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  Modelling the perception of music in brain network dynamics

Sawicki, J., Hartmann, L., Bader, R., Schöll, E. (2022): Modelling the perception of music in brain network dynamics. - Frontiers in Network Physiology, 2, 910920.
https://doi.org/10.3389/fnetp.2022.910920

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 Creators:
Sawicki, Jakub1, Author              
Hartmann, Lenz2, Author
Bader, Rolf2, Author
Schöll, Eckehard1, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Abstract: We analyze the influence of music in a network of FitzHugh-Nagumo oscillators with empirical structural connectivity measured in healthy human subjects. We report an increase of coherence between the global dynamics in our network and the input signal induced by a specific music song. We show that the level of coherence depends crucially on the frequency band. We compare our results with experimental data, which also describe global neural synchronization between different brain regions in the gamma-band range in a time-dependent manner correlated with musical large-scale form, showing increased synchronization just before transitions between different parts in a musical piece (musical high-level events). The results also suggest a separation in musical form-related brain synchronization between high brain frequencies, associated with neocortical activity, and low frequencies in the range of dance movements, associated with interactivity between cortical and subcortical regions.

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Language(s): eng - English
 Dates: 2022-08-292022-08-29
 Publication Status: Finally published
 Pages: 17
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3389/fnetp.2022.910920
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Quantitative Methods
OATYPE: Gold Open Access
 Degree: -

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Title: Frontiers in Network Physiology
Source Genre: Journal, other, oa
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Pages: - Volume / Issue: 2 Sequence Number: 910920 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/frontiers-network-physiology
Publisher: Frontiers