Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses

摘要

Many different kinds of noise are experimentally observed in the brain. Among them, we study a model ofnnoisy chemical synapse and obtain critical avalanches for the spatiotemporal activity of the neural network.nNeurons and synapses are modeled by dynamical maps.We discuss the relevant neuronal and synaptic propertiesnto achieve the critical state. We verify that networks of functionally excitable neurons with fast synapses presentnpower-lawavalanches, due to rebound spiking dynamics.We also discuss themeasuring of neuronal avalanches bynsubsampling our data, shedding light on the experimental search for self-organized criticality in neural networks.