A4 Article in conference proceedings
Dynamic Functional Connectivity in the Musical Brain (2019)


Niranjan, Dipankar; Toiviainen, Petri; Brattico, Elvira; Alluri, Vinoo (2019). Dynamic Functional Connectivity in the Musical Brain. In Liang, Peipeng; Goel, Vinod; Shan, Chunlei (Eds.) BI 2019 : International Conference on Brain Informatics, Lecture Notes in Computer Science. Cham: Springer 11976, 82-91. DOI: 10.1007/978-3-030-37078-7_9


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Publication details

All authors or editors: Niranjan, Dipankar; Toiviainen, Petri; Brattico, Elvira; Alluri, Vinoo

Parent publication: BI 2019 : International Conference on Brain Informatics

Parent publication editors: Liang, Peipeng; Goel, Vinod; Shan, Chunlei

Conference:

  • International Conference on Brain Informatics

Place and date of conference: Haikou, China, 13.-15.12.2019

ISBN: 978-3-030-37077-0

eISBN: 978-3-030-37078-7

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Publication year: 2019

Volume: 11976

Pages range: 82-91

Number of pages in the book: 274

Publisher: Springer

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-030-37078-7_9

Open Access: Publication channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/67321


Abstract

Musical training causes structural and functional changes in the brain due to its sensory-motor demands. This leads to differences in how musicians perceive and process music as compared to non-musicians, thereby providing insights into brain adaptations and plasticity. Correlational studies and network analysis investigations have indicated the presence of large-scale brain networks involved in the processing of music and have highlighted differences between musicians and non-musicians. However, studies on functional connectivity in the brain during music listening tasks have thus far focused solely on static network analysis. Dynamic Functional Connectivity (DFC) studies have lately been found useful in unearthing meaningful, time-varying functional connectivity information in both resting-state and task-based experimental settings. In this study, we examine DFC in the fMRI obtained from two groups of participants, 18 musicians and 18 non-musicians, while they listened to a musical stimulus in a naturalistic setting. We utilize spatial Group Independent Component Analysis (ICA), sliding time window correlations, and a deterministic agglomerative clustering of windowed correlation matrices to identify quasi-stable Functional Connectivity (FC) states in the two groups. To compute cluster centroids that represent FC states, we devise and present a method that primarily utilizes windowed correlation matrices occurring repeatedly over time and across participants, while excluding matrices corresponding to spontaneous fluctuations. Preliminary analysis indicate states with greater visuo-sensorimotor integration in musicians, larger presence of DMN states in non-musicians, and variability in states found in musicians due to differences in training and prior experiences.


Keywords: musicians; music; brain research

Free keywords: dynamic functional connectivity; clustering; ICA; state characterization; musicians vs. non-musicians


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Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1


Last updated on 2020-18-08 at 13:32