@inproceedings{maldonado-bouchardNeuralEndophenotypesSecure2026,

title = {From Neural Endophenotypes to Secure Human-Machine Interaction: Identifying Empathy-Related Vulnerabilities from Resting-State qEEG using Deep Learning},

author = {S. Maldonado-Bouchard and A. Saki and U. Faghihi and M. Brideau-Duquette and P. Renaud},

url = {https://www.scopus.com/pages/publications/105042126330?origin=resultslist},

doi = {10.1109/CAI68641.2026.11536416},

isbn = {979-833156039-3 (ISBN)},

year  = {2026},

date = {2026-01-01},

booktitle = {IEEE Conf. Artif. Intell., CAI},

pages = {1725–1732},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Telepresence and extended reality (XR) platforms increasingly integrate physiological sensing to infer socio-affective traits and personalize interaction. We test whether resting-state electroencephalography (EEG) alone can predict inter-individual differences in callous affect (SRP-CA; a proxy for reduced affective empathy) in a forensic cohort. Using 32-channel qEEG recorded at 500 Hz during one minute of eyes-open (EO) followed by one minute of eyes-closed (EC), we retain 143 quality-controlled sessions from 72 participants, each paired with a session-level SRP-CA score. We implement an EEG-only, leakage-aware evaluation protocol: splitting is performed at the session level and normalization parameters are fit on training data only. EEG is segmented into overlapping windows of 250-1,000 samples (50% overlap), and a lightweight Transformer encoder regressor is trained per window length; session-level predictions are obtained by averaging window-level outputs. On held-out test sessions, the best performance is achieved with 400-sample windows (MSE = 0.0595},

note = {Journal Abbreviation: IEEE Conf. Artif. Intell., CAI},

keywords = {Deep learning, Electroencephalography, Electrophysiology, Evaluation protocol, Human machine interaction, Inter-individual differences, Matchings, Physiological sensing, Resting state, Sample windows, Session level, Splittings, telepresence, Template matching, Visual communication},

pubstate = {published},

tppubtype = {inproceedings}

}