Decorrelation of spike trains by synaptic depression

Mark S Goldman; Sacha B. Nelson; L. F. Abbott

doi:10.1016/S0925-2312(99)00068-5

Decorrelation of spike trains by synaptic depression

Mark S Goldman, Sacha B. Nelson, L. F. Abbott

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

16 Scopus citations

Abstract

Synaptic depression modeled after that seen in cortical slices removes correlations from realistic spike sequences. If not removed, such correlations can lead to inefficient and redundant neural codes. We suggest that this redundancy reduction at individual synapses enables a neuron to better process information from multiple inputs.

Original language	English (US)
Pages (from-to)	147-153
Number of pages	7
Journal	Neurocomputing
Volume	26-27
DOIs	https://doi.org/10.1016/S0925-2312(99)00068-5
State	Published - Jun 1999
Externally published	Yes

Keywords

Correlation
Cortical network
Short-term plasticity
Synaptic depression

ASJC Scopus subject areas

Artificial Intelligence
Cellular and Molecular Neuroscience

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10.1016/S0925-2312(99)00068-5

Cite this

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title = "Decorrelation of spike trains by synaptic depression",

abstract = "Synaptic depression modeled after that seen in cortical slices removes correlations from realistic spike sequences. If not removed, such correlations can lead to inefficient and redundant neural codes. We suggest that this redundancy reduction at individual synapses enables a neuron to better process information from multiple inputs.",

keywords = "Correlation, Cortical network, Short-term plasticity, Synaptic depression",

author = "Goldman, {Mark S} and Nelson, {Sacha B.} and Abbott, {L. F.}",

year = "1999",

month = jun,

doi = "10.1016/S0925-2312(99)00068-5",

language = "English (US)",

volume = "26-27",

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journal = "Neurocomputing",

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T1 - Decorrelation of spike trains by synaptic depression

AU - Goldman, Mark S

AU - Nelson, Sacha B.

AU - Abbott, L. F.

PY - 1999/6

Y1 - 1999/6

N2 - Synaptic depression modeled after that seen in cortical slices removes correlations from realistic spike sequences. If not removed, such correlations can lead to inefficient and redundant neural codes. We suggest that this redundancy reduction at individual synapses enables a neuron to better process information from multiple inputs.

AB - Synaptic depression modeled after that seen in cortical slices removes correlations from realistic spike sequences. If not removed, such correlations can lead to inefficient and redundant neural codes. We suggest that this redundancy reduction at individual synapses enables a neuron to better process information from multiple inputs.

KW - Correlation

KW - Cortical network

KW - Short-term plasticity

KW - Synaptic depression

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DO - 10.1016/S0925-2312(99)00068-5

M3 - Article

AN - SCOPUS:0032834803

VL - 26-27

SP - 147

EP - 153

JO - Neurocomputing

JF - Neurocomputing

SN - 0925-2312

ER -

Decorrelation of spike trains by synaptic depression

Abstract

Keywords

ASJC Scopus subject areas

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