of dependent and independent variables that any adequate formal model of categorization should be expected to...

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Learning rule-described and non-rule-described categories: A comparison of children and adults.

Cited by 75 publications

References 48 publications

Separate influences in learning: Evidence from artificial grammar learning with traumatic brain injury patients

Separate influences in learning: Evidence from artificial grammar learning with traumatic brain injury patients

Combination or Differentiation? Two theories of processing order in classification

On the adequacy of current empirical evaluations of formal models of categorization.

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