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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Phase transitions and self-organized criticality in networks of stochastic spiking neurons

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Author(s):
Brochini, Ludmila ; Costa, Ariadne de Andrade ; Abadi, Miguel ; Roque, Antonio C. ; Stolfi, Jorge ; Kinouchi, Osame
Total Authors: 6
Document type: Journal article
Source: SCIENTIFIC REPORTS; v. 6, NOV 7 2016.
Web of Science Citations: 19
Abstract

Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Phi(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function F. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing. (AU)

FAPESP's process: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat
Grantee:Jefferson Antonio Galves
Support type: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 16/00430-3 - Computational simulations of stochastic integrate-and-fire neurons balanced networks
Grantee:Ariadne de Andrade Costa
Support type: Scholarships in Brazil - Post-Doctorate