Analysis of brain network temporal reconfiguration and frequency-domain features during dynamic orchestral segmentation transition based on electroencephalography

Abstract

Background/Objectives: The human brain’s natural capacity for music perception relies on dynamic interactions across distributed neural systems. To understand this process, we investigated how the brain responds to musical segment transitions and identified the acoustic and informational features that drive these neural dynamics. Method: In a passive listening task, we used Mozart’s Serenade in G major for Strings, K.525 (Allegro) as the auditory stimulus. Based on distinct acoustic and informational profiles, two contrasting 10-s segments were selected: one transitioned from a high-frequency, less-predictable segment to a low-frequency, more-predictable segment, and the other followed the reverse pattern. We calculated metrics of EEG rhythms and brain networks and subjected them to statistical analysis to investigate their dynamics during the transitions. Results: The study reveals that the brain employs an efficiency-trade-off strategy during musical transitions. In stable periods, it conserves energy through efficient frontal and occipital processing. During a transition, the fronto-occipital-central network dynamically reconfigures, accompanied by a transient drop in global efficiency and recruitment of the right prefrontal cortex. Such resource reallocation during unpredictable shifts delays neural processing. Furthermore, θ power increased with greater structural complexity and a higher spectral centroid (FDR-corrected p  < 0.05), indicating a specific mapping between these acoustic features and oscillatory activity. Our study provides evidence for the deep interactive relationship that persists between changes in musical acoustic structure and internal neural oscillations of the brain.