EEG microstates dynamics of happiness and sadness during music listening

Gupta, Ashish; Srivastava, Chandan Kumar; Bhushan, Braj; Behera, Laxmidhar · 2025 · Crossref

DOI: 10.3389/fnhum.2025.1472689

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates the neural mechanisms underlying the cognitive and emotional effects of music listening, specifically focusing on how happy and sad classical music modulate EEG microstates. While music is known to enhance attention and aid emotion regulation, the specific electroencephalogram (EEG) microstates associated with these effects remain unclear. The research aims to identify distinct microstate dynamics in the alpha band (8–13 Hz) linked to happiness and sadness, providing a framework for understanding music-induced changes in brain dynamics. The researchers utilized two secondary datasets comprising 15 male participants each, selected to control for gender differences and musical training. One group listened to happy Indian classical music (Raga Darbari), while the other listened to sad music (Raga Jogiya) following a sad autobiographical recall task. EEG data were recorded from 32 scalp positions, preprocessed to remove artifacts, and filtered for the alpha band. Microstate analysis was performed using spatial k-means clustering to identify four standard classes (A, B, C, and D) based on topographical orientation. Parameters including global explained variance (GEV), global field potential (GFP), coverage, occurrence, and duration were calculated and compared across baseline, music listening, and post-music silence conditions using repeated measures ANOVA and correlation analyses. Results indicated distinct microstate patterns for each emotional valence. During happy music listening, Class D microstates, associated with attention and executive functioning, showed significantly increased GEV and GFP compared to Classes A, B, and C. An inverse relationship was observed between Class C (linked to mind-wandering and the Default Mode Network) and Class D, suggesting that happy music upregulates attention while suppressing mind-wandering. Conversely, sad music elicited increased presence of Classes B, C, and D. Specifically, GEV and GFP analyses revealed upregulation of both Class C and Class D compared to the resting state. This concurrent activation suggests that sad music facilitates emotion regulation and self-regulatory goals by engaging both self-referential processing and attentional networks. Additionally, mean microstate duration was significantly longer for both happy and sad music conditions compared to baseline, indicating that music listening enhances the temporal stability of active brain states. These findings advance the understanding of how music modulates brain dynamics at a millisecond scale. The study demonstrates that happy music enhances attention through the dominance of Class D microstates and suppression of Class C, whereas sad music supports emotion regulation through the simultaneous engagement of self-referential (Class C) and attentional (Class D) networks. This provides a neurophysiological basis for the therapeutic use of music in mental healthcare and cognitive therapy, highlighting its potential as a non-intrusive tool for modulating attention and emotional processing.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• music audio mood