Spike Pattern Structure Influences Efficacy Variability under STDP and Synaptic Homeostasis

TL;DR

This paper investigates how different statistical features of spike patterns affect synaptic efficacy variability under STDP and synaptic homeostasis, revealing their impact on neural network structure and function.

Contribution

It systematically analyzes the influence of spike pattern features on efficacy variability, integrating STDP and synaptic homeostasis, and highlights their role in neural encoding and development.

Findings

Spike pattern features significantly affect efficacy variability.

Efficacy variability influences neural encoding and network development.

The study offers new insights into plasticity and spike pattern interactions.

Abstract

In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons, synapses and networks, spike trains typically exhibit externally uncontrollable variability such as spatial heterogeneity and temporal stochasticity, resulting in variability of synapses, which we call efficacy variability. Spike patterns with the same population rate but inducing different efficacy variability may result in neuronal networks with sharply different structures and functions. However, how the variability of spike trains influences the efficacy variability remains unclear. Here, we systematically study this influence when spike patterns possess four aspects of statistical features, i.e. synchronous firing, auto-temporal structure, heterogeneity of rates and heterogeneity of cross-correlations, under spike-timing dependent plasticity (STDP) after dynamically bounding the mean strength of plastic synapses into or out of a neuron (synaptic homeostasis). We then show the functional importance of efficacy variability on the encoding and maintenance of connection patterns and on the early development of primary visual systems driven by retinal waves. We anticipate our work brings a fresh perspective to the understanding of the interaction between synaptic plasticity and dynamical spike patterns in functional processes of neural systems.