Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	Professor Dongzhuo Zhou, Shanghai Jiao Tong University
Inviter:	Professor Haijun Yu
Title:	Dynamics and information coding in balanced neuronal networks
Language:	Chinese
Time & Venue:	2023.08.04 10:00-11:00 Z301
Abstract:	The idea of a balanced state is that the excitatory and inhibitory components of inputs nearly cancel each other, and the neural firing activity is driven by strong fluctuations that intermittently interrupt this cancellation and give rise to the irregularity of neural spikes. Consistent with the hypothesized scenario, balanced synaptic inputs have been observed in experiment, and it is believed that the balanced state is closely related to the efficient coding in real neuronal networks. Previous theoretical and computational works proposed a mechanism to understand the emergence of the balanced state in homogeneous networks and have shown that small perturbations of the balanced state in a network with binary neurons grow exponentially, indicating the chaotic nature of the balanced activity. However, there are several issues that remain to be clarified. First, whether the chaotic dynamics is the underlying mechanism for the irregularity of neural activity in a balanced network. Second, whether a balanced state can exist in heterogeneous networks and how it differs from the balanced state in homogeneous networks. Third, how the balanced state is related to information coding in networks as well as network structure. We will address these issues through modeling, analysis and simulations in this talk.