Speaker
Description
Phase Response Curves (PRCs) are useful in studying the existence and stability of various phase-locking modes in networks of oscillators under pulse-coupling assumptions. However, for network oscillations at higher frequencies, the basic assumptions of pulsatile coupling are broken. So, our lab recently introduced a mean field approach to study coupling and phase-locking in a network of identical oscillators with conduction delays in the neuronal context \cite{canavier2025mean}. A periodic train of biexponential conductance was divided into a tonic and a phasic component resulting in the mean field synaptic input. The theoretical predictions using this approach were tested using simulations performed on a homogenous network of inhibitory interneurons. In this work, we extend the theoretical approach to include an excitatory population of neurons to study the effects on phase locking and stability. For the simulations, we add an RTM model of an excitatory neuron to represent a synchronous population. Our results show that the mean field approach better predicts the existence and stability of synchrony compared to the classical pulsatile coupling approach. Although we use the mean field approach in the context of biological neuronal networks, there may be other applications such as in central pattern generators or cardiac circuits.
Bibliography
@article{canavier2025mean,
title={A mean field theory for pulse-coupled neural oscillators based on the spike time response curve},
author={Canavier, Carmen C},
journal={Journal of neurophysiology},
volume={133},
number={6},
pages={1630--1640},
year={2025},
publisher={American Physiological Society Rockville, MD}
}
