Autaptic Connections Shift Network Excitability and Bursting

TL;DR

This study investigates how autaptic connections influence neuronal network excitability and bursting, revealing that autapses can modulate burst frequency and are affected by neuron controllability and degree.

Contribution

It demonstrates the impact of autaptic connections on network bursting behavior and highlights the influence of neuronal controllability and degree in this process.

Findings

Increasing autapses raises burst frequency and spiking events.

High controllability neurons with autapses induce more bursts.

Targeting high-degree neurons reduces the autapse requirement for bursting.

Abstract

Network architecture forms a critical constraint on neuronal function. Here we examine the role of structural autapses, when a neuron synapses onto itself, in driving network-wide bursting behavior. Using a simple spiking model of neuronal activity, we study how autaptic connections affect activity patterns, and evaluate if neuronal degree or controllability are significant factors that affect changes in bursting from these autaptic connections. We observed that adding increasing numbers of autaptic connections to excitatory neurons increased the number of spiking events in the network and the number of network-wide bursts, particularly in the portion of the phase space in which excitatory synapses were stronger contributors to bursting behavior than inhibitory synapses. In comparison, autaptic connections to excitatory neurons with high average controllability led to higher burst frequencies than adding the same number of self-looping connections to neurons with high modal controllability. The number of autaptic connections required to induce bursting behavior could be lowered by selectively adding autapses to high degree excitatory neurons. These results suggest a role of autaptic connections in controlling network-wide bursts in diverse cortical and subcortical regions of mammalian brain. Moreover, they open up new avenues for the study of dynamic neurophysiological correlates of structural controllability.