Dynamic Functional Connectivity in the Musical Brain

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Dipankar Niranjan, International Institute of Information Technology Hyderabad
  • ,
  • Petri Toiviainen, University of Jyväskylä
  • ,
  • Elvira Brattico
  • Vinoo Alluri, Cognitive Science Lab, International Institute of Information Technology Hyderabad

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.

Original languageEnglish
Title of host publicationBrain Informatics : 12th International Conference, BI 2019 Haikou, China, December 13–15, 2019 Proceedings
EditorsPeipeng Liang, Vinod Goel, Chunlei Shan
Number of pages10
Place of publicationCham
PublisherSpringer
Publication year2019
Pages82-91
ISBN (print)9783030370770
DOIs
Publication statusPublished - 2019
Event12th International Conference on Brain Informatics, BI 2019 - Haikou, China
Duration: 13 Dec 201915 Dec 2019

Conference

Conference12th International Conference on Brain Informatics, BI 2019
LandChina
ByHaikou
Periode13/12/201915/12/2019
SeriesLecture Notes in Computer Science
Volume11976 LNAI
ISSN0302-9743

    Research areas

  • Clustering, Dynamic Functional Connectivity, ICA, Musicians vs. non-musicians, State characterization

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