Individualized brain-body signatures of positive emotions revealed by large-scale multimodal neurophysiological recording
- 1University of California San Francisco
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.
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BibTeX
@misc{bijanzadeh2026individualized,
title = {{Individualized brain-body signatures of positive emotions revealed by large-scale multimodal neurophysiological recording}},
author = {M. Bijanzadeh and B. Nandi and V. Wang and B. Kalisetti and R. Campusano and J. Townsend and R. Anguera-Singla and I. Hartley and M. Osheroff and D. Ziegler and T. Zanto and A. Gazzaley and R. Abbasi-Asl},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.23.761434},
url = {https://www.biorxiv.org/content/10.64898/2026.10.23.761434v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Individualized brain-body signatures of positive emotions revealed by large-scale multimodal neurophysiological recording
AU - M. Bijanzadeh
AU - B. Nandi
AU - V. Wang
AU - B. Kalisetti
AU - R. Campusano
AU - J. Townsend
AU - R. Anguera-Singla
AU - I. Hartley
AU - M. Osheroff
AU - D. Ziegler
AU - T. Zanto
AU - A. Gazzaley
AU - R. Abbasi-Asl
PY - 2026
DA - 2026/10/23
PB - bioRxiv
DO - 10.64898/2026.10.23.761434
UR - https://www.biorxiv.org/content/10.64898/2026.10.23.761434v1
AB - 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.
ER -