报告人学术简介
Gi-Yeul Bae is an Assistant Professor in the Department of Psychology at Arizona State University (https://sites.google.com/view/gybae). He received my ph.d. from Johns Hopkins University and did a post-doctoral training under the supervision of Steven Luck at UC Davis. In his research, he utilizes EEG, computational modeling, along with traditional psychophysical methods, to understand neural and cognitive mechanisms underlying visual information processing in the brain.  He has published over 40 papers in Journal of Neuroscience、NeuroImage and other journals.
报告内容
EEG recordings from the scalp provide a window into how the brain processes information over time. However, univariate EEG methods often miss the details of what information the brain is processing (i.e., the information content) and how that information changes over time. In this talk, he will introduce a machine-learning-based multivariate classification approach that allows us to track stimulus-specific information in the brain as it unfolds over time. He will then discuss how this method reveals the brain’s mechanisms for encoding, maintenance, and the use of the stimulus information under the contexts of perception and memory tasks.