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Functional specificity of rat vibrissal primary afferents

In this study, we propose to analyze the peripheral vibrissal system specificity through its neuronal responses. Receiver operating characteristics (ROC) curve analyses were used, which required the implementation of a binary classifier (artificial neural network) trained to identify the applied sti...

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Detalles Bibliográficos
Autores principales: Lucianna, Facundo A., Farfán, Fernando D., Pizá, Gabriel A., Albarracín, Ana L., Felice, Carmelo J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908488/
https://www.ncbi.nlm.nih.gov/pubmed/27288058
http://dx.doi.org/10.14814/phy2.12810
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author Lucianna, Facundo A.
Farfán, Fernando D.
Pizá, Gabriel A.
Albarracín, Ana L.
Felice, Carmelo J.
author_facet Lucianna, Facundo A.
Farfán, Fernando D.
Pizá, Gabriel A.
Albarracín, Ana L.
Felice, Carmelo J.
author_sort Lucianna, Facundo A.
collection PubMed
description In this study, we propose to analyze the peripheral vibrissal system specificity through its neuronal responses. Receiver operating characteristics (ROC) curve analyses were used, which required the implementation of a binary classifier (artificial neural network) trained to identify the applied stimulus. The training phase consisted of the observation of a predetermined amount of vibrissal sweeps on two surfaces of different texture and similar roughness. Our results suggest that the specificity of the peripheral vibrissal system easily permits the discrimination between perceived stimuli, quantified through neuronal responses, and that it can be evaluated through an ROC curve analysis. We found that such specificity makes a linear binary classifier capable of detecting differences between stimuli with five sweeps at most.
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spelling pubmed-49084882016-06-17 Functional specificity of rat vibrissal primary afferents Lucianna, Facundo A. Farfán, Fernando D. Pizá, Gabriel A. Albarracín, Ana L. Felice, Carmelo J. Physiol Rep Original Research In this study, we propose to analyze the peripheral vibrissal system specificity through its neuronal responses. Receiver operating characteristics (ROC) curve analyses were used, which required the implementation of a binary classifier (artificial neural network) trained to identify the applied stimulus. The training phase consisted of the observation of a predetermined amount of vibrissal sweeps on two surfaces of different texture and similar roughness. Our results suggest that the specificity of the peripheral vibrissal system easily permits the discrimination between perceived stimuli, quantified through neuronal responses, and that it can be evaluated through an ROC curve analysis. We found that such specificity makes a linear binary classifier capable of detecting differences between stimuli with five sweeps at most. John Wiley and Sons Inc. 2016-06-10 /pmc/articles/PMC4908488/ /pubmed/27288058 http://dx.doi.org/10.14814/phy2.12810 Text en © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Lucianna, Facundo A.
Farfán, Fernando D.
Pizá, Gabriel A.
Albarracín, Ana L.
Felice, Carmelo J.
Functional specificity of rat vibrissal primary afferents
title Functional specificity of rat vibrissal primary afferents
title_full Functional specificity of rat vibrissal primary afferents
title_fullStr Functional specificity of rat vibrissal primary afferents
title_full_unstemmed Functional specificity of rat vibrissal primary afferents
title_short Functional specificity of rat vibrissal primary afferents
title_sort functional specificity of rat vibrissal primary afferents
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908488/
https://www.ncbi.nlm.nih.gov/pubmed/27288058
http://dx.doi.org/10.14814/phy2.12810
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