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Response nonlinearities in networks of spiking neurons.

Publication ,  Journal Article
Sanzeni, A; Histed, MH; Brunel, N
Published in: PLoS Comput Biol
September 2020

Combining information from multiple sources is a fundamental operation performed by networks of neurons in the brain, whose general principles are still largely unknown. Experimental evidence suggests that combination of inputs in cortex relies on nonlinear summation. Such nonlinearities are thought to be fundamental to perform complex computations. However, these non-linearities are inconsistent with the balanced-state model, one of the most popular models of cortical dynamics, which predicts networks have a linear response. This linearity is obtained in the limit of very large recurrent coupling strength. We investigate the stationary response of networks of spiking neurons as a function of coupling strength. We show that, while a linear transfer function emerges at strong coupling, nonlinearities are prominent at finite coupling, both at response onset and close to saturation. We derive a general framework to classify nonlinear responses in these networks and discuss which of them can be captured by rate models. This framework could help to understand the diversity of non-linearities observed in cortical networks.

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Published In

PLoS Comput Biol

DOI

EISSN

1553-7358

Publication Date

September 2020

Volume

16

Issue

9

Start / End Page

e1008165

Location

United States

Related Subject Headings

  • Nonlinear Dynamics
  • Neurons
  • Nerve Net
  • Models, Neurological
  • Mice
  • Haplorhini
  • Computational Biology
  • Brain
  • Bioinformatics
  • Animals
 

Citation

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Sanzeni, A., Histed, M. H., & Brunel, N. (2020). Response nonlinearities in networks of spiking neurons. PLoS Comput Biol, 16(9), e1008165. https://doi.org/10.1371/journal.pcbi.1008165
Sanzeni, Alessandro, Mark H. Histed, and Nicolas Brunel. “Response nonlinearities in networks of spiking neurons.PLoS Comput Biol 16, no. 9 (September 2020): e1008165. https://doi.org/10.1371/journal.pcbi.1008165.
Sanzeni A, Histed MH, Brunel N. Response nonlinearities in networks of spiking neurons. PLoS Comput Biol. 2020 Sep;16(9):e1008165.
Sanzeni, Alessandro, et al. “Response nonlinearities in networks of spiking neurons.PLoS Comput Biol, vol. 16, no. 9, Sept. 2020, p. e1008165. Pubmed, doi:10.1371/journal.pcbi.1008165.
Sanzeni A, Histed MH, Brunel N. Response nonlinearities in networks of spiking neurons. PLoS Comput Biol. 2020 Sep;16(9):e1008165.

Published In

PLoS Comput Biol

DOI

EISSN

1553-7358

Publication Date

September 2020

Volume

16

Issue

9

Start / End Page

e1008165

Location

United States

Related Subject Headings

  • Nonlinear Dynamics
  • Neurons
  • Nerve Net
  • Models, Neurological
  • Mice
  • Haplorhini
  • Computational Biology
  • Brain
  • Bioinformatics
  • Animals