Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model

Area of Science:

• Neuroscience
• Computational Neuroscience

Background:

• Fast neuronal oscillations, specifically gamma (20-80 Hz), are linked to behavioral arousal in the neocortex and hippocampus.
• The precise mechanisms generating these oscillations in neural networks remain an active area of research.

Purpose of the Study:

• To investigate the emergence of gamma oscillations in a random network of GABAergic fast-spiking interneurons using computer simulations.
• To identify the specific cellular and circuit conditions necessary for population synchronization.

Main Methods:

• Utilized computer simulations of interconnected GABAergic fast-spiking interneurons.
• Employed a population coherence measure based on coincident neural firings.
• Varied parameters such as spike afterhyperpolarization, synaptic decay time, network connectivity, and external excitatory drive.

Main Results:

• Identified key conditions for population synchronization: spike afterhyperpolarization above GABAA reversal potential, sufficient synaptic decay time relative to oscillation period, and modest cellular heterogeneity.
• Determined that a critical number of synaptic contacts per cell is essential for large-scale network synchronization.
• Observed that network synchronization was highest within the gamma frequency band (20-80 Hz), despite monotonic changes in firing frequency with parameter variations.

Conclusions:

• GABAergic synaptic transmission is a viable mechanism for generating synchronized gamma oscillations in sparsely connected fast-spiking interneuron networks.
• Such interneuron networks may play a role in maintaining subthreshold oscillations in principal cells and synchronizing neuronal discharges across brain regions.