Literature DB >> 15671857

Cortical and subcortical brain regions involved in rule-based category learning.

J Vincent Filoteo1, W Todd Maddox, Alan N Simmons, A David Ing, Xavier E Cagigas, Scott Matthews, Martin P Paulus.   

Abstract

The brain regions contributing to rule-based category learning were examined using fMRI. Participants categorized single lines that varied in length and orientation into one of two categories. Category membership was based on the length of the line. Results indicated that left frontal and parietal regions were differentially activated in those participants who learned the task as compared to those who did not. Further, the head of the caudate displayed relative decreases in activation on incorrect trials relative to correct trials. The involvement of this latter structure is likely related to (1) processing an error signal, or (2) volitional switching between potential category rules. Results are consistent with theories suggesting that a frontal-striatal circuit is involved in rule-based category learning.

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Year:  2005        PMID: 15671857     DOI: 10.1097/00001756-200502080-00007

Source DB:  PubMed          Journal:  Neuroreport        ISSN: 0959-4965            Impact factor:   1.837


  36 in total

1.  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

2.  The dimensionality of perceptual category learning: a state-trace analysis.

Authors:  Ben R Newell; John C Dunn; Michael Kalish
Journal:  Mem Cognit       Date:  2010-07

3.  Cognitive complexity effects in perceptual classification are dissociable.

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

Review 4.  How do the basal ganglia contribute to categorization? Their roles in generalization, response selection, and learning via feedback.

Authors:  Carol A Seger
Journal:  Neurosci Biobehav Rev       Date:  2007-08-12       Impact factor: 8.989

Review 5.  A matched filter hypothesis for cognitive control.

Authors:  Evangelia G Chrysikou; Matthew J Weber; Sharon L Thompson-Schill
Journal:  Neuropsychologia       Date:  2013-11-05       Impact factor: 3.139

Review 6.  Neurocomputational mechanisms of reinforcement-guided learning in humans: a review.

Authors:  Michael X Cohen
Journal:  Cogn Affect Behav Neurosci       Date:  2008-06       Impact factor: 3.282

7.  When more is less: feedback effects in perceptual category learning.

Authors:  W Todd Maddox; Bradley C Love; Brian D Glass; J Vincent Filoteo
Journal:  Cognition       Date:  2008-05-01

8.  Dissociating the contributions of independent corticostriatal systems to visual categorization learning through the use of reinforcement learning modeling and Granger causality modeling.

Authors:  Carol A Seger; Erik J Peterson; Corinna M Cincotta; Dan Lopez-Paniagua; Charles W Anderson
Journal:  Neuroimage       Date:  2009-12-05       Impact factor: 6.556

9.  A Comparison of the neural correlates that underlie rule-based and information-integration category learning.

Authors:  Kathryn L Carpenter; Andy J Wills; Abdelmalek Benattayallah; Fraser Milton
Journal:  Hum Brain Mapp       Date:  2016-05-20       Impact factor: 5.038

10.  Category label and response location shifts in category learning.

Authors:  W Todd Maddox; Brian D Glass; Jeffrey B O'Brien; J Vincent Filoteo; F Gregory Ashby
Journal:  Psychol Res       Date:  2009-05-27
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