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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Autores principales:	Wei Wu, Thomas G Mast, Christopher Ziembko, Joseph M Breza, Robert J Contreras
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5322f25eadb54066bb8ee1be9c4e7530
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spelling	oai:doaj.org-article:5322f25eadb54066bb8ee1be9c4e75302021-11-18T07:43:46ZStatistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.1932-620310.1371/journal.pone.0065439https://doaj.org/article/5322f25eadb54066bb8ee1be9c4e75302013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23738016/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203We 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.Wei WuThomas G MastChristopher ZiembkoJoseph M BrezaRobert J ContrerasPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 5, p e65439 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q 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.
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.
format	article
author	Wei Wu Thomas G Mast Christopher Ziembko Joseph M Breza Robert J Contreras
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)
publishDate	2013
url	https://doaj.org/article/5322f25eadb54066bb8ee1be9c4e7530
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Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.

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