Title: How neurons integrate synaptic inputs: computational modeling, analysis and experiments

Speaker: 周栋焯 (Douglas Zhou) Institute of Natural Sciences & School of Mathematics, Shanghai Jiao Tong University

Time: 2018年04月19日14:00-15:00

Location: Center for Mathematical Sciences, Room 813

Abstract:

    A neuron receives thousands of synaptic inputs from other neurons and integrates them to process information. Many experimental results demonstrate this integration could be highly nonlinear, yet few theoretical analyses have been performed to obtain a precise quantitative characterization. Based on asymptotic analysis of an idealized cable model, we derive a bilinear spatiotemporal integration rule for a pair of time-dependent synaptic inputs. Note that the above rule is obtained from idealized models. However, we have confirmed this rule both in simulations of a realistic pyramidal neuron model and in electrophysiological experiments of rat hippocampal CA1 neurons. Our results demonstrate that the integration of multiple synaptic inputs can be decomposed into the sum of all possible pairwise integration with each paired integration obeying a bilinear rule.

    周栋焯博士于2002和2007年在北京大学获学士和博士学位，从2007年至2009年，他在美国纽约大学库朗研究所从事博士后研究，周栋焯博士于2010年加入上海交通大学自然科学研究院、数学科学学院，从2010年1月至2016年1月任特别研究员，从2016年2月至今任教授。周栋焯博士目前的主要研究兴趣是理论和计算神经科学领域的科学问题，包括神经元网络动力学的信息编码原理的研究，针对神经生理实验现象的数学建模与动力学模拟以及神经元网络机制的研究，发展有助实验的数据处理方法等，其工作发表在如PNAS，PLoS Comput. Biol，Phys. Rev. Lett.以及J. Comput. Neurosci.等国际期刊上。