• Rapid Communication

Critical excitation-inhibition balance in dense neural networks

Lorenz Baumgarten and Stefan Bornholdt
Phys. Rev. E 100, 010301(R) – Published 10 July 2019
PDFHTMLExport Citation

Abstract

The “edge of chaos” phase transition in artificial neural networks is of renewed interest in light of recent evidence for criticality in brain dynamics. Statistical mechanics traditionally studied this transition with connectivity k as the control parameter and an exactly balanced excitation-inhibition ratio. While critical connectivity has been found to be low in these model systems, typically around k=2, which is unrealistic for natural neural systems, a recent study utilizing the excitation-inhibition ratio as the control parameter found a new, nearly degree independent, critical point when connectivity is large. However, the new phase transition is accompanied by an unnaturally high level of activity in the network. Here we study random neural networks with the additional properties of (i) a high clustering coefficient and (ii) neurons that are solely either excitatory or inhibitory, a prominent property of natural neurons. As a result, we observe an additional critical point for networks with large connectivity, regardless of degree distribution, which exhibits low activity levels that compare well with neuronal brain networks.

  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Received 29 March 2019

DOI:https://doi.org/10.1103/PhysRevE.100.010301

©2019 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied PhysicsNetworksGeneral PhysicsInterdisciplinary PhysicsPhysics of Living SystemsStatistical Physics & Thermodynamics

Authors & Affiliations

Lorenz Baumgarten* and Stefan Bornholdt

  • Institut für Theoretische Physik, Universität Bremen, 28759 Bremen, Germany

  • *lbaumgarten@itp.uni-bremen.de
  • bornholdt@itp.uni-bremen.de

Article Text (Subscription Required)

Click to Expand

Supplemental Material (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 100, Iss. 1 — July 2019

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review E

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×