Self Organized Criticality in a Mesoscopic Model of Excitatory-Inhibitory Neuronal Populations by Short-term and Long-term Synaptic Plasticity

2022/03/15 by Masud Ehsani, Jürgen Jost, Ehsani, Masud +1
Engineering · Neuroscience · Physics and Astronomy · #Advanced Memory and Neural Computing #Biological Physics (physics.bio-ph) #FOS: Physical sciences #Neural dynamics and brain function #stochastic dynamics and bifurcation

paper · pdf · doi:10.48550/arxiv.2203.07841

openalex publication_date 2022/03/15 · openalex created_date 2022/04/03 · openalex updated_date 2026/07/28

Abstract

In [1], we have shown that the dynamics of an interconnected population of excitatory and inhibitory spiking neurons wandering around a Bogdanov-Takens (BT)bifurcation point can generate the observed scale-free avalanches at the population level and the highly variable spike patterns of individual neurons. These characteristics match experimental findings for spontaneous intrinsic activity in the brain. In this paper, we address the mechanisms causing the system to get and remain near this BT point. We propose an effective stochastic neural field model which captures the dynamics of the mean-field model. We show how the network tunes itself through local long-term synaptic plasticity by STDP and short-term synaptic depression to be close to this bifurcation point. The mesoscopic model that we derive matches the directed percolation model at the absorbing state phase transition.

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