摘要

       The brain is a complex system with time-evolving dynamics to support varied cognitive behaviors. Predicting how the brain can fluctuate or be driven to specific states requires a fundamental understanding of the relationshin between neural connectivity and activity. Network control theory provides analytical tools to predictably manipulate a system behavior thus can be used to formalize the study of how the dynamics of a complex system can arise from its underlying structure of interconnected units. In this lecture, we will systematically cover the content in analyzing the brain networks through control theory.

 个人简介 

        顾实，电子科技大学计算机科学与工程学院教授。美国宾夕法尼亚大学(UniversityofPennsylvania)应用数学与计算科学专业博士，清华大学数理基础科学专业学士，2017年入选第十三批国家青年特聘专家，同年入选福布斯中国“30岁以下30人“榜单主要研究方向为计算神经科学与类脑人工智能，当前主要研究兴趣是基于人工智能的脑认知表达以及脑启发的智能。在Nature Communications,PNAS,Science Advances 等国际顶级期刊或会议上发表多篇脑科学与类脑人工智能相关论文。