Evidence map›Paper›PMID 33164348›Full record

ArticleBrain and behavior2021

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

Tomoya Nakai, Naoko Koide-Majima, Shinji Nishimoto

Abstract read
In one paragraph

Article in Brain and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Tomoya NakaiCenter for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan.ORCID 0000-0001-5225-0894
Naoko Koide-MajimaGraduate School of Frontier Biosciences, Osaka University, Suita, Japan.ORCID 0000-0002-3805-5758
Shinji NishimotoCenter for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan.ORCID 0000-0001-8015-340X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHumans 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.

methodsWe 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.

resultsOur 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.

conclusionOur 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.

Indexed as

MusicAcoustic StimulationAuditory PerceptionBrainBrain MappingHumansMagnetic Resonance ImagingfMRIMTF modelmusic genreSTG

Identifiers

PMID33164348
PMCPMC7821620

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.