Cooperation in neural systems: Bridging complexity and periodicity Metadata

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Title

  • Main Title Cooperation in neural systems: Bridging complexity and periodicity

Creator

  • Author: Zare, Marzieh
    Creator Type: Personal
    Creator Info: University of North Texas
  • Author: Grigolini, Paolo
    Creator Type: Personal
    Creator Info: University of North Texas

Publisher

  • Name: American Physical Society
    Place of Publication: [College Park, Maryland]

Date

  • Creation: 2012-11-29

Language

  • English

Description

  • Content Description: Article discussing research on cooperation and neural systems and bridging complexity and periodicity.
  • Physical Description: 6 p.

Subject

  • Keyword: periodicity
  • Keyword: neural systems
  • Keyword: power index
  • Keyword: inverse power
  • Keyword: law distribution

Source

  • Journal: Physical Review E, 2012, College Park: American Physical Society

Citation

  • Publication Title: Physical Review E
  • Volume: 86
  • Pages: 6
  • Peer Reviewed: True

Collection

  • Name: UNT Scholarly Works
    Code: UNTSW

Institution

  • Name: UNT College of Arts and Sciences
    Code: UNTCAS

Rights

  • Rights Access: public

Resource Type

  • Article

Format

  • Text

Identifier

  • DOI: 10.1103/PhysRevE.86.051918
  • Archival Resource Key: ark:/67531/metadc132986

Degree

  • Academic Department: Physics
  • Academic Department: Center for Nonlinear Science

Note

  • Display Note: Copyright 2012 American Physical Society. The following article appeared in Physical Review E, 86; http://pre.aps.org/abstract/PRE/v86/i5/e051918
  • Display Note: Abstract: Inverse power law distributions are generally interpreted as a manifestation of complexity, and waiting time distributions with power index μ < 2 reflect the occurrence of ergodicity-breaking renewal events. In this paper we show how to combine these properties with the apparently foreign clocklike nature of biological processes. We use a two-dimensional regular network of leaky integrate-and-fire neurons, each of which is linked to its four nearest neighbors, to show that both complexity and periodicity are generated by locality breakdown: Links of increasing strength have the effect of turning local interactions into long-range interactions, thereby generating time complexity followed by time periodicity. Increasing the density of neuron firings reduces the influence of periodicity, thus creating a cooperation-induced renewal condition that is distinctly non-Poissonian.