V-128 | The role of intrinsic neuronal properties in the synchronization of weakly-coupled neural networks

V-128 | The role of intrinsic neuronal properties in the synchronization of weakly-coupled neural networks 150 150 SAN 2024 Annual Meeting

Theoretical and Computational Neuroscience
Author: Ines Samengo | Email: ines.samengo@gmail.com


Ines Samengo1°2°3°, Bautista Arenaza1°2°3°

Department of Medical Physics, Centro Atómico Bariloche
Instituto Balseiro, Universidad Nacional de Cuyo
Consejo Nacional de Investigaciones Científicas y Técnicas

Weakly coupled neurons may or may not tend to synchronize. The factors determining this tendency include intrinsic neuronal properties and the connectivity pattern of the network. The intrinsic neuronal properties represent a vast set of parameters that govern single-neuron dynamics. Remarkably, in the limit of weak coupling, all these parameters can be encapsulated in the phase-resetting curve, which describes how the timing of the next spike is advanced or delayed based on the timing of a small and brief synaptic input. Depending on whether a neuron integrates its inputs or resonates with a specific input frequency, phase-resetting curves exhibit different functional shapes. Here, we present a theoretical framework that reveals how the shape of phase-resetting curves influences the synchrony of spiking neurons under various connectivity patterns. We demonstrate that the key factors are (a) the sign, (b) the symmetry, and (c) the magnitude of the derivative of the phase-resetting curve.

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