Robust gamma oscillations in networks of inhibitory Hippocampal interneurons

TL;DR

This study uses model simulations to demonstrate that synaptic noise enhances the robustness of gamma oscillations in inhibitory hippocampal interneuron networks, aligning with experimental observations and surpassing previous models in stability.

Contribution

The paper introduces a model showing that synaptic noise promotes robust stochastic weak synchronization in inhibitory networks, extending understanding of gamma oscillation stability.

Findings

Stochastic weak synchronization occurs with synaptic noise.

Robust gamma oscillations are observed in larger networks.

Synchronization is more resilient with increased noise.

Abstract

Recent experiments suggest that inhibitory networks of interneurons can synchronize the neuronal discharge in in vitro hippocampal slices. Subsequent theoretical work has shown that strong synchronization by mutual inhibition is only moderately robust against neuronal heterogeneities in the current drive, provided by activation of metabotropic glutamate receptors. In vivo neurons display greater variability in the interspike intervals due to the presence of synaptic noise. Noise and heterogeneity affect synchronization properties differently. In this paper we study using model simulations how robust synchronization can be in the presence of synaptic noise and neuronal heterogeneity. We find that with at least a minimum amount of noise stochastic weak synchronization (SWS) (i.e. when neurons spike within a short interval from each other, but not necessarily at each period) is produced that is much more robust than strong synchronization (i.e. when neurons spike each period). The statistics of the SWS population discharge are consistent with previous experimental data. We find robust SWS in the gamma frequency range (20-80 Hz) for a stronger synaptic coupling compared to previous models and for networks with 10 -- 1000 neurons.