Abstract:

Affective brain-computer interface (aBCI) aims to recognize and/or regulate human emotions. In particular, according to whether to regulate emotions, aBCI can be divided into two categories. The first category is emotion recognition BCI, which can recognize emotions based on the brain signals, other physiological signals and non-physiological signals collected by external devices. The second category is emotion recognition BCI, which can not only recognize emotions but also regulate emotions by stimulating specific brain areas. This talk will introduce our recent work on emotion recognition BCI and its application to objective assessment of mood disorder. Specifically, we will introduce basic principles of psychology and neuroscience for aBCI, oil paintings as emotional stimuli, a seven emotions dataset with continuous labels, a multimodal aBCI framework of combining EEG signals and eye movement signals, a plug-and-play domain adaptation for cross-subject EEG-based emotion recognition, a large brain model for learning generic representations with tremendous EEG data, the similarities and differences among Chinese, German, and French individuals in emotion recognition with EEG and eye movements from aBCI perspective, and preliminary results on objective assessment of depression with oil paintings as stimuli from eye movement data.

Speaker Bio:

Bao-Liang Lu received a B.S. degree in instrument and control engineering from Qingdao University of Science and Technology, Qingdao, China, in 1982; an M.S. degree in computer science and technology from Northwestern Polytechnical University, Xian, China, in 1989; and a Dr. Eng. Degree in electrical engineering from Kyoto University, Kyoto, Japan, in 1994. He was with Qingdao University of Science and Technology from 1982 to 1986. From 1994 to 1999, he was a Frontier Researcher with the Bio-Mimetic Control Research Center, Institute of Physical and Chemical Research (RIKEN), Nagoya, Japan, and he was a Research Scientist with the RIKEN Brain Science Institute, Wako, Japan, from 1999 to 2002. Since 2002, he has been a Full Professor with the Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China. He received the IEEE Transactions on Autonomous Mental Development Outstanding Paper Award from the IEEE Computational Intelligence Society in 2018, the Best of IEEE Transactions on Affective Computing Paper Collection in 2021, and the 2022 Asia Pacific Neural Network Society (APNNS) Outstanding Achievement Award. His current research interests include brain-like computing, deep learning, and affective brain-computer interfaces. He is currently an associate editor of IEEE Transactions on Affective Computing, IEEE Transactions on  Cognitive and Development Systems and the Journal of Neural Engineering and the IEEE Fellow.