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Abstract

Neural circuits in the brain have distinct and highly conserved ratios of excitatory and inhibitory neurons. There is typically about 20-30% of inhibitory neurons in the cortex and hippocampus. The percentage remains unchanged throughout the lifespan of an animal. The role of such a specific proportion in network dynamics remains unclear. To investigate this question, we designed a novel experimental platform that allowed us to reliably isolate inhibitory neurons from mice hippocampus and culture networks with different excitatory/inhibitory ratios. Cultures with a broad range of E/I ratios maintained stable spontaneous bursting dynamics, which we further characterized by looking at inter-burst intervals. Cultures with 10-80% of inhibitory neurons showed similar mean inter-burst intervals, whereas cultures with extreme 0% and 100% of inhibitory neurons developed longer inter-burst intervals. The coefficient of variation of inter-burst intervals grew with the number of inhibitory neurons.

To link the network properties and bursting dynamics, we fit a network of leaky integrate-and-fire neurons with spike-frequency adaptation and different ratios of excitatory and inhibitory neurons to the experimental data. The results demonstrate that a wide range of parameters may lead to the bursting dynamics observed in vitro. However, the number of inhibitory connections in fitted networks typically stayed proportional to the number of excitatory connections. This suggests the hypothesis that networks adapt to an unusual number of inhibitory cells by balancing E/I connectivity. We further validated this hypothesis by single-cell measurements in patch-clamp experiments.

After fitting the model to the recorded activity we pharmacologically blocked inhibitory receptors in different cultures and correspondingly reduced the inhibitory strength in the model. Without refitting, the increase of the mean inter-burst intervals observed in vitro was precisely matched by changes in silico bursting. We demonstrate analytically that network bursting originates from the interaction of fast inhibition and slow spike-frequency adaptation in the context of noise-driven bistable dynamics. Thus, combining measurements of collective and single-cell activity with network modeling, we identify the main mechanisms underlying the spontaneous activity of cultured hippocampal networks and show that they adapt to different numbers of inhibitory neurons by keeping the E/I connections balanced.