Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons

Davide Bernardi and Benjamin Lindner
Phys. Rev. Lett. 118, 268301 – Published 29 June 2017
PDFHTMLExport Citation

Abstract

Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.

  • Figure
  • Figure
  • Figure
  • Figure
  • Received 19 December 2016

DOI:https://doi.org/10.1103/PhysRevLett.118.268301

© 2017 American Physical Society

Physics Subject Headings (PhySH)

Interdisciplinary PhysicsNetworksPhysics of Living Systems

Authors & Affiliations

Davide Bernardi1,2 and Benjamin Lindner1,2

  • 1Bernstein Center for Computational Neuroscience Berlin, Philippstraße 13, Haus 2, 10115 Berlin, Germany
  • 2Physics Department of Humboldt University Berlin, Newtonstraße 15, 12489 Berlin, Germany

Article Text (Subscription Required)

Click to Expand

Supplemental Material (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 118, Iss. 26 — 30 June 2017

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 Letters

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×