The combined effect of chemical and electrical synapses in small Hindmarsch-Rose neural networks on synchronisation and on the rate of information

TL;DR

This study investigates how chemical and electrical synapses influence synchronization and information rate in small Hindmarsh-Rose neural networks, revealing how synaptic types and strengths affect network dynamics and information capacity.

Contribution

It provides new insights into the combined effects of chemical and electrical synapses on neural synchronization and introduces a semi-analytical method to estimate the information rate upper bound.

Findings

Excitatory chemical synapses reduce electrical synapse strength needed for synchronization.

Inhibitory chemical synapses increase electrical synapse strength required for synchronization.

The upper bound of information rate scales linearly with the number of neurons in highly connected networks.

Abstract

In this work we studied the combined action of chemical and electrical synapses in small networks of Hindmarsh-Rose (HR) neurons on the synchronous behaviour and on the rate of information produced (per time unit) by the networks. We show that if the chemical synapse is excitatory, the larger the chemical synapse strength used the smaller the electrical synapse strength needed to achieve complete synchronisation, and for moderate synaptic strengths one should expect to find desynchronous behaviour. Otherwise, if the chemical synapse is inhibitory, the larger the chemical synapse strength used the larger the electrical synapse strength needed to achieve complete synchronisation, and for moderate synaptic strengths one should expect to find synchronous behaviours. Finally, we show how to calculate semi-analytically an upper bound for the rate of information produced per time unit (Kolmogorov-Sinai entropy) in larger networks. As an application, we show that this upper bound is linearly proportional to the number of neurons in a network whose neurons are highly connected.