Modelling the perception of music in brain network dynamics

Area of Science:

• Computational neuroscience
• Neuroscience of music
• Complex systems

Background:

• The brain's complex network dynamics are influenced by external stimuli.
• Understanding neural responses to music provides insights into brain function.

Purpose of the Study:

• To investigate how music influences the coherence of a neural network model.
• To compare model dynamics with experimental data on brain synchronization during music listening.

Main Methods:

• Utilized a FitzHugh-Nagumo oscillator network model.
• Incorporated empirical structural connectivity data from healthy human subjects.
• Analyzed coherence between network dynamics and music input signals across different frequency bands.

Main Results:

• Observed increased coherence between network dynamics and music input.
• Found that coherence levels are critically dependent on frequency bands.
• Demonstrated synchronization in the gamma-band range, correlating with musical structure and high-level musical events.
• Identified a frequency-dependent separation in synchronization, linking high frequencies to neocortical activity and low frequencies to cortical-subcortical interactions.

Conclusions:

• Music can entrain neural network dynamics, increasing coherence.
• Neural synchronization patterns reflect musical structure, with distinct frequency bands associated with different brain processes.
• The findings support a multi-frequency model of music perception and its neural underpinnings.