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Response Features Determining Spike Times

Interpreting messages encoded in single neuronal responses requires knowing which features of the responses carry information. That the number of spikes is an important part of the code has long been obvious. In recent years, it has been shown that modulation of the firing rate with about 25 ms prec...

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Detalles Bibliográficos
Autores principales: Richmond, Barry J., Oram, Mike W., Wiener, Matthew C.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 1999
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2565320/
https://www.ncbi.nlm.nih.gov/pubmed/10714266
http://dx.doi.org/10.1155/NP.1999.133
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author Richmond, Barry J.
Oram, Mike W.
Wiener, Matthew C.
author_facet Richmond, Barry J.
Oram, Mike W.
Wiener, Matthew C.
author_sort Richmond, Barry J.
collection PubMed
description Interpreting messages encoded in single neuronal responses requires knowing which features of the responses carry information. That the number of spikes is an important part of the code has long been obvious. In recent years, it has been shown that modulation of the firing rate with about 25 ms precision carries information that is not available from the total number of spikes across the whole response. It has been proposed that patterns of exactly timed (1 ms precision) spikes, such as repeating triplets or quadruplets, might carry information that is not available from knowing about spike count and rate modulation. A model using the spike count distribution, the low pass filtered PSTH (bandwidth below 30 Hz), and, to a small degree, the interspike interval distribution predicts the numbers and types of exactly-timed triplets and quadruplets that are indistinguishable from those found in the data. From this it can be concluded that the coarse (<30 Hz) sequential correlation structure over time gives rise to the exactly timed patterns present in the recorded spike trains. Because the coarse temporal structure predicts the fine temporal structure, the information carried by the fine temporal structure must be completely redundant with that carried by the coarse structure. Thus, the existence of precisely timed spike patterns carrying stimulus-related information does not imply control of spike timing at precise time scales.
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spelling pubmed-25653202008-10-16 Response Features Determining Spike Times Richmond, Barry J. Oram, Mike W. Wiener, Matthew C. Neural Plast Article Interpreting messages encoded in single neuronal responses requires knowing which features of the responses carry information. That the number of spikes is an important part of the code has long been obvious. In recent years, it has been shown that modulation of the firing rate with about 25 ms precision carries information that is not available from the total number of spikes across the whole response. It has been proposed that patterns of exactly timed (1 ms precision) spikes, such as repeating triplets or quadruplets, might carry information that is not available from knowing about spike count and rate modulation. A model using the spike count distribution, the low pass filtered PSTH (bandwidth below 30 Hz), and, to a small degree, the interspike interval distribution predicts the numbers and types of exactly-timed triplets and quadruplets that are indistinguishable from those found in the data. From this it can be concluded that the coarse (<30 Hz) sequential correlation structure over time gives rise to the exactly timed patterns present in the recorded spike trains. Because the coarse temporal structure predicts the fine temporal structure, the information carried by the fine temporal structure must be completely redundant with that carried by the coarse structure. Thus, the existence of precisely timed spike patterns carrying stimulus-related information does not imply control of spike timing at precise time scales. Hindawi Publishing Corporation 1999 /pmc/articles/PMC2565320/ /pubmed/10714266 http://dx.doi.org/10.1155/NP.1999.133 Text en Copyright © 1999 .
spellingShingle Article
Richmond, Barry J.
Oram, Mike W.
Wiener, Matthew C.
Response Features Determining Spike Times
title Response Features Determining Spike Times
title_full Response Features Determining Spike Times
title_fullStr Response Features Determining Spike Times
title_full_unstemmed Response Features Determining Spike Times
title_short Response Features Determining Spike Times
title_sort response features determining spike times
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2565320/
https://www.ncbi.nlm.nih.gov/pubmed/10714266
http://dx.doi.org/10.1155/NP.1999.133
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