Gibbs distribution analysis of temporal correlations structure in retina ganglion cells

J. C. Vasquez; O. Marre; A. G. Palacios; M. J. Berry; B. Cessac

doi:10.1016/j.jphysparis.2011.11.001

Gibbs distribution analysis of temporal correlations structure in retina ganglion cells

J. C. Vasquez
, O. Marre
, A. G. Palacios
, M. J. Berry
, B. Cessac

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

We present a method to estimate Gibbs distributions with spatio-temporal constraints on spike trains statistics. We apply this method to spike trains recorded from ganglion cells of the salamander retina, in response to natural movies. Our analysis, restricted to a few neurons, performs more accurately than pairwise synchronization models (Ising) or the 1-time step Markov models (Marre et al., 2009) to describe the statistics of spatio-temporal spike patterns and emphasizes the role of higher order spatio-temporal interactions.

Original language	English (US)
Pages (from-to)	120-127
Number of pages	8
Journal	Journal of Physiology Paris
Volume	106
Issue number	3-4
DOIs	https://doi.org/10.1016/j.jphysparis.2011.11.001
State	Published - May 2012

All Science Journal Classification (ASJC) codes

General Neuroscience
Physiology (medical)

Keywords

Gibbs distributions
Higher-order correlation
Maximum entropy
Spike-train analysis
Statistical physics

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10.1016/j.jphysparis.2011.11.001

Cite this

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title = "Gibbs distribution analysis of temporal correlations structure in retina ganglion cells",

abstract = "We present a method to estimate Gibbs distributions with spatio-temporal constraints on spike trains statistics. We apply this method to spike trains recorded from ganglion cells of the salamander retina, in response to natural movies. Our analysis, restricted to a few neurons, performs more accurately than pairwise synchronization models (Ising) or the 1-time step Markov models (Marre et al., 2009) to describe the statistics of spatio-temporal spike patterns and emphasizes the role of higher order spatio-temporal interactions.",

keywords = "Gibbs distributions, Higher-order correlation, Maximum entropy, Spike-train analysis, Statistical physics",

author = "Vasquez, \{J. C.\} and O. Marre and Palacios, \{A. G.\} and Berry, \{M. J.\} and B. Cessac",

note = "Funding Information: This work has highly benefited from the collaboration with the INRIA team Cortex, and we warmly acknowledge T. Vi{\'e}ville. It was supported by the INRIA, ERC-NERVI number 227747, KEOPS ANR-CONICYT and European Union Project \#FP7-269921 (BrainScales) to B.C and J.C.V; grants EY 014196 and EY 017934 to M.J.B; and FONDECYT 1110292, ICM-IC09-022-P to A.P. J.C Vasquez has been funded by French ministry of Research and University of Nice (ED-STIC). ",

year = "2012",

month = may,

doi = "10.1016/j.jphysparis.2011.11.001",

language = "English (US)",

volume = "106",

pages = "120--127",

journal = "Journal of Physiology Paris",

issn = "0928-4257",

publisher = "Elsevier Masson s.r.l.",

number = "3-4",

}

TY - JOUR

T1 - Gibbs distribution analysis of temporal correlations structure in retina ganglion cells

AU - Vasquez, J. C.

AU - Marre, O.

AU - Palacios, A. G.

AU - Berry, M. J.

AU - Cessac, B.

N1 - Funding Information: This work has highly benefited from the collaboration with the INRIA team Cortex, and we warmly acknowledge T. Viéville. It was supported by the INRIA, ERC-NERVI number 227747, KEOPS ANR-CONICYT and European Union Project #FP7-269921 (BrainScales) to B.C and J.C.V; grants EY 014196 and EY 017934 to M.J.B; and FONDECYT 1110292, ICM-IC09-022-P to A.P. J.C Vasquez has been funded by French ministry of Research and University of Nice (ED-STIC).

PY - 2012/5

Y1 - 2012/5

N2 - We present a method to estimate Gibbs distributions with spatio-temporal constraints on spike trains statistics. We apply this method to spike trains recorded from ganglion cells of the salamander retina, in response to natural movies. Our analysis, restricted to a few neurons, performs more accurately than pairwise synchronization models (Ising) or the 1-time step Markov models (Marre et al., 2009) to describe the statistics of spatio-temporal spike patterns and emphasizes the role of higher order spatio-temporal interactions.

AB - We present a method to estimate Gibbs distributions with spatio-temporal constraints on spike trains statistics. We apply this method to spike trains recorded from ganglion cells of the salamander retina, in response to natural movies. Our analysis, restricted to a few neurons, performs more accurately than pairwise synchronization models (Ising) or the 1-time step Markov models (Marre et al., 2009) to describe the statistics of spatio-temporal spike patterns and emphasizes the role of higher order spatio-temporal interactions.

KW - Gibbs distributions

KW - Higher-order correlation

KW - Maximum entropy

KW - Spike-train analysis

KW - Statistical physics

UR - https://www.scopus.com/pages/publications/84862201186

UR - https://www.scopus.com/pages/publications/84862201186#tab=citedBy

U2 - 10.1016/j.jphysparis.2011.11.001

DO - 10.1016/j.jphysparis.2011.11.001

M3 - Article

C2 - 22115900

AN - SCOPUS:84862201186

SN - 0928-4257

VL - 106

SP - 120

EP - 127

JO - Journal of Physiology Paris

JF - Journal of Physiology Paris

IS - 3-4

ER -

Gibbs distribution analysis of temporal correlations structure in retina ganglion cells

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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