Literature DB >> 11508718

A possible role of the striatum in linear and nonlinear category learning: evidence from patients with Huntington's disease.

J V Filoteo1, W T Maddox, J D Davis.   

Abstract

Linear and nonlinear categorization rule learning was examined in patients with Huntington's disease (HD) and a group of controls using the perceptual categorization task. Participants learned to categorize simple line stimuli into 1 of 2 categories over 600 trials. In addition to traditional measures of accuracy, quantitative model-based analyses were applied to each participant's data to characterize better the nature of any observed deficits. In the linear rule condition, HD patients displayed an early-training deficit relative to controls, whereas later in training the HD patients were not statistically different from controls. In the nonlinear rule condition, HD patients displayed both an early- and late-training deficit. The quantitative model-based analyses revealed that the HD patients' deficits in the linear condition were due to an impairment in learning the experimenter-defined rule and not in applying a learned rule inconsistently. In the nonlinear condition, in contrast, the HD patients' deficits were due to an impairment in learning the experimenter-defined rule and in applying a learned rule inconsistently. Overall, these results suggest that HD can result in a deficit in learning both linear and nonlinear categorization rules.

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Year:  2001        PMID: 11508718     DOI: 10.1037//0735-7044.115.4.786

Source DB:  PubMed          Journal:  Behav Neurosci        ISSN: 0735-7044            Impact factor:   1.912


  20 in total

1.  Procedural learning in perceptual categorization.

Authors:  F Gregory Ashby; Shawn W Ell; Elliott M Waldron
Journal:  Mem Cognit       Date:  2003-10

Review 2.  Toward a unified theory of decision criterion learning in perceptual categorization.

Authors:  W Todd Maddox
Journal:  J Exp Anal Behav       Date:  2002-11       Impact factor: 2.468

3.  Observational versus feedback training in rule-based and information-integration category learning.

Authors:  F Gregory Ashby; W Todd Maddox; Corey J Bohil
Journal:  Mem Cognit       Date:  2002-07

4.  Computational Models Inform Clinical Science and Assessment: An Application to Category Learning in Striatal-Damaged Patients.

Authors:  W Todd Maddox; J Vincent Filoteo; Dagmar Zeithamova
Journal:  J Math Psychol       Date:  2010-02-01       Impact factor: 2.223

5.  Cognitive complexity effects in perceptual classification are dissociable.

Authors:  W Todd Maddox; J Scott Lauritzen; A David Ing
Journal:  Mem Cognit       Date:  2007-07

6.  Response processes in information-integration category learning.

Authors:  Brian J Spiering; F Gregory Ashby
Journal:  Neurobiol Learn Mem       Date:  2008-06-11       Impact factor: 2.877

7.  Posterror slowing predicts rule-based but not information-integration category learning.

Authors:  Helen Tam; W Todd Maddox; Cynthia L Huang-Pollock
Journal:  Psychon Bull Rev       Date:  2013-12

8.  Rule-based and information-integration perceptual category learning in children with attention-deficit/hyperactivity disorder.

Authors:  Cynthia L Huang-Pollock; W Todd Maddox; Helen Tam
Journal:  Neuropsychology       Date:  2014-03-17       Impact factor: 3.295

9.  Altered implicit category learning in anorexia nervosa.

Authors:  Megan E Shott; J Vincent Filoteo; Leah M Jappe; Tamara Pryor; W Todd Maddox; Michael D H Rollin; Jennifer O Hagman; Guido K W Frank
Journal:  Neuropsychology       Date:  2011-12-26       Impact factor: 3.295

Review 10.  Quantitative modeling of category learning deficits in various patient populations.

Authors:  J Vincent Filoteo; W Todd Maddox; F Gregory Ashby
Journal:  Neuropsychology       Date:  2017-11       Impact factor: 3.295

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