---
_id: '2257'
abstract:
- lang: eng
  text: 'Maximum entropy models are the least structured probability distributions
    that exactly reproduce a chosen set of statistics measured in an interacting network.
    Here we use this principle to construct probabilistic models which describe the
    correlated spiking activity of populations of up to 120 neurons in the salamander
    retina as it responds to natural movies. Already in groups as small as 10 neurons,
    interactions between spikes can no longer be regarded as small perturbations in
    an otherwise independent system; for 40 or more neurons pairwise interactions
    need to be supplemented by a global interaction that controls the distribution
    of synchrony in the population. Here we show that such “K-pairwise” models—being
    systematic extensions of the previously used pairwise Ising models—provide an
    excellent account of the data. We explore the properties of the neural vocabulary
    by: 1) estimating its entropy, which constrains the population''s capacity to
    represent visual information; 2) classifying activity patterns into a small set
    of metastable collective modes; 3) showing that the neural codeword ensembles
    are extremely inhomogenous; 4) demonstrating that the state of individual neurons
    is highly predictable from the rest of the population, allowing the capacity for
    error correction.'
acknowledgement: 'This work was funded by NSF grant IIS-0613435, NSF grant PHY-0957573,
  NSF grant CCF-0939370, NIH grant R01 EY14196, NIH grant P50 GM071508, the Fannie
  and John Hertz Foundation, the Swartz Foundation, the WM Keck Foundation, ANR Optima
  and the French State program “Investissements d''Avenir” [LIFESENSES: ANR-10-LABX-65],
  and the Austrian Research Foundation FWF P25651.'
article_number: e1003408
article_processing_charge: No
author:
- first_name: Gasper
  full_name: Tkacik, Gasper
  id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
  last_name: Tkacik
  orcid: 0000-0002-6699-1455
- first_name: Olivier
  full_name: Marre, Olivier
  last_name: Marre
- first_name: Dario
  full_name: Amodei, Dario
  last_name: Amodei
- first_name: Elad
  full_name: Schneidman, Elad
  last_name: Schneidman
- first_name: William
  full_name: Bialek, William
  last_name: Bialek
- first_name: Michael
  full_name: Berry, Michael
  last_name: Berry
citation:
  ama: Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry M. Searching for
    collective behavior in a large network of sensory neurons. <i>PLoS Computational
    Biology</i>. 2014;10(1). doi:<a href="https://doi.org/10.1371/journal.pcbi.1003408">10.1371/journal.pcbi.1003408</a>
  apa: Tkačik, G., Marre, O., Amodei, D., Schneidman, E., Bialek, W., &#38; Berry,
    M. (2014). Searching for collective behavior in a large network of sensory neurons.
    <i>PLoS Computational Biology</i>. Public Library of Science. <a href="https://doi.org/10.1371/journal.pcbi.1003408">https://doi.org/10.1371/journal.pcbi.1003408</a>
  chicago: Tkačik, Gašper, Olivier Marre, Dario Amodei, Elad Schneidman, William Bialek,
    and Michael Berry. “Searching for Collective Behavior in a Large Network of Sensory
    Neurons.” <i>PLoS Computational Biology</i>. Public Library of Science, 2014.
    <a href="https://doi.org/10.1371/journal.pcbi.1003408">https://doi.org/10.1371/journal.pcbi.1003408</a>.
  ieee: G. Tkačik, O. Marre, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Searching
    for collective behavior in a large network of sensory neurons,” <i>PLoS Computational
    Biology</i>, vol. 10, no. 1. Public Library of Science, 2014.
  ista: Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry M. 2014. Searching
    for collective behavior in a large network of sensory neurons. PLoS Computational
    Biology. 10(1), e1003408.
  mla: Tkačik, Gašper, et al. “Searching for Collective Behavior in a Large Network
    of Sensory Neurons.” <i>PLoS Computational Biology</i>, vol. 10, no. 1, e1003408,
    Public Library of Science, 2014, doi:<a href="https://doi.org/10.1371/journal.pcbi.1003408">10.1371/journal.pcbi.1003408</a>.
  short: G. Tkačik, O. Marre, D. Amodei, E. Schneidman, W. Bialek, M. Berry, PLoS
    Computational Biology 10 (2014).
corr_author: '1'
date_created: 2018-12-11T11:56:36Z
date_published: 2014-01-02T00:00:00Z
date_updated: 2025-09-29T11:14:06Z
day: '02'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1003408
external_id:
  isi:
  - '000337948500010'
file:
- access_level: open_access
  checksum: c720222c5e924a4acb17f23b9381a6ca
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  creator: system
  date_created: 2018-12-12T10:12:46Z
  date_updated: 2020-07-14T12:45:35Z
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file_date_updated: 2020-07-14T12:45:35Z
has_accepted_license: '1'
intvolume: '        10'
isi: 1
issue: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '01'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_identifier:
  issn:
  - 1553-734X
publication_status: published
publisher: Public Library of Science
publist_id: '4689'
pubrep_id: '436'
quality_controlled: '1'
related_material:
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  - id: '5562'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: Searching for collective behavior in a large network of sensory neurons
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 10
year: '2014'
...