Synaptic balance due to homeostatically self-organized quasicritical dynamics

Abstract

Recent experiments suggested that homeostatic regulation of synaptic balance leads the visual system to recover and maintain a regime of power-law avalanches. Here we study an excitatory/inhibitory (E/I) mean-field neuronal network that has a critical point with power-law avalanches and synaptic balance. When short term depression in inhibitory synapses and firing threshold adaptation are added, the system hovers around the critical point. This homeostatically self-organized quasi-critical (SOqC) dynamics generates E/I synaptic current cancellation in fast time scales, causing fluctuation-driven asynchronous-irregular (AI) firing. We present the full phase diagram of the model without adaptation varying external input versus synaptic coupling. This system has a rich dynamical repertoire of spiking patterns: synchronous regular (SR), asynchronous regular (AR), synchronous irregular (SI), slow oscillations (SO) and AI. It also presents dynamic balance of synaptic currents, since inhibitory currents try and compensate excitatory currents over time, resulting in both of them scaling linearly with external input. Our model thus unifies two different perspectives on cortical spontaneous activity: both critical avalanches and fluctuation-driven AI firing arise from SOqC homeostatic adaptation, and are indeed two sides of the same coin.

arXiv comment18 pages, 4 figures

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• Role of inhibitory neurons in temporal correlations of critical and supercritical spontaneous activity
• Building a model of the brain: from detailed connectivity maps to network organization
• Critical drift in a neuro-inspired adaptive network
• Physics of Psychophysics: two coupled square lattices of spiking neurons have huge dynamic range at criticality
• Optimal input reverberation and homeostatic self-organization towards the edge of synchronization