报告题目：Complex Neural Connectivity and Activity: Perspective from Cost-Efficiency Trade-off

报告人：周昌松 教授（香港浸会大学）

主持人：兰岳恒 教授

报告时间：2018年7月4日（星期三）下午 3:00-5:00

报告地点：主楼804

报告摘要：

We are interested in understanding neural systems as functional, complex dynamical networks. The brain is highly energy consuming, therefore is under strong evolution pressure to achieve cost-efficiency in both cortical connectivity and activity. In our recent works, we emphasized that the formation of the complex network architecture and dynamical activity of neural systems is subject to multiple structural and functional constraints. In the macaque brain connectome, we showed that network connectivity indeed displays a cost-efficiency trade-off, and up to 67% of the existing links can be recovered by the trade-off model. The model also reveals new organization feature of long distance-connectors (LDCs) in the system which are crucial for both functional segregation  and integration. In terms of neural activity, we demonstrated using biologically plausible neural circuit model that the co-emergence of salient features of cortical activity, including irregular firing, oscillations and neuronal avalanches as observed in experiments achieves minimal  energy cost as well as maximal energy efficiency on information capacity.  Indeed, cost-efficient neural network structure and cost-efficient neural dynamics have collaborative interaction to enable neural systems to achieve “less is more” in both structure and dynamics. The perspective of cost-efficiency trade-off could provide a framework to better understand various salient features in neural connectivity and activity, and likely also suggest a novel angle to study the inherent vulnerability in brain networks which could be closely related to various neurodegenerative diseases and brain disorders。

报告人简介：

周昌松，物理学博士，香港浸会大学物理系教授，浸会大学非线性研究中心及北京-香港-新加坡非线性复杂系统联合中心主任。1992年获南开大学物理学士，1997年获南开大学物理博士，1997-2007 年在新加坡、香港、德国等地从事访问研究，是洪堡基金获得者。2007年加入香港浸会大学物理系，2011年获浸会大学“杰出青年研究者董事长奖”。周昌松博士致力于复杂系统动力学基础研究及其应用，特别是网络的复杂联结结构与体系的动态行为的关系和相互作用。近几年一直与国际国内系统和认知神经科学家紧密合作，把这些理论进展应用到大脑的复杂联结结构和活动以及认知功能及障碍的分析和建模等方面研究中。