Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.

Electrodermal activity (EDA) is a direct read-out of sweat-induced changes in the skin's electrical conductance. Sympathetically-mediated pulsatile changes in skin sweat measured as EDA resemble an integrate-and-fire process, which yields an inverse Gaussian model as the inter-pulse interval di...

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Autores principales:	Sandya Subramanian, Patrick L Purdon, Riccardo Barbieri, Emery N Brown
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/1129d58290ab40e599ab8e5480b546df
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spelling	oai:doaj.org-article:1129d58290ab40e599ab8e5480b546df2021-12-02T19:57:34ZElementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.1553-734X1553-735810.1371/journal.pcbi.1009099https://doaj.org/article/1129d58290ab40e599ab8e5480b546df2021-07-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009099https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Electrodermal activity (EDA) is a direct read-out of sweat-induced changes in the skin's electrical conductance. Sympathetically-mediated pulsatile changes in skin sweat measured as EDA resemble an integrate-and-fire process, which yields an inverse Gaussian model as the inter-pulse interval distribution. We have previously showed that the inter-pulse intervals in EDA follow an inverse Gaussian distribution. However, the statistical structure of EDA pulse amplitudes has not yet been characterized based on the physiology. Expanding upon the integrate-and-fire nature of sweat glands, we hypothesized that the amplitude of an EDA pulse is proportional to the excess volume of sweat produced compared to what is required to just reach the surface of the skin. We modeled this as the difference of two inverse Gaussian models for each pulse, one which represents the time required to produce just enough sweat to rise to the surface of the skin and one which represents the time requires to produce the actual volume of sweat. We proposed and tested a series of four simplifications of our hypothesis, ranging from a single difference of inverse Gaussians to a single simple inverse Gaussian. We also tested four additional models for comparison, including the lognormal and gamma distributions. All models were tested on EDA data from two subject cohorts, 11 healthy volunteers during 1 hour of quiet wakefulness and a different set of 11 healthy volunteers during approximately 3 hours of controlled propofol sedation. All four models which represent simplifications of our hypothesis outperformed other models across all 22 subjects, as measured by Akaike's Information Criterion (AIC), as well as mean and maximum distance from the diagonal on a quantile-quantile plot. Our broader model set of four simplifications offered a useful framework to enhance further statistical descriptions of EDA pulse amplitudes. Some of the simplifications prioritize fit near the mode of the distribution, while others prioritize fit near the tail. With this new insight, we can summarize the physiologically-relevant amplitude information in EDA with at most four parameters. Our findings establish that physiologically based probability models provide parsimonious and accurate description of temporal and amplitude characteristics in EDA.Sandya SubramanianPatrick L PurdonRiccardo BarbieriEmery N BrownPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 7, p e1009099 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Sandya Subramanian Patrick L Purdon Riccardo Barbieri Emery N Brown Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.
description	Electrodermal activity (EDA) is a direct read-out of sweat-induced changes in the skin's electrical conductance. Sympathetically-mediated pulsatile changes in skin sweat measured as EDA resemble an integrate-and-fire process, which yields an inverse Gaussian model as the inter-pulse interval distribution. We have previously showed that the inter-pulse intervals in EDA follow an inverse Gaussian distribution. However, the statistical structure of EDA pulse amplitudes has not yet been characterized based on the physiology. Expanding upon the integrate-and-fire nature of sweat glands, we hypothesized that the amplitude of an EDA pulse is proportional to the excess volume of sweat produced compared to what is required to just reach the surface of the skin. We modeled this as the difference of two inverse Gaussian models for each pulse, one which represents the time required to produce just enough sweat to rise to the surface of the skin and one which represents the time requires to produce the actual volume of sweat. We proposed and tested a series of four simplifications of our hypothesis, ranging from a single difference of inverse Gaussians to a single simple inverse Gaussian. We also tested four additional models for comparison, including the lognormal and gamma distributions. All models were tested on EDA data from two subject cohorts, 11 healthy volunteers during 1 hour of quiet wakefulness and a different set of 11 healthy volunteers during approximately 3 hours of controlled propofol sedation. All four models which represent simplifications of our hypothesis outperformed other models across all 22 subjects, as measured by Akaike's Information Criterion (AIC), as well as mean and maximum distance from the diagonal on a quantile-quantile plot. Our broader model set of four simplifications offered a useful framework to enhance further statistical descriptions of EDA pulse amplitudes. Some of the simplifications prioritize fit near the mode of the distribution, while others prioritize fit near the tail. With this new insight, we can summarize the physiologically-relevant amplitude information in EDA with at most four parameters. Our findings establish that physiologically based probability models provide parsimonious and accurate description of temporal and amplitude characteristics in EDA.
format	article
author	Sandya Subramanian Patrick L Purdon Riccardo Barbieri Emery N Brown
author_facet	Sandya Subramanian Patrick L Purdon Riccardo Barbieri Emery N Brown
author_sort	Sandya Subramanian
title	Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.
title_short	Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.
title_full	Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.
title_fullStr	Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.
title_full_unstemmed	Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.
title_sort	elementary integrate-and-fire process underlies pulse amplitudes in electrodermal activity.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/1129d58290ab40e599ab8e5480b546df
work_keys_str_mv	AT sandyasubramanian elementaryintegrateandfireprocessunderliespulseamplitudesinelectrodermalactivity AT patricklpurdon elementaryintegrateandfireprocessunderliespulseamplitudesinelectrodermalactivity AT riccardobarbieri elementaryintegrateandfireprocessunderliespulseamplitudesinelectrodermalactivity AT emerynbrown elementaryintegrateandfireprocessunderliespulseamplitudesinelectrodermalactivity
_version_	1718375764270776320

Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.

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