Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/12135
Title: Extracting information from neuronal populations: information theory and decoding approaches.
Authors: Quian Quiroga R
Panzeri, S
First Published: Mar-2009
Citation: NAT REV NEUROSCI, 2009, 10 (3), pp. 173-185
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.
DOI Link: 10.1038/nrn2578
eISSN: 1471-0048
Links: http://hdl.handle.net/2381/12135
Type: Journal Article
Appears in Collections:Published Articles, Dept. of Engineering

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