讲题主题: Computational cognitive neuroscience: From neurons to behavior 时间: 99.7.28(星期三)下午2:20~3:20 地点: 国立台湾大学心理系北馆N106(北A教室) 演讲学者: Dr. Tsung-Ren Huang (黄从仁) Department of Psychology Department of Cognitive and Neural Systems Boston University 演讲摘要： How does the brain control behavior? What do neural circuits compute? The field of cognitive neuroscience is thriving due to advances of various methodologies such as neuroanatomy, neurophysiology, neuroimaging, and cognitive psychology. Given the rapid aggregation of empirical observations in these areas, an emerging challenge is to provide a unified theory that relates different levels of analysis, explaining how neural systems in the brain give rise to intelligent human behavior. Modern computational cognitive neuroscience endeavors to delineate neural representations and mechanisms from a theoretical perspective. It has offered new insights beyond brain/behavior correlations. One example is the application of machine learning/pattern recognition, which underlies recent development of brain-computer interfaces for patients and healthy individuals, and becomes a popular tool for probing neural representations in brain imaging studies. Another example is the class of neural models that construct system-level architectures from the first principles such as local computation and competitive normalization. These computational models not only quantitatively simulate cognitive functions, but also clarify seemingly conflicting or unrelated phenomena in a coherent framework with plausible neural mechanisms. In this presentation, differences among computational approaches in (cognitive) neuroscience will be contrasted. The past, present, and future of computational cognitive neuroscience will be discussed in light of several research lines in the field. --

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