Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.

We analyzed the spike discharge patterns of two types of neurons in the rodent peripheral gustatory system, Na specialists (NS) and acid generalists (AG) to lingual stimulation with NaCl, acetic acid, and mixtures of the two stimuli. Previous computational investigations found that both spike rate a...

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Main Authors: Wei Wu, Thomas G Mast, Christopher Ziembko, Joseph M Breza, Robert J Contreras
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23738016/pdf/?tool=EBI
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spelling doaj-5322f25eadb54066bb8ee1be9c4e75302021-03-04T12:11:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0185e6543910.1371/journal.pone.0065439Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.Wei WuThomas G MastChristopher ZiembkoJoseph M BrezaRobert J ContrerasWe analyzed the spike discharge patterns of two types of neurons in the rodent peripheral gustatory system, Na specialists (NS) and acid generalists (AG) to lingual stimulation with NaCl, acetic acid, and mixtures of the two stimuli. Previous computational investigations found that both spike rate and spike timing contribute to taste quality coding. These studies used commonly accepted computational methods, but they do not provide a consistent statistical evaluation of spike trains. In this paper, we adopted a new computational framework that treated each spike train as an individual data point for computing summary statistics such as mean and variance in the spike train space. We found that these statistical summaries properly characterized the firing patterns (e. g. template and variability) and quantified the differences between NS and AG neurons. The same framework was also used to assess the discrimination performance of NS and AG neurons and to remove spontaneous background activity or "noise" from the spike train responses. The results indicated that the new metric system provided the desired decoding performance and noise-removal improved stimulus classification accuracy, especially of neurons with high spontaneous rates. In summary, this new method naturally conducts statistical analysis and neural decoding under one consistent framework, and the results demonstrated that individual peripheral-gustatory neurons generate a unique and reliable firing pattern during sensory stimulation and that this pattern can be reliably decoded.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23738016/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Wei Wu
Thomas G Mast
Christopher Ziembko
Joseph M Breza
Robert J Contreras
spellingShingle Wei Wu
Thomas G Mast
Christopher Ziembko
Joseph M Breza
Robert J Contreras
Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.
PLoS ONE
author_facet Wei Wu
Thomas G Mast
Christopher Ziembko
Joseph M Breza
Robert J Contreras
author_sort Wei Wu
title Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.
title_short Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.
title_full Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.
title_fullStr Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.
title_full_unstemmed Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.
title_sort statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description We analyzed the spike discharge patterns of two types of neurons in the rodent peripheral gustatory system, Na specialists (NS) and acid generalists (AG) to lingual stimulation with NaCl, acetic acid, and mixtures of the two stimuli. Previous computational investigations found that both spike rate and spike timing contribute to taste quality coding. These studies used commonly accepted computational methods, but they do not provide a consistent statistical evaluation of spike trains. In this paper, we adopted a new computational framework that treated each spike train as an individual data point for computing summary statistics such as mean and variance in the spike train space. We found that these statistical summaries properly characterized the firing patterns (e. g. template and variability) and quantified the differences between NS and AG neurons. The same framework was also used to assess the discrimination performance of NS and AG neurons and to remove spontaneous background activity or "noise" from the spike train responses. The results indicated that the new metric system provided the desired decoding performance and noise-removal improved stimulus classification accuracy, especially of neurons with high spontaneous rates. In summary, this new method naturally conducts statistical analysis and neural decoding under one consistent framework, and the results demonstrated that individual peripheral-gustatory neurons generate a unique and reliable firing pattern during sensory stimulation and that this pattern can be reliably decoded.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23738016/pdf/?tool=EBI
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