Literature DB >> 21377688

Development of implicit and explicit category learning.

Cynthia L Huang-Pollock1, W Todd Maddox, Sarah L Karalunas.   

Abstract

We present two studies that examined developmental differences in the implicit and explicit acquisition of category knowledge. College-attending adults consistently outperformed school-age children on two separate information-integration paradigms due to children's more frequent use of an explicit rule-based strategy. Accuracy rates were also higher for adults on a unidimensional rule-based task due to children's more frequent use of the irrelevant dimension to guide their behavior. Results across these two studies suggest that the ability to learn categorization structures may be dependent on a child's ability to inhibit output from the explicit system.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21377688      PMCID: PMC3069659          DOI: 10.1016/j.jecp.2011.02.002

Source DB:  PubMed          Journal:  J Exp Child Psychol        ISSN: 0022-0965


  42 in total

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Authors:  O Monchi; M Petrides; V Petre; K Worsley; A Dagher
Journal:  J Neurosci       Date:  2001-10-01       Impact factor: 6.167

2.  The effects of concurrent task interference on category learning: evidence for multiple category learning systems.

Authors:  E M Waldron; F G Ashby
Journal:  Psychon Bull Rev       Date:  2001-03

3.  Category number impacts rule-based but not information-integration category learning: further evidence for dissociable category-learning systems.

Authors:  W Todd Maddox; J Vincent Filoteo; Kelli D Hejl; A David Ing
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2004-01       Impact factor: 3.051

4.  Visual categorization during childhood: an ERP study.

Authors:  M Batty; M J Taylor
Journal:  Psychophysiology       Date:  2002-07       Impact factor: 4.016

5.  Dissociating explicit and procedural-learning based systems of perceptual category learning.

Authors:  W Todd Maddox; F Gregory Ashby
Journal:  Behav Processes       Date:  2004-06-30       Impact factor: 1.777

6.  Early development of subcortical regions involved in non-cued attention switching.

Authors:  B J Casey; Matthew C Davidson; Yuko Hara; Kathleen M Thomas; Antigona Martinez; Adriana Galvan; Jeffrey M Halperin; Claudia E Rodríguez-Aranda; Nim Tottenham
Journal:  Dev Sci       Date:  2004-11

7.  Implicit category learning performance predicts rate of cognitive decline in nondemented patients with Parkinson's disease.

Authors:  J Vincent Filoteo; W Todd Maddox; David P Salmon; David D Song
Journal:  Neuropsychology       Date:  2007-03       Impact factor: 3.295

8.  Implicit and explicit category learning by macaques (Macaca mulatta) and humans (Homo sapiens).

Authors:  J David Smith; Michael J Beran; Matthew J Crossley; Joseph Boomer; F Gregory Ashby
Journal:  J Exp Psychol Anim Behav Process       Date:  2010-01

9.  "Artificial grammar learning" in pigeons: a preliminary analysis.

Authors:  Walter T Herbranson; Charles P Shimp
Journal:  Learn Behav       Date:  2003-02       Impact factor: 1.986

10.  A neuropsychological theory of multiple systems in category learning.

Authors:  F G Ashby; L A Alfonso-Reese; A U Turken; E M Waldron
Journal:  Psychol Rev       Date:  1998-07       Impact factor: 8.934

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  19 in total

1.  Compensatory processing during rule-based category learning in older adults.

Authors:  Krishna L Bharani; Ken A Paller; Paul J Reber; Sandra Weintraub; Jorge Yanar; Robert G Morrison
Journal:  Neuropsychol Dev Cogn B Aging Neuropsychol Cogn       Date:  2015-09-30

2.  Cognitive changes in conjunctive rule-based category learning: An ERP approach.

Authors:  Rahel Rabi; Marc F Joanisse; Tianshu Zhu; John Paul Minda
Journal:  Cogn Affect Behav Neurosci       Date:  2018-10       Impact factor: 3.282

3.  Perceptual dimensions influence auditory category learning.

Authors:  Casey L Roark; Lori L Holt
Journal:  Atten Percept Psychophys       Date:  2019-05       Impact factor: 2.199

4.  Prior experience with negative spectral correlations promotes information integration during auditory category learning.

Authors:  Mathias Scharinger; Molly J Henry; Jonas Obleser
Journal:  Mem Cognit       Date:  2013-07

5.  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

6.  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

7.  The time course of explicit and implicit categorization.

Authors:  J David Smith; Alexandria C Zakrzewski; Eric R Herberger; Joseph Boomer; Jessica L Roeder; F Gregory Ashby; Barbara A Church
Journal:  Atten Percept Psychophys       Date:  2015-10       Impact factor: 2.199

8.  Auditory information-integration category learning in young children and adults.

Authors:  Casey L Roark; Lori L Holt
Journal:  J Exp Child Psychol       Date:  2019-08-17

9.  The role of age and executive function in auditory category learning.

Authors:  Rachel Reetzke; W Todd Maddox; Bharath Chandrasekaran
Journal:  J Exp Child Psychol       Date:  2015-10-22

10.  Rule-based category learning in Down syndrome.

Authors:  B Allyson Phillips; Frances A Conners; Edward Merrill; Mark R Klinger
Journal:  Am J Intellect Dev Disabil       Date:  2014-05
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