Literature DB >> 33164348

Correspondence of categorical and feature-based representations of music in the human brain.

Tomoya Nakai1,2, Naoko Koide-Majima2,3, Shinji Nishimoto1,2,4.   

Abstract

INTRODUCTION: Humans tend to categorize auditory stimuli into discrete classes, such as animal species, language, musical instrument, and music genre. Of these, music genre is a frequently used dimension of human music preference and is determined based on the categorization of complex auditory stimuli. Neuroimaging studies have reported that the superior temporal gyrus (STG) is involved in response to general music-related features. However, there is considerable uncertainty over how discrete music categories are represented in the brain and which acoustic features are more suited for explaining such representations.
METHODS: We used a total of 540 music clips to examine comprehensive cortical representations and the functional organization of music genre categories. For this purpose, we applied a voxel-wise modeling approach to music-evoked brain activity measured using functional magnetic resonance imaging. In addition, we introduced a novel technique for feature-brain similarity analysis and assessed how discrete music categories are represented based on the cortical response pattern to acoustic features.
RESULTS: Our findings indicated distinct cortical organizations for different music genres in the bilateral STG, and they revealed representational relationships between different music genres. On comparing different acoustic feature models, we found that these representations of music genres could be explained largely by a biologically plausible spectro-temporal modulation-transfer function model.
CONCLUSION: Our findings have elucidated the quantitative representation of music genres in the human cortex, indicating the possibility of modeling this categorization of complex auditory stimuli based on brain activity.
© 2020 The Authors. Brain and Behavior published by Wiley Periodicals LLC.

Entities:  

Keywords:  MTF model; STG; fMRI; music genre

Year:  2020        PMID: 33164348      PMCID: PMC7821620          DOI: 10.1002/brb3.1936

Source DB:  PubMed          Journal:  Brain Behav            Impact factor:   2.708


  38 in total

1.  Spectrotemporal features of the auditory cortex: the activation in response to dynamic ripples.

Authors:  Dave R M Langers; Walter H Backes; Pim van Dijk
Journal:  Neuroimage       Date:  2003-09       Impact factor: 6.556

2.  Distinct Cortical Pathways for Music and Speech Revealed by Hypothesis-Free Voxel Decomposition.

Authors:  Nancy G Kanwisher; Josh H McDermott; Sam Norman-Haignere
Journal:  Neuron       Date:  2015-12-16       Impact factor: 17.173

3.  Multiresolution spectrotemporal analysis of complex sounds.

Authors:  Taishih Chi; Powen Ru; Shihab A Shamma
Journal:  J Acoust Soc Am       Date:  2005-08       Impact factor: 1.840

4.  Reconstructing visual experiences from brain activity evoked by natural movies.

Authors:  Shinji Nishimoto; An T Vu; Thomas Naselaris; Yuval Benjamini; Bin Yu; Jack L Gallant
Journal:  Curr Biol       Date:  2011-09-22       Impact factor: 10.834

5.  The Hierarchical Cortical Organization of Human Speech Processing.

Authors:  Wendy A de Heer; Alexander G Huth; Thomas L Griffiths; Jack L Gallant; Frédéric E Theunissen
Journal:  J Neurosci       Date:  2017-06-06       Impact factor: 6.167

6.  Capturing the musical brain with Lasso: Dynamic decoding of musical features from fMRI data.

Authors:  Petri Toiviainen; Vinoo Alluri; Elvira Brattico; Mikkel Wallentin; Peter Vuust
Journal:  Neuroimage       Date:  2013-11-19       Impact factor: 6.556

Review 7.  An anatomical and functional topography of human auditory cortical areas.

Authors:  Michelle Moerel; Federico De Martino; Elia Formisano
Journal:  Front Neurosci       Date:  2014-07-29       Impact factor: 4.677

8.  Correspondence of categorical and feature-based representations of music in the human brain.

Authors:  Tomoya Nakai; Naoko Koide-Majima; Shinji Nishimoto
Journal:  Brain Behav       Date:  2020-11-08       Impact factor: 2.708

9.  Music in our ears: the biological bases of musical timbre perception.

Authors:  Kailash Patil; Daniel Pressnitzer; Shihab Shamma; Mounya Elhilali
Journal:  PLoS Comput Biol       Date:  2012-11-01       Impact factor: 4.475

Review 10.  Methodological challenges and solutions in auditory functional magnetic resonance imaging.

Authors:  Jonathan E Peelle
Journal:  Front Neurosci       Date:  2014-08-21       Impact factor: 4.677

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  5 in total

1.  Voluntary control of semantic neural representations by imagery with conflicting visual stimulation.

Authors:  Ryohei Fukuma; Takufumi Yanagisawa; Shinji Nishimoto; Hidenori Sugano; Kentaro Tamura; Shota Yamamoto; Yasushi Iimura; Yuya Fujita; Satoru Oshino; Naoki Tani; Naoko Koide-Majima; Yukiyasu Kamitani; Haruhiko Kishima
Journal:  Commun Biol       Date:  2022-03-18

2.  High-Order Areas and Auditory Cortex Both Represent the High-Level Event Structure of Music.

Authors:  Jamal A Williams; Elizabeth H Margulis; Samuel A Nastase; Janice Chen; Uri Hasson; Kenneth A Norman; Christopher Baldassano
Journal:  J Cogn Neurosci       Date:  2022-03-05       Impact factor: 3.420

3.  Correspondence of categorical and feature-based representations of music in the human brain.

Authors:  Tomoya Nakai; Naoko Koide-Majima; Shinji Nishimoto
Journal:  Brain Behav       Date:  2020-11-08       Impact factor: 2.708

4.  Music genre neuroimaging dataset.

Authors:  Tomoya Nakai; Naoko Koide-Majima; Shinji Nishimoto
Journal:  Data Brief       Date:  2021-12-04

Review 5.  On the encoding of natural music in computational models and human brains.

Authors:  Seung-Goo Kim
Journal:  Front Neurosci       Date:  2022-09-20       Impact factor: 5.152

  5 in total

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