From chaos to clock in reverberating neural net. Case study

TL;DR

This case study investigates how a simple deterministic neural network exhibits complex, chaotic transient dynamics before settling into periodic behavior, shedding light on neural computation mechanisms.

Contribution

It demonstrates that complex neural dynamics can emerge from a deterministic network without noise, highlighting intrinsic computational processes.

Findings

Long chaotic transients observed in a simple neural network

Transient dynamics last significantly longer than initial stimulation

Network eventually stabilizes into a periodic state

Abstract

What is the reason for complex dynamical patterns registered from real biological neuronal networks? Noise and dynamical reconfiguring of a network (functional/dynamic connectome) were proposed as possible answers. In this case study, we report a complex dynamical pattern observed in a simple deterministic network of 25 neurons with fixed connectome. After a short initial stimulation, the network is engaged into a complex dynamics, which lasts for a long time. Eventually, with no external intervention, the dynamics comes to a periodic one with a short period. The long transient is positively checked for being chaotic. We conclude that the complex dynamics observed is the output of neural computation performed in the process of neuronal firings and spikes propagation.