Effect of the after-spike membrane potential on neuronal network dynamics

Abstract

In this work we explored the dynamics of three in silico neuronal cultures, each consisting of 3200 neurons and exhibiting different levels of aggregation. The inter-neuronal connectivity was generated in a biologically-realistic manner, based on the intersections between axons and dendrites, and the collective behaviour of the network was simulated using the Izhikevich model, specifically to reveal regimes of high neuronal synchrony. The dependence of network behaviour on the after-spike membrane potential value c of the Izhikevich model was then explored, revealing that a possible non-pathological regime lies within the range c ∈ [−130 ± 5,−55 ± 5] mV. Additionally, highly aggregated networks exhibited stable fluctuations in their synchrony, which may be a key feature for the proper functioning of biological neuronal computation. Furthermore, structural and functional connectivities were compared for each network, showing that greater aggregation leads to higher similarity between them