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Multivariate model for cooperation: bridging social physiological compliance and hyperscanning
The neurophysiological analysis of cooperation has evolved over the past 20 years, moving towards the research of common patterns in neurophysiological signals of people interacting. Social physiological compliance (SPC) and hyperscanning represent two frameworks for the joint analysis of autonomic...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812636/ https://www.ncbi.nlm.nih.gov/pubmed/32860692 http://dx.doi.org/10.1093/scan/nsaa119 |
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author | Sciaraffa, Nicolina Liu, Jieqiong Aricò, Pietro Flumeri, Gianluca Di Inguscio, Bianca M S Borghini, Gianluca Babiloni, Fabio |
author_facet | Sciaraffa, Nicolina Liu, Jieqiong Aricò, Pietro Flumeri, Gianluca Di Inguscio, Bianca M S Borghini, Gianluca Babiloni, Fabio |
author_sort | Sciaraffa, Nicolina |
collection | PubMed |
description | The neurophysiological analysis of cooperation has evolved over the past 20 years, moving towards the research of common patterns in neurophysiological signals of people interacting. Social physiological compliance (SPC) and hyperscanning represent two frameworks for the joint analysis of autonomic and brain signals, respectively. Each of the two approaches allows to know about a single layer of cooperation according to the nature of these signals: SPC provides information mainly related to emotions, and hyperscanning that related to cognitive aspects. In this work, after the analysis of the state of the art of SPC and hyperscanning, we explored the possibility to unify the two approaches creating a complete neurophysiological model for cooperation considering both affective and cognitive mechanisms We synchronously recorded electrodermal activity, cardiac and brain signals of 14 cooperative dyads. Time series from these signals were extracted, and multivariate Granger causality was computed. The results showed that only when subjects in a dyad cooperate there is a statistically significant causality between the multivariate variables representing each subject. Moreover, the entity of this statistical relationship correlates with the dyad’s performance. Finally, given the novelty of this approach and its exploratory nature, we provided its strengths and limitations. |
format | Online Article Text |
id | pubmed-7812636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-78126362021-01-25 Multivariate model for cooperation: bridging social physiological compliance and hyperscanning Sciaraffa, Nicolina Liu, Jieqiong Aricò, Pietro Flumeri, Gianluca Di Inguscio, Bianca M S Borghini, Gianluca Babiloni, Fabio Soc Cogn Affect Neurosci Original Manuscript The neurophysiological analysis of cooperation has evolved over the past 20 years, moving towards the research of common patterns in neurophysiological signals of people interacting. Social physiological compliance (SPC) and hyperscanning represent two frameworks for the joint analysis of autonomic and brain signals, respectively. Each of the two approaches allows to know about a single layer of cooperation according to the nature of these signals: SPC provides information mainly related to emotions, and hyperscanning that related to cognitive aspects. In this work, after the analysis of the state of the art of SPC and hyperscanning, we explored the possibility to unify the two approaches creating a complete neurophysiological model for cooperation considering both affective and cognitive mechanisms We synchronously recorded electrodermal activity, cardiac and brain signals of 14 cooperative dyads. Time series from these signals were extracted, and multivariate Granger causality was computed. The results showed that only when subjects in a dyad cooperate there is a statistically significant causality between the multivariate variables representing each subject. Moreover, the entity of this statistical relationship correlates with the dyad’s performance. Finally, given the novelty of this approach and its exploratory nature, we provided its strengths and limitations. Oxford University Press 2020-08-29 /pmc/articles/PMC7812636/ /pubmed/32860692 http://dx.doi.org/10.1093/scan/nsaa119 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Manuscript Sciaraffa, Nicolina Liu, Jieqiong Aricò, Pietro Flumeri, Gianluca Di Inguscio, Bianca M S Borghini, Gianluca Babiloni, Fabio Multivariate model for cooperation: bridging social physiological compliance and hyperscanning |
title | Multivariate model for cooperation: bridging social physiological compliance and hyperscanning |
title_full | Multivariate model for cooperation: bridging social physiological compliance and hyperscanning |
title_fullStr | Multivariate model for cooperation: bridging social physiological compliance and hyperscanning |
title_full_unstemmed | Multivariate model for cooperation: bridging social physiological compliance and hyperscanning |
title_short | Multivariate model for cooperation: bridging social physiological compliance and hyperscanning |
title_sort | multivariate model for cooperation: bridging social physiological compliance and hyperscanning |
topic | Original Manuscript |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812636/ https://www.ncbi.nlm.nih.gov/pubmed/32860692 http://dx.doi.org/10.1093/scan/nsaa119 |
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