Phys. Rev. E 88, 024701 (2013) [5 pages]
Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses
Received 23 August 2012; revised 29 May 2013; published 27 August 2013
Many different kinds of noise are experimentally observed in the brain. Among them, we study a model of noisy chemical synapse and obtain critical avalanches for the spatiotemporal activity of the neural network. Neurons and synapses are modeled by dynamical maps. We discuss the relevant neuronal and synaptic properties to achieve the critical state. We verify that networks of functionally excitable neurons with fast synapses present power-law avalanches, due to rebound spiking dynamics. We also discuss the measuring of neuronal avalanches by subsampling our data, shedding light on the experimental search for self-organized criticality in neural networks.
©2013 American Physical Society