Literature DB >> 34543762

Neural dynamics underlying the acquisition of distinct auditory category structures.

Gangyi Feng1, Zhenzhong Gan2, Han Gyol Yi3, Shawn W Ell4, Casey L Roark5, Suiping Wang6, Patrick C M Wong7, Bharath Chandrasekaran8.   

Abstract

Despite the multidimensional and temporally fleeting nature of auditory signals we quickly learn to assign novel sounds to behaviorally relevant categories. The neural systems underlying the learning and representation of novel auditory categories are far from understood. Current models argue for a rigid specialization of hierarchically organized core regions that are fine-tuned to extracting and mapping relevant auditory dimensions to meaningful categories. Scaffolded within a dual-learning systems approach, we test a competing hypothesis: the spatial and temporal dynamics of emerging auditory-category representations are not driven by the underlying dimensions but are constrained by category structure and learning strategies. To test these competing models, we used functional Magnetic Resonance Imaging (fMRI) to assess representational dynamics during the feedback-based acquisition of novel non-speech auditory categories with identical dimensions but differing category structures: rule-based (RB) categories, hypothesized to involve an explicit sound-to-rule mapping network, and information integration (II) based categories, involving pre-decisional integration of dimensions via a procedural-based sound-to-reward mapping network. Adults were assigned to either the RB (n = 30, 19 females) or II (n = 30, 22 females) learning tasks. Despite similar behavioral learning accuracies, learning strategies derived from computational modeling and involvements of corticostriatal systems during feedback processing differed across tasks. Spatiotemporal multivariate representational similarity analysis revealed an emerging representation within an auditory sensory-motor pathway exclusively for the II learning task, prominently involving the superior temporal gyrus (STG), inferior frontal gyrus (IFG), and posterior precentral gyrus. In contrast, the RB learning task yielded distributed neural representations within regions involved in cognitive-control and attentional processes that emerged at different time points of learning. Our results unequivocally demonstrate that auditory learners' neural systems are highly flexible and show distinct spatial and temporal patterns that are not dimension-specific but reflect underlying category structures and learning strategies.
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Auditory category learning; Category structure; Computational modeling; MVPA; Neural representation; Spatiotemporal dynamics

Mesh:

Year:  2021        PMID: 34543762      PMCID: PMC8785192          DOI: 10.1016/j.neuroimage.2021.118565

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  86 in total

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Authors:  Randy L Diehl; Andrew J Lotto; Lori L Holt
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Authors:  Anitha Pasupathy; Earl K Miller
Journal:  Nature       Date:  2005-02-24       Impact factor: 49.962

4.  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

5.  Language learning in the adult brain: A neuroanatomical meta-analysis of lexical and grammatical learning.

Authors:  Kaitlyn M Tagarelli; Kyle F Shattuck; Peter E Turkeltaub; Michael T Ullman
Journal:  Neuroimage       Date:  2019-02-28       Impact factor: 6.556

6.  Learning of new sound categories shapes neural response patterns in human auditory cortex.

Authors:  Anke Ley; Jean Vroomen; Lars Hausfeld; Giancarlo Valente; Peter De Weerd; Elia Formisano
Journal:  J Neurosci       Date:  2012-09-19       Impact factor: 6.167

7.  Phonetic feature encoding in human superior temporal gyrus.

Authors:  Nima Mesgarani; Connie Cheung; Keith Johnson; Edward F Chang
Journal:  Science       Date:  2014-01-30       Impact factor: 47.728

8.  Inferior frontal regions underlie the perception of phonetic category invariance.

Authors:  Emily B Myers; Sheila E Blumstein; Edward Walsh; James Eliassen
Journal:  Psychol Sci       Date:  2009-06-08

9.  The modulation transfer function for speech intelligibility.

Authors:  Taffeta M Elliott; Frédéric E Theunissen
Journal:  PLoS Comput Biol       Date:  2009-03-06       Impact factor: 4.475

10.  Emerging native-similar neural representations underlie non-native speech category learning success.

Authors:  Gangyi Feng; Yu Li; Shen-Mou Hsu; Patrick C M Wong; Tai-Li Chou; Bharath Chandrasekaran
Journal:  Neurobiol Lang (Camb)       Date:  2021-06-09
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