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Extracting information from neuronal populations: information theory and decoding approaches

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Extracting information from neuronal populations: information theory and decoding approaches. / Quian Quiroga, Rodrigo; UK, Department of Engineering University of Leicester Leicester LE1.

In: NAT REV NEUROSCI, Vol. 10, No. 3, 03.2009, p. 173-85.

Research output: SCORING: Contribution to journal › SCORING: Review article › Research

Harvard

Quian Quiroga, R & UK, DOEUOLLLE 2009, 'Extracting information from neuronal populations: information theory and decoding approaches', NAT REV NEUROSCI, vol. 10, no. 3, pp. 173-85. https://doi.org/10.1038/nrn2578

APA

Quian Quiroga, R., & UK, D. O. E. U. O. L. L. LE. (2009). Extracting information from neuronal populations: information theory and decoding approaches. NAT REV NEUROSCI, 10(3), 173-85. https://doi.org/10.1038/nrn2578

Vancouver

Quian Quiroga R, UK DOEUOLLLE. Extracting information from neuronal populations: information theory and decoding approaches. NAT REV NEUROSCI. 2009 Mar;10(3):173-85. https://doi.org/10.1038/nrn2578

Bibtex

@article{378c6d5ab7d949699d4164646df6935b,
title = "Extracting information from neuronal populations: information theory and decoding approaches",
abstract = "To a large extent, progress in neuroscience has been driven by the study of single-cell responses averaged over several repetitions of stimuli or behaviours. However,the brain typically makes decisions based on single events by evaluating the activity of large neuronal populations. Therefore, to further understand how the brain processes information, it is important to shift from a single-neuron, multiple-trial framework to multiple-neuron, single-trial methodologies. Two related approaches--decoding and information theory--can be used to extract single-trial information from the activity of neuronal populations. Such population analysis can give us more information about how neurons encode stimulus features than traditional single-cell studies.",
keywords = "Action Potentials/physiology, Algorithms, Animals, Brain/physiology, Humans, Information Theory, Nerve Net/physiology, Neural Networks, Computer, Neurons/physiology, Neurophysiology/methods, Signal Processing, Computer-Assisted",
author = "{Quian Quiroga}, Rodrigo and UK, {Department of Engineering University of Leicester Leicester LE1}",
year = "2009",
month = mar,
doi = "10.1038/nrn2578",
language = "English",
volume = "10",
pages = "173--85",
journal = "NAT REV NEUROSCI",
issn = "1471-003X",
publisher = "NATURE PUBLISHING GROUP",
number = "3",

}

RIS

TY - JOUR

T1 - Extracting information from neuronal populations: information theory and decoding approaches

AU - Quian Quiroga, Rodrigo

AU - UK, Department of Engineering University of Leicester Leicester LE1

PY - 2009/3

Y1 - 2009/3

N2 - To a large extent, progress in neuroscience has been driven by the study of single-cell responses averaged over several repetitions of stimuli or behaviours. However,the brain typically makes decisions based on single events by evaluating the activity of large neuronal populations. Therefore, to further understand how the brain processes information, it is important to shift from a single-neuron, multiple-trial framework to multiple-neuron, single-trial methodologies. Two related approaches--decoding and information theory--can be used to extract single-trial information from the activity of neuronal populations. Such population analysis can give us more information about how neurons encode stimulus features than traditional single-cell studies.

AB - To a large extent, progress in neuroscience has been driven by the study of single-cell responses averaged over several repetitions of stimuli or behaviours. However,the brain typically makes decisions based on single events by evaluating the activity of large neuronal populations. Therefore, to further understand how the brain processes information, it is important to shift from a single-neuron, multiple-trial framework to multiple-neuron, single-trial methodologies. Two related approaches--decoding and information theory--can be used to extract single-trial information from the activity of neuronal populations. Such population analysis can give us more information about how neurons encode stimulus features than traditional single-cell studies.

KW - Action Potentials/physiology

KW - Algorithms

KW - Animals

KW - Brain/physiology

KW - Humans

KW - Information Theory

KW - Nerve Net/physiology

KW - Neural Networks, Computer

KW - Neurons/physiology

KW - Neurophysiology/methods

KW - Signal Processing, Computer-Assisted

U2 - 10.1038/nrn2578

DO - 10.1038/nrn2578

M3 - SCORING: Review article

C2 - 19229240

VL - 10

SP - 173

EP - 185

JO - NAT REV NEUROSCI

JF - NAT REV NEUROSCI

SN - 1471-003X

IS - 3

ER -