A view of Neural Networks as dynamical systems

TL;DR

This paper explores neural networks through the lens of dynamical systems theory, reviewing recent advances in understanding their collective behavior, spike train statistics, structural interactions, and synaptic plasticity effects.

Contribution

It provides a comprehensive review of recent results connecting neural network dynamics with structural and plasticity aspects from a dynamical systems perspective.

Findings

Characterization of collective neural dynamics

Analysis of spike train statistics

Insights into synaptic plasticity effects

Abstract

We consider neural networks from the point of view of dynamical systems theory. In this spirit we review recent results dealing with the following questions, adressed in the context of specific models. 1. Characterizing the collective dynamics; 2. Statistical analysis of spikes trains; 3. Interplay between dynamics and network structure; 4. Effects of synaptic plasticity.