Literature DB >> 20547171

Rule-based and information-integration category learning in normal aging.

W Todd Maddox1, Jennifer Pacheco, Maia Reeves, Bo Zhu, David M Schnyer.   

Abstract

The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated processes, whereas information-integration is thought to involve implicit, striatally mediated processes. As a group, older adults showed rule-based and information-integration deficits. A series of models were applied that provided insights onto the type of strategy used to solve the task. Interestingly, when the analyses focused only on participants who used the task appropriate strategy in the final block of trials, the age-related rule-based deficit disappeared whereas the information-integration deficit remained. For this group of individuals, the final block information-integration deficit was due to less consistent application of the task appropriate strategy by older adults, and over the course of learning these older adults shifted from an explicit hypothesis-testing strategy to the task appropriate strategy later in learning. In addition, the use of the task appropriate strategy was associated with less interference and better inhibitory control for rule-based and information-information learning, whereas use of the task appropriate strategy was associated with greater working memory and better new verbal learning only for the rule-based task. These results suggest that normal aging impacts both forms of category learning and that there are some important similarities and differences in the explanatory locus of these deficits. The data also support a two-component model of information-integration category learning that includes a striatal component that mediated procedural-based learning, and a prefrontal cortical component that mediates the transition from hypothesis-testing to procedural-based strategies. Implications for independent vs. interactive category learning systems are discussed. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 20547171      PMCID: PMC2914220          DOI: 10.1016/j.neuropsychologia.2010.06.008

Source DB:  PubMed          Journal:  Neuropsychologia        ISSN: 0028-3932            Impact factor:   3.139


  66 in total

1.  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

2.  Information-integration category learning in patients with striatal dysfunction.

Authors:  J Vincent Filoteo; W Todd Maddox; David P Salmon; David D Song
Journal:  Neuropsychology       Date:  2005-03       Impact factor: 3.295

3.  The ability to decide advantageously declines prematurely in some normal older persons.

Authors:  N L Denburg; D Tranel; A Bechara
Journal:  Neuropsychologia       Date:  2005       Impact factor: 3.139

4.  Dual-task interference in perceptual category learning.

Authors:  Dagmar Zeithamova; W Todd Maddox
Journal:  Mem Cognit       Date:  2006-03

5.  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

6.  Effects of stimulus integrality on visual attention in older and younger adults: a quantitative model-based analysis.

Authors:  W T Maddox; J V Filoteo; J R Huntington
Journal:  Psychol Aging       Date:  1998-09

7.  The roles of the caudate nucleus in human classification learning.

Authors:  Carol A Seger; Corinna M Cincotta
Journal:  J Neurosci       Date:  2005-03-16       Impact factor: 6.167

8.  The impact of irrelevant dimensional variation on rule-based category learning in patients with Parkinson's disease.

Authors:  J Vincent Filoteo; W Todd Maddox; A David Ing; Vanessa Zizak; David D Song
Journal:  J Int Neuropsychol Soc       Date:  2005-09       Impact factor: 2.892

9.  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

10.  A role for the perceptual representation memory system in category learning.

Authors:  Michael B Casale; F Gregory Ashby
Journal:  Percept Psychophys       Date:  2008-08
View more
  29 in total

1.  Analogical transfer in perceptual categorization.

Authors:  Michael B Casale; Jessica L Roeder; F Gregory Ashby
Journal:  Mem Cognit       Date:  2012-04

2.  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

Review 3.  Human category learning 2.0.

Authors:  F Gregory Ashby; W Todd Maddox
Journal:  Ann N Y Acad Sci       Date:  2010-12-23       Impact factor: 5.691

4.  Adult age differences in learning on a sequentially cued prediction task.

Authors:  Kendra L Seaman; Darlene V Howard; James H Howard
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2013-06-26       Impact factor: 4.077

5.  Development of implicit and explicit category learning.

Authors:  Cynthia L Huang-Pollock; W Todd Maddox; Sarah L Karalunas
Journal:  J Exp Child Psychol       Date:  2011-03-05

Review 6.  Visual category learning: Navigating the intersection of rules and similarity.

Authors:  Gregory I Hughes; Ayanna K Thomas
Journal:  Psychon Bull Rev       Date:  2021-01-19

7.  Photobiomodulation improves the frontal cognitive function of older adults.

Authors:  Agnes S Chan; Tsz Lok Lee; Michael K Yeung; Michael R Hamblin
Journal:  Int J Geriatr Psychiatry       Date:  2018-12-10       Impact factor: 3.485

8.  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

9.  Age-related declines in the fidelity of newly acquired category representations.

Authors:  Tyler Davis; Bradley C Love; W Todd Maddox
Journal:  Learn Mem       Date:  2012-07-18       Impact factor: 2.460

10.  Category learning strategies in younger and older adults: Rule abstraction and memorization.

Authors:  Christopher N Wahlheim; Mark A McDaniel; Jeri L Little
Journal:  Psychol Aging       Date:  2016-03-07
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.