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

Phys Rev Lett. 2017 Jun 30;118(26):268301. doi: 10.1103/PhysRevLett.118.268301. Epub 2017 Jun 29.

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.

MeSH terms

  • Action Potentials*
  • Animals
  • Models, Neurological*
  • Nerve Net
  • Neurons / physiology*
  • Rats