Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses
Published in Phys. Rev. E, 2013
Recommended citation: Mauricio Girardi-Schappo, Osame Kinouchi, Marcelo Tragtenberg (2013): Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses. Phys. Rev. E 88: 024701. https://dx.doi.org/10.1103/PhysRevE.88.024701
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.