Event Abstract

Back to Event

Dynamical neuronal gains produce self-organized criticality in stochastic spiking neural networks.

Osame Kinouchi1*, Ariadne D. Costa1, 2, Ludmila Brochini3 and Antônio C. Roque Da Silva4
  • 1 Universidade de São Paulo, Departamento de Física - Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Brazil
  • 2 Universidade de Campinas, Instituto de Computação, Brazil
  • 3 Universidade de São Paulo, Departamento de Estatística - IME, Brazil
  • 4 Universidade de São Paulo, Departamento de Física - FFCLRP, Brazil

We show that continuous (second order) and discontinuous (first order) phase transitions occurs in networks of stochastic integrate-and-fire neurons. These transitions are obtained by a very simple analytic mean-field calculations that is exact for networks with all-to-all coupling. The second order transition is described by a critical line $\gamma_c W_c = 1$ where $\gamma$ is the average neuronal gain and $W$ is the average synaptic weight. On this line we have neuronal avalanches with standard mean-field exponents of the Directed Percolation class. The usual procedure for obtaining self-organization to criticality is to use dynamical synapses $W_{ij}[t]$ with fixed gains $\gamma_i$. Here we propose a new biological mechanism toward self-organized criticality (SOC) based in dynamical neuronal gains $\gamma[t]$ with fixed synapses $W_{ij}$. We show that SOC can be achieved because the stationary value for the average gain $\gamma^*$ satisfies the critical condition $\gamma^* W = 1$.

Acknowledgements

The authors acknowledge support from FAPESP Center for Neuromathematics (FAPESP grant 2013/07699-0).
OK and AAC also received support from CNAIPS-USP and FAPESP. LB received CNPq
support (grants 165828/2015-3 and 310706/2015-7).

Keywords: integrate-and-fire neuron, Stochastic Modeling, self-organized criticality, neuronal avalancehes, Stochastic neuron, phase transitions, Directed percolation

Conference: Neuroinformatics 2016, Reading, United Kingdom, 3 Sep - 4 Sep, 2016.

Presentation Type: Poster

Topic: Computational neuroscience

Citation: Kinouchi O, Costa AD, Brochini L and Roque Da Silva AC (2016). Dynamical neuronal gains produce self-organized criticality in stochastic spiking neural networks.. Front. Neuroinform. Conference Abstract: Neuroinformatics 2016. doi: 10.3389/conf.fninf.2016.20.00059

Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.

The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.

Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.

For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.

Received: 30 Apr 2016; Published Online: 18 Jul 2016.

* Correspondence: Prof. Osame Kinouchi, Universidade de São Paulo, Departamento de Física - Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Ribeirão Preto, São Paulo, 14040-901, Brazil, okinouchi@gmail.com