台大心理系

One of the goals of studying systems neuroscience is to understand how the brain works under day-to-day, natural conditions. Pursuing such a goal inevitably involves the use of two kinds of high-dimensional data: one of them is dynamic spatiotemporal patterns of perceptual and cognitive experience. The other is spatiotemporal patterns of brain activity that represent those internal experiences. We aim to understand the brain by building predictive models that explain the relationship between these two kinds of high-dimensional patterns. Such models reveal quantitative representations inside the brain, such as space-time visual representations in early visual areas, semantic representations in occipitotemporal areas, and their dynamic warps during cognitive tasks. We have also built brain decoders that can quantify and visualize perceptual experiences from brain activity in humans. As a whole, modeling of the brain provides a general and quantitative foundation for understanding human perception and cognition.