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Paper saindo do forno: Critical avalanches and subsampling in map-based neural networks coupled with noisy synapses

Phys. Rev. E 88, 024701 (2013) [5 pages]

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

Abstract
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M. Girardi-Schappo1, O. Kinouchi2,3, and M. H. R. Tragtenberg1,*
1Departamento de Física, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, Santa Catarina, Brazil
2Departamento de Física, FFCLRP, Universidade de São Paulo, 14040-900, Ribeirão Preto, São Paulo, Brazil
3Center for Natural and Artificial Information Processing Systems, Universidade de São Paulo, São Paulo, Brazil

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

URL:
http://link.aps.org/doi/10.1103/PhysRevE.88.024701
DOI:
10.1103/PhysRevE.88.024701
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