Robust cortical criticality and diverse dynamics resulting from functional specification

Lei Gu and Ruqian Wu
Phys. Rev. E 103, 042407 – Published 12 April 2021

Abstract

Despite the recognition of the layered structure and evident criticality in the cortex, how the specification of input, output, and computational layers affects the self-organized criticality has not been much explored. By constructing heterogeneous structures with a well-accepted model of leaky neurons, we find that the specification can lead to robust criticality rather insensitive to the strength of external stimuli. This naturally unifies the adaptation to strong inputs without extra synaptic plasticity mechanisms. Low degree of recurrence constitutes an alternative explanation to subcriticality other than the high-frequency inputs. Unlike fully recurrent networks where external stimuli always render subcriticality, the dynamics of networks with sufficient feedforward connections can be driven to criticality and supercriticality. These findings indicate that functional and structural specification and their interplay with external stimuli are of crucial importance for the network dynamics. The robust criticality puts forward networks of the leaky neurons as promising platforms for realizing artificial neural networks that work in the vicinity of critical points.

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  • Received 11 November 2020
  • Revised 12 February 2021
  • Accepted 23 March 2021

DOI:https://doi.org/10.1103/PhysRevE.103.042407

©2021 American Physical Society

Physics Subject Headings (PhySH)

Physics of Living Systems

Authors & Affiliations

Lei Gu and Ruqian Wu*

  • Department of Physics and Astronomy, University of California, Irvine, California 92697, USA

  • *wur@uci.edu

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Issue

Vol. 103, Iss. 4 — April 2021

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