Bifurcation of the neuronal population dynamics of the modified theta model: transition to macroscopic gamma oscillation
Kiyoshi Kotani, Akihiko Akao, Hayato Chiba

TL;DR
This paper investigates how inhibitory neuron interactions lead to gamma oscillations, analyzing the bifurcation behavior of the modified theta model and identifying conditions for stable oscillations based on network connectivity and current distributions.
Contribution
It provides a theoretical analysis of gamma oscillation bifurcations in inhibitory neuronal populations using the modified theta model and generalized spectral theory.
Findings
Gamma oscillations exist only within a specific range of connection probabilities.
Lorentzian distribution of tonic currents simplifies the Vlasov equation to a finite-dimensional system.
Numerical simulations align with spectral and bifurcation analyses.
Abstract
Interactions of inhibitory neurons produce gamma oscillations (30--80 Hz) in the local field potential, which is known to be involved in functions such as cognition and attention. In this study, the modified theta model is considered to investigate the theoretical relationship between the microscopic structure of inhibitory neurons and their gamma oscillations under a wide class of distribution functions of tonic currents on individual neurons. The stability and bifurcation of gamma oscillations for the Vlasov equation of the model is investigated by the generalized spectral theory. It is shown that as a connection probability of neurons increases, a pair of generalized eigenvalues crosses the imaginary axis twice, which implies that a stable gamma oscillation exists only when the connection probability has a value within a suitable range. On the other hand, when the distribution of…
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