Applied Mathematics & Information Sciences

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Neural populations encode sensory information, memory and motor patterns through electro-chemical firings, which propagate throughout the nervous system via synapses, a structure that couples neurons together. A powerful tool to investigate synchronization issues in such systems are the Phase Resetting curves. However these are best suited for brief and small perturbations. Motivated by the observation of strong inhibition in some neural circuits, we investigate a resetting model with similar features to a known neural population called striatum, in which three groups of neurons inhibit themselves. The model is intrinsically based on Kuramoto oscillators, and is analytically treatable. We derive a synchronization threshold in this model, and show numerically an unexpected complex dynamics.