Cooperation in neural systems: Bridging complexity and periodicity Metadata
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- Main Title Cooperation in neural systems: Bridging complexity and periodicity
Author: Zare, MarziehCreator Type: PersonalCreator Info: University of North Texas
Author: Grigolini, PaoloCreator Type: PersonalCreator Info: University of North Texas
Name: American Physical SocietyPlace of Publication: [College Park, Maryland]
- Creation: 2012-11-29
- Content Description: Article discussing research on cooperation and neural systems and bridging complexity and periodicity.
- Physical Description: 6 p.
- Keyword: periodicity
- Keyword: neural systems
- Keyword: power index
- Keyword: inverse power
- Keyword: law distribution
- Journal: Physical Review E, 2012, College Park: American Physical Society
- Publication Title: Physical Review E
- Volume: 86
- Pages: 6
- Peer Reviewed: True
Name: UNT Scholarly WorksCode: UNTSW
Name: UNT College of Arts and SciencesCode: UNTCAS
- Rights Access: public
- DOI: 10.1103/PhysRevE.86.051918
- Archival Resource Key: ark:/67531/metadc132986
- Academic Department: Physics
- Academic Department: Center for Nonlinear Science
- 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.