D3 Article in professional conference proceedings
Predicting Individual Differences from Brain Responses to Music using Functional Network Centrality (2022)

Jain, A., Brattico, E., Toiviainen, P., & Alluri, V. (2022). Predicting Individual Differences from Brain Responses to Music using Functional Network Centrality. In CCN 2022 : 2022 Conference on Cognitive Computational Neuroscience (Article 1233). Conference Management Services, Inc.. https://doi.org/10.32470/CCN.2022.1233-0

JYU authors or editors

Publication details

All authors or editors: Jain, Arihant; Brattico, Elvira; Toiviainen, Petri; Alluri, Vinoo

Parent publication: CCN 2022 : 2022 Conference on Cognitive Computational Neuroscience

Conference:

Place and date of conference: San Francisco, USA, 25.-28.8.2022

Publication year: 2022

Article number: 1233

Publisher: Conference Management Services, Inc.

Publication country: United States

Publication language: English

DOI: https://doi.org/10.32470/CCN.2022.1233-0

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/82710

Abstract

Individual differences are known to modulate brain responses to music. Recent neuroscience research suggests that each individual has unique and fundamentally stable functional brain connections irrespective of the task they perform. 77 participants’ functional Magnetic Resonance Imaging (fMRI) responses were measured while continuously listening to music. Using a graph-theory-based approach, we modeled whole-brain functional connectivity. We then calculate voxel-wise eigenvector centrality and subsequently use it to classify gender and musical expertise using binary Support Vector Machine (SVM). We achieved a cross-validated classification accuracy of 97% and 96% for gender and musical expertise, respectively. We also identify regions that contribute most to this classification. Thus, this study demonstrates that individual differences can be decoded from brain responses to music using a graph-based method with near-perfect precision.

Keywords: music psychology; cognitive neuroscience; listening; differences; individuality; functional magnetic resonance imaging

Free keywords: individual differences; fMRI; naturalistic paradigm; functional connectivity; centrality; classification

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2022