Literature DB >> 24364408

Dual systems of speech category learning across the lifespan.

W Todd Maddox1, Bharath Chandrasekaran2, Kirsten Smayda1, Han-Gyol Yi2.   

Abstract

Although categorization is fundamental to speech processing, little is known about the learning systems that mediate auditory categorization and even less is known about changes across the life span. Vision research supports dual-learning systems that are grounded in neuroscience and are partially dissociable. The reflective, rule-based system is prefrontally mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive, information-integration system is striatally mediated and operates by implicitly associating perception with actions that lead to reinforcement. We examine the extent to which dual-learning systems mediate auditory and speech learning in younger and older adults. We examined auditory category learning when a rule-based strategy (Experiment 1) or information-integration strategy (Experiment 2) was optimal, and found an age-related rule-based deficit, but intact information-integration learning. Experiment 3 examined natural auditory category learning, and found an age-related performance deficit. Computational modeling suggested that this was attributable to older adults' persistent reliance on suboptimal, unidimensional strategies when 2-dimensional strategies were optimal. Working memory capacity was also found to be associated with improved rule-based and natural auditory category learning, but not information-integration category learning. These results suggest that dual-learning systems are operative in speech category learning across the life span, and that performance deficits, when present, are attributable to deficiencies in frontally mediated, rule-based processes. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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Year:  2013        PMID: 24364408      PMCID: PMC3876037          DOI: 10.1037/a0034969

Source DB:  PubMed          Journal:  Psychol Aging        ISSN: 0882-7974


  60 in total

Review 1.  The frontal aging hypothesis evaluated.

Authors:  P M Greenwood
Journal:  J Int Neuropsychol Soc       Date:  2000-09       Impact factor: 2.892

2.  Generalizing a neuropsychological model of visual categorization to auditory categorization of vowels.

Authors:  W Todd Maddox; Michelle R Molis; Randy L Diehl
Journal:  Percept Psychophys       Date:  2002-05

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.  The effect of age on rule-based category learning.

Authors:  Caroline A Racine; Deanna M Barch; Todd S Braver; David C Noelle
Journal:  Neuropsychol Dev Cogn B Aging Neuropsychol Cogn       Date:  2006 Sep-Dec

Review 5.  Rule-based category learning in patients with Parkinson's disease.

Authors:  Amanda Price; J Vincent Filoteo; W Todd Maddox
Journal:  Neuropsychologia       Date:  2009-02-02       Impact factor: 3.139

6.  Learning a novel phonological contrast depends on interactions between individual differences and training paradigm design.

Authors:  Tyler K Perrachione; Jiyeon Lee; Louisa Y Y Ha; Patrick C M Wong
Journal:  J Acoust Soc Am       Date:  2011-07       Impact factor: 1.840

7.  Unattended exposure to components of speech sounds yields same benefits as explicit auditory training.

Authors:  Aaron R Seitz; Athanassios Protopapas; Yoshiaki Tsushima; Eleni L Vlahou; Simone Gori; Stephen Grossberg; Takeo Watanabe
Journal:  Cognition       Date:  2010-03-25

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

Authors:  J Vincent Filoteo; W Todd Maddox; Alan N Simmons; A David Ing; Xavier E Cagigas; Scott Matthews; Martin P Paulus
Journal:  Neuroreport       Date:  2005-02-08       Impact factor: 1.837

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.  Human midbrain sensitivity to cognitive feedback and uncertainty during classification learning.

Authors:  A R Aron; D Shohamy; J Clark; C Myers; M A Gluck; R A Poldrack
Journal:  J Neurophysiol       Date:  2004-03-10       Impact factor: 2.714

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  24 in total

1.  Individual differences in learning talker categories: the role of working memory.

Authors:  Susannah V Levi
Journal:  Phonetica       Date:  2015-02-19       Impact factor: 1.759

2.  Dopaminergic Genetic Polymorphisms Predict Rule-based Category Learning.

Authors:  Kaileigh A Byrne; Tyler Davis; Darrell A Worthy
Journal:  J Cogn Neurosci       Date:  2016-02-26       Impact factor: 3.225

3.  Perceptual Learning of Intonation Contour Categories in Adults and 9- to 11-Year-Old Children: Adults Are More Narrow-Minded.

Authors:  Vsevolod Kapatsinski; Paul Olejarczuk; Melissa A Redford
Journal:  Cogn Sci       Date:  2016-02-22

4.  The Role of Corticostriatal Systems in Speech Category Learning.

Authors:  Han-Gyol Yi; W Todd Maddox; Jeanette A Mumford; Bharath Chandrasekaran
Journal:  Cereb Cortex       Date:  2014-10-19       Impact factor: 5.357

5.  Performance Pressure Enhances Speech Learning.

Authors:  W Todd Maddox; Seth Koslov; Han-Gyol Yi; Bharath Chandrasekaran
Journal:  Appl Psycholinguist       Date:  2015-12-23

6.  Perceptual dimensions influence auditory category learning.

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

7.  Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.

Authors:  W Todd Maddox; Bharath Chandrasekaran; Kirsten Smayda; Han-Gyol Yi; Seth Koslov; Christopher G Beevers
Journal:  Cortex       Date:  2014-06-25       Impact factor: 4.027

8.  Aging and a genetic KIBRA polymorphism interactively affect feedback- and observation-based probabilistic classification learning.

Authors:  Nicolas W Schuck; Jessica R Petok; Martijn Meeter; Brit-Maren M Schjeide; Julia Schröder; Lars Bertram; Mark A Gluck; Shu-Chen Li
Journal:  Neurobiol Aging       Date:  2017-09-05       Impact factor: 4.673

9.  The C957T polymorphism in the dopamine receptor D₂ gene modulates domain-general category learning.

Authors:  Zilong Xie; W Todd Maddox; John E McGeary; Bharath Chandrasekaran
Journal:  J Neurophysiol       Date:  2015-03-11       Impact factor: 2.714

10.  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
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