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, Jahrgang 10, Nr. 3, 03.2009, S. 173-85.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Review › Forschung
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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 -