English

Cooperation in Neural Systems: Bridging Complexity and Periodicity

Adaptation and Self-Organizing Systems 2015-06-11 v2 Neurons and Cognition

Abstract

Inverse power law distributions are generally interpreted as a manifestation of complexity, and waiting time distributions with power index \mu < 2 reflect the occurrence of ergodicity breaking renewal events. In this Letter 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 into long-range interaction, thereby generating first time complexity and then time periodicity. Increasing the density of neuron firings reduces the influence of periodicity thus creating a cooperation-induced distinctly non-Poisson renewal condition.

Keywords

Cite

@article{arxiv.1208.0547,
  title  = {Cooperation in Neural Systems: Bridging Complexity and Periodicity},
  author = {Marzieh Zare and Paolo Grigolini},
  journal= {arXiv preprint arXiv:1208.0547},
  year   = {2015}
}

Comments

The paper is under review and might be under copyright of a journal

R2 v1 2026-06-21T21:45:24.827Z