Modelling the perception of music in brain network dynamics

Jakub Sawicki; Lenz Hartmann; Rolf Bader; Eckehard Schöll

doi:10.3389/fnetp.2022.910920

Modelling the perception of music in brain network dynamics

Front Netw Physiol. 2022 Aug 29:2:910920. doi: 10.3389/fnetp.2022.910920. eCollection 2022.

Authors

Jakub Sawicki^{1

2

3

4}, Lenz Hartmann⁵, Rolf Bader⁵, Eckehard Schöll^{1

4

6}

Affiliations

¹ Potsdam Institute for Climate Impact Research, Potsdam, Germany.
² Institut für Musikpädagogik, Universität der Künste Berlin, Berlin, Germany.
³ Fachhochschule Nordwestschweiz FHNW, Basel, Switzerland.
⁴ Institut für Theoretische Physik, Technische Universität Berlin, Berlin, Germany.
⁵ Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany.
⁶ Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität, Berlin, Germany.

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.

Keywords: coupled oscillators; electroencephalography (EEG); external driven; neuronal network dynamics; pattern formation: activity and anatomic; synchronization.

Grants and funding

This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project No. 429685422) and the Open Access Publication Fund of TU Berlin.