Analysis of Microstate Organization During Emotional Events

TL;DR

This study uses EEG microstate analysis to investigate brain activity during spontaneous emotional events, revealing distinct microstate patterns and transitions that differentiate emotional from neutral states, highlighting the neural mechanisms of emotional experience.

Contribution

It introduces a microstate-based approach to characterize neural dynamics during emotional experiences, identifying specific microstates and transition patterns associated with emotional and neutral conditions.

Findings

Four distinct microstates identified for emotional and neutral conditions.

Higher occurrence and transition to MS1 during emotional states.

Source localization links microstates to sensory and socio-emotional brain regions.

Abstract

Understanding the dynamics of emotional experience is an old problem. However, a clear understanding of the mechanism of emotional experience is still far away. In the presented work, we tried to address this problem using a well-established method called microstate analysis using multichannel electroencephalography (EEG). We recorded the brain activity of spontaneous emotional experiences while participants were watching multimedia emotional stimuli. The time duration where the participants spontaneously felt an emotion, we termed it an emotional event. Microstate segmentation is performed for all emotional events to calculate the set of microstates (MS). Followed by a comparison of calculated statistical parameters and transition probabilities for the emotional and non-emotional conditions. We found a set of MS (four MS) for emotional and non-emotional conditions that differ from each other. We observed that MS1 has a higher value of occurrence, duration and coverage for emotional conditions. In addition, the transition to MS1 for the emotional condition was higher. On the other hand, for non-emotion (or neutral) condition, transition to MS3 was higher. A set of MS related to neutral condition was source localized to brain regions involved in higher-level sensory feature processing. On the other hand, for emotional conditions, MS1 \& MS2 are localized to sensory feature processing regions, and MS3 \& MS4 are additionally localized to regions related to socio-emotional processing. Our results hint toward the constructionist mechanism, which has an asymmetric contribution from bottom-up and top-down processing during an emotional experience.