Computational Psychophysiology

Our Goal

Computational Psychophysiology (CP) is an interdisciplinary research which covers analysis and modeling of physiological responses and their correlations with psychological aspects of human behavior with theories and technologies of computer science, mathematics and physics. The research interests of CP include studies in multimodal indices, like MRI, PET, MEG, ERP, EEG, ECG, SP, respiration, behavior, etc., and other physiological effects of mentation under different mental states. The Technical Committee (TC) on CP aims to fuse the fields of computer science, cognitive neuroscience, neuropsychology, physiology, psychiatry, and biomedical engineering toward the investigation of psychological-physiological mechanisms, neuro-informatics, and innovative clinical technologies and therapies. For example, one emphasis will be placed on novel applications of psychophysiology for the research of biomarkers of mental disorders.

This technical committee will encourage the development of Computational Psychophysiology and promote multidisciplinary research collaborations, serve as a novel direction in computation field. Through CP study, our aims are to (1) exploit the mechanisms of emotion and cognition of mankind, (2) utilize multi-indices analysis, multimodal signals integration, multimodal modeling and inferential computing for evaluation and early intervention of mental disease. Computational psychophysiology contributes to the investigation of diagnosis and treatment of psychophysiological disease, structure and function of human brain, and the development of human-computer interaction technology.

Join Us

Join us to promote a new interdisciplinary field -- Computational Psychophysiology, which aims to encourage multidisciplinary collaboration and exploit the mechanisms related to emotion and cognition of human from multiple perspectives. With combining diversified knowledge (e.g., psychology, neuroscience and engineering) for understanding, revealing and modeling psychophysiological problems. We also focus on developing innovative methodologies for multimodal indices fusion and multimodal model construction to diversify current analysis methodologies. In terms of application, developing universal systems for early warning of the risk, aided diagnosis and intervening of mental disorders (e.g., depression) is also one of our targets.

Through this TC, we would like our members to join more academic exchange activities, conferences and symposiums to exchange ideas with scientists from different fields and touch the thoughts from different perspective. We also try to broaden the bridge of cross-disciplinary connection and will strongly support young researchers who are interested in.