Dynamic Hemispheric Lateralization of Naturalistic Emotional Processing After Unilateral Stroke: An
EEG
Study
Menglin Han, Yuting Tang, Yunyi Lv, Xiaoyun Chen, Xiaocao Liu, Zhuoming Chen, Jinyi Long ABSTRACT
Aim
Emotional impairment is common after stroke, but the neural electrophysiological mechanisms by which left‐ and right‐hemisphere lesions differentially alter emotional processing remain unclear. Conventional time‐averaged measures may overlook its dynamic features in the temporal organization of emotional processing. This study aimed to characterize hemisphere‐group‐associated differences in dynamic hemispheric lateralization during naturalistic emotional processing after unilateral stroke.
Methods
In this cross‐sectional study, 15 patients with left‐hemisphere stroke (L‐stroke), 15 patients with right‐hemisphere stroke (R‐stroke), and 15 healthy controls viewed validated positive, neutral, and negative film clips during 64‐channel electroencephalography recording. Self‐Assessment Manikin ratings were collected after each clip. We computed spectral power, emotion‐averaged lateralization index (LI), inter‐clip LI stability, and within‐clip LI dynamics (detectability, switching rate, and entropy). Mixed‐effects models accounted for repeated observations within participants and, where applicable, variability across film clips.
Results
Stroke patients showed reduced valence and arousal responses to positive clips, particularly in R‐stroke patients. Low‐frequency spectral power analysis showed preserved emotion modulation, whereas emotion‐averaged LI mainly reflected group‐dependent hemispheric bias. Within‐clip parietal‐theta LI dynamics revealed hemispheric differences: L‐stroke showed higher detectability and lower switching, while R‐stroke showed increased switching and entropy during positive clips. Switching showed a group‐dependent association with arousal in the primary model, with stronger coupling in R‐stroke.
Conclusion
Dynamic parietal‐theta lateralization revealed hemisphere‐group‐associated differences in the stability–flexibility balance of emotional brain states that were not captured by time‐averaged measures. These findings suggest that parietal‐theta LI dynamics may provide a preliminary candidate electrophysiological feature for characterizing post‐stroke emotional dysfunction.