"Network architecture underlying sparse neural activity characterized by structured higher-order interactions", Hideaki Shimazaki, Kyoto University
Neural Computation Unit (Doya Unit) would like to invite you to a seminar as follows.
Date: Tuesday, March 26
Venue: Meeting Room C016 - L1 Bldg
Speaker: Dr. Hideaki Shimazaki, Kyoto University
Title: Network architecture underlying sparse neural activity characterized by structured higher-order interactions
Abstract: Population activity of neurons is constrained by their biophysical properties and network architecture. Hence, statistical regularity of neural activity in turn tells us about these underlying mechanisms. In this talk, we report structured higher-order interactions in population activity of hippocampal CA3 neurons in cultured slices, and show that it is explained by excess simultaneous silence of neurons [Shimazaki et al. Sci Rep 2015]. We then investigated mechanisms underlying the excess silence. Using an analytical input-output relation of a leaky integrate-and-fire neuron model that operates under in-vivo conditions [Shomali et al. J Comp Neuro 2017], we constructed a model that links synaptic inputs, nonlinearity of spiking, network architecture, and statistics of population activity. With this model, we found that either common inhibition of neurons or excitatory inputs to pairs of neurons could induce the excess silence; but only the latter quantitatively explained the observed level of excess silence [Shomali et al. biRxiv 2018]. This work shows that the unified modeling framework is a useful tool to explore biophysical mechanisms of neural information processing from population activity.
We hope to see many of you.
Neural Computation Unit