Collective dynamics in spiking neural networks: A systematic review

Abstract

This study aims to identify typical collective phenomena that emerge in excitatory and inhibitory (E-I) spiking neural networks as reported in recent computational studies. The research methodology used is Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedures, comprising three primary stages: an initial search for literature in the SCOPUS database, a screening process based on specific inclusion and exclusion criteria, and a review of the selected literatures. Out of 491 documents from 2014 to 2024, six research papers are selected in the review stage. Four generic collective regimes have been identified, including synchrony, irregular behavior, stationary state, and oscillatory patterns. Our review findings suggest that the collective dynamics of E-I spiking neurons stem from the interplay of intrinsic neuronal characteristics, network topology, and external stimuli. Additionally, the prevalent use of Quadratic Integrate-and-Fire (QIF) neuron model in the literature highlights its significance as a robust candidate for exploring collective behaviors in large-scale neuronal networks. The findings outlined in this paper might be useful for individuals who lack prior familiarity with computational modelling of spiking neurons but have an interest in the field.