# Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity

## TL;DR

This paper develops a mesoscopic population model for spiking neural networks incorporating short-term synaptic plasticity, enabling accurate and tractable analysis of neural dynamics with finite synapses and correlations.

## Contribution

It extends existing static-synapse mesoscopic models to include dynamic STP, deriving stochastic mean-field equations under Poisson spike assumptions.

## Key findings

- Model accurately reproduces stochastic synaptic input in simulations.
- Captures stochastic Up and Down state transitions.
- Accounts for correlations between neurotransmitter release and resource availability.

## Abstract

Coarse-graining microscopic models of biological neural networks to obtain mesoscopic models of neural activities is an essential step towards multi-scale models of the brain. Here, we extend a recent theory for mesoscopic population dynamics with static synapses to the case of dynamic synapses exhibiting short-term plasticity (STP). Under the assumption that spike arrivals at synapses have Poisson statistics, we derive analytically stochastic mean-field dynamics for the effective synaptic coupling between finite-size populations undergoing Tsodyks-Markram STP. The novel mean-field equations account for both finite number of synapses and correlations between the neurotransmitter release probability and the fraction of available synaptic resources. Comparisons with Monte Carlo simulations of the microscopic model show that in both feedforward and recurrent networks the mesoscopic mean-field model accurately reproduces stochastic realizations of the total synaptic input into a postsynaptic neuron and accounts for stochastic switches between Up and Down states as well as for population spikes. The extended mesoscopic population theory of spiking neural networks with STP may be useful for a systematic reduction of detailed biophysical models of cortical microcircuits to efficient and mathematically tractable mean-field models.