Dynamical Analysis Of The Role Of Synaptic Dynamics In Coupled Neural Populations

Authors: Ana Mayora-Cebollero, Roberto Barrio, Jorge A. Jover-Galtier, Carmen Mayora-Cebollero, Lucía Pérez, Sergio Serrano

Presentation type: Poster at SNUFA 2025 online workshop (5-6 Nov 2025)

Abstract

The dynamical analysis of mean-field models of neural populations allows us to study the different dynamical regimes that are present when certain properties, such as synaptic dynamics, are taken into account or not. The well-known mean-field model of Montbrió-Pazó-Roxin [1] represents the dynamics of heterogeneous all-to-all coupled QIF spiking neural networks without synaptic dynamics (i.e., with instantaneous synapses), whereas the mean-field model of Dumont-Gutkin [2] represents such system but considering synaptic dynamics. Both models are linked through a parameter related to synaptic coupling [3, 4]. In this presentation, we provide an in-depth explanation of the dynamical changes that arise as this parameter is varied, using techniques such as numerical continuation and spike-counting sweeping.

[1] Montbrió, E., Pazó, D., & Roxin, A. (2015). Macroscopic description for networks of spiking neurons. Physical Review X, 5(2), 021028. [2] Dumont, G., & Gutkin, B. (2019). Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits. PLoS computational biology, 15(5), e1007019. [3] Barrio, R., Jover-Galtier, J. A., Mayora-Cebollero, A., Mayora-Cebollero, C., & Serrano, S. (2024). Synaptic dependence of dynamic regimes when coupling neural populations. Physical Review E, 109(1), 014301. [4] Mayora-Cebollero, A., Barrio, R., Li, L., Mayora-Cebollero, C., & Pérez, L. (2025). Dynamics of coupled neural populations: The role of synaptic dynamics. Chaos: An Interdisciplinary Journal of Nonlinear Science, 35(6).