Cross frequency coupling in next generation inhibitory neural mass models

TL;DR

This paper introduces a neural mass model derived from inhibitory spiking networks that can generate and analyze various oscillatory regimes and cross-frequency couplings, shedding light on neural rhythm interactions.

Contribution

The study presents a novel neural mass model capable of producing and controlling collective oscillations and cross-frequency couplings based on inhibitory neural dynamics.

Findings

Neural mass model exhibits super-critical Hopf bifurcation leading to oscillations.

Different synaptic time scales produce diverse dynamical regimes including chaos.

Bidirectional coupling induces theta-gamma cross-frequency couplings enhanced by external theta forcing.

Abstract

Coupling among neural rhythms is one of the most important mechanisms at the basis of cognitive processes in the brain. In this study we consider a neural mass model, rigorously obtained from the microscopic dynamics of an inhibitory spiking network with exponential synapses, able to autonomously generate collective oscillations (COs). These oscillations emerge via a super-critical Hopf bifurcation, and their frequencies are controlled by the synaptic time scale, the synaptic coupling and the excitability of the neural population. Furthermore, we show that two inhibitory populations in a master-slave configuration with different synaptic time scales can display various collective dynamical regimes: namely, damped oscillations towards a stable focus, periodic and quasi-periodic oscillations, and chaos. Finally, when bidirectionally coupled the two inhibitory populations can exhibit different types of theta-gamma cross-frequency couplings (CFCs): namely, phase-phase and phase-amplitude CFC. The coupling between theta and gamma COs is enhanced in presence of a external theta forcing, reminiscent of the type of modulation induced in Hippocampal and Cortex circuits via optogenetic drive.