Individualized brain-body signatures of positive emotions revealed by large-scale multimodal neurophysiological recording

Abstract

Using one of the most comprehensive multimodal biosensing datasets in affective research, densely sampled within individuals, we asked how emotions are instantiated in each person's brain and body. Four participants viewed 168 emotion-evoking videos during 128-channel EEG and 28 autonomic, ocular and facial recordings. Cross-validated elastic-net classifiers distinguished each of 15 positive and neutral emotions from baseline in every participant (mean accuracy 87-97%). We found that no emotion was predicted by a single marker and each reflected a multimodal ensemble of cortical and autonomic activity whose composition was largely person-specific. Yet physiology-derived groupings converged selectively with self-report; Interest-Awe-Amusement-Satisfaction and Entrancement-Aesthetic Appreciation recurred across individuals based on physiology. Across emotion groups, frontal and posterior delta, posterior alpha and electrodermal activity formed a shared backbone, plausibly reflecting affective and sensory engagement, whereas cardiovascular and facial signals varied between people. This framework yields individualized, objective neurophysiological indicators of emotion, potentially aiding personalized diagnosis.