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Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.

Publication ,  Journal Article
Martí, D; Brunel, N; Ostojic, S
Published in: Phys Rev E
June 2018

Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in experimental data being the overrepresentation of bidirectional connections among pyramidal cells. Using numerical and analytical methods, we investigate the effects of partially symmetric connectivity on the dynamics in networks of rate units. We consider the two dynamical regimes exhibited by random neural networks: the weak-coupling regime, where the firing activity decays to a single fixed point unless the network is stimulated, and the strong-coupling or chaotic regime, characterized by internally generated fluctuating firing rates. In the weak-coupling regime, we compute analytically, for an arbitrary degree of symmetry, the autocorrelation of network activity in the presence of external noise. In the chaotic regime, we perform simulations to determine the timescale of the intrinsic fluctuations. In both cases, symmetry increases the characteristic asymptotic decay time of the autocorrelation function and therefore slows down the dynamics in the network.

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Published In

Phys Rev E

DOI

EISSN

2470-0053

Publication Date

June 2018

Volume

97

Issue

6-1

Start / End Page

062314

Location

United States

Related Subject Headings

  • Time Factors
  • Synapses
  • Neurons
  • Neural Networks, Computer
  • Models, Neurological
  • Animals
  • Action Potentials
  • 51 Physical sciences
  • 49 Mathematical sciences
  • 40 Engineering
 

Citation

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Martí, D., Brunel, N., & Ostojic, S. (2018). Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks. Phys Rev E, 97(6–1), 062314. https://doi.org/10.1103/PhysRevE.97.062314
Martí, Daniel, Nicolas Brunel, and Srdjan Ostojic. “Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.Phys Rev E 97, no. 6–1 (June 2018): 062314. https://doi.org/10.1103/PhysRevE.97.062314.
Martí, Daniel, et al. “Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.Phys Rev E, vol. 97, no. 6–1, June 2018, p. 062314. Pubmed, doi:10.1103/PhysRevE.97.062314.

Published In

Phys Rev E

DOI

EISSN

2470-0053

Publication Date

June 2018

Volume

97

Issue

6-1

Start / End Page

062314

Location

United States

Related Subject Headings

  • Time Factors
  • Synapses
  • Neurons
  • Neural Networks, Computer
  • Models, Neurological
  • Animals
  • Action Potentials
  • 51 Physical sciences
  • 49 Mathematical sciences
  • 40 Engineering