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通过短期和长期突触可塑性在兴奋性-抑制性神经元群体的介观模型中的自组织临界性

Self-organized criticality in a mesoscopic model of excitatory-inhibitory neuronal populations by short-term and long-term synaptic plasticity.

作者信息

Ehsani Masud, Jost Jürgen

机构信息

Max Planck Institute for Mathematics in Sciences, Leipzig, Germany.

Santa Fe Institute, Santa Fe, NM, United States.

出版信息

Front Comput Neurosci. 2022 Oct 10;16:910735. doi: 10.3389/fncom.2022.910735. eCollection 2022.

DOI:10.3389/fncom.2022.910735
PMID:36299476
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9588946/
Abstract

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.

摘要

相互连接的兴奋性和抑制性脉冲发放神经元群体围绕一个博格达诺夫 - 塔肯斯（BT）分岔点漂移的动力学过程，能够在群体层面产生观测到的无标度雪崩以及单个神经元高度可变的脉冲模式。这些特征与大脑中自发内在活动的实验结果相匹配。在本文中，我们探讨了使系统到达并保持在这个BT点附近的机制。我们提出了一个有效的随机神经场模型，该模型捕捉了平均场模型的动力学。我们展示了网络如何通过基于STDP的局部长期突触可塑性和短期突触抑制来自我调节，以接近这个分岔点。我们推导的介观模型在吸收态相变时与定向渗流模型相匹配。

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