Literature DB >> 32860692

Multivariate model for cooperation: bridging social physiological compliance and hyperscanning.

Nicolina Sciaraffa1,2, Jieqiong Liu3, Pietro Aricò1,2,4, Gianluca Di Flumeri1,2,4, Bianca M S Inguscio2,5, Gianluca Borghini1,2,4, Fabio Babiloni1,2,6.   

Abstract

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.
© The Author(s) 2020. Published by Oxford University Press.

Entities:  

Keywords:  EEG-hyperscanning; cooperation; multivariate Granger causality; social physiological compliance

Year:  2021        PMID: 32860692      PMCID: PMC7812636          DOI: 10.1093/scan/nsaa119

Source DB:  PubMed          Journal:  Soc Cogn Affect Neurosci        ISSN: 1749-5016            Impact factor:   3.436


  80 in total

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2.  The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference.

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3.  Interbrains cooperation: Hyperscanning and self-perception in joint actions.

Authors:  Michela Balconi; Maria Elide Vanutelli
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Review 4.  Social neuroscience and hyperscanning techniques: past, present and future.

Authors:  Fabio Babiloni; Laura Astolfi
Journal:  Neurosci Biobehav Rev       Date:  2012-08-13       Impact factor: 8.989

5.  Sex differences in neural and behavioral signatures of cooperation revealed by fNIRS hyperscanning.

Authors:  Joseph M Baker; Ning Liu; Xu Cui; Pascal Vrticka; Manish Saggar; S M Hadi Hosseini; Allan L Reiss
Journal:  Sci Rep       Date:  2016-06-08       Impact factor: 4.379

6.  Affective Synchrony and Autonomic Coupling during Cooperation: A Hyperscanning Study.

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Journal:  Biomed Res Int       Date:  2017-11-27       Impact factor: 3.411

7.  Performance similarities predict collective benefits in dyadic and triadic joint visual search.

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8.  Coupling and dynamics of cortical and autonomic signals are linked to central inhibition during the wake-sleep transition.

Authors:  Christine Ulke; Jue Huang; Justus T C Schwabedal; Galina Surova; Roland Mergl; Tilman Hensch
Journal:  Sci Rep       Date:  2017-09-18       Impact factor: 4.379

9.  Is It Easy to Synchronize Our Minds When We Are Forced to Cooperate?

Authors:  Ángel Romero-Martínez; Alejandro Rodríguez; Luis Moya-Albiol
Journal:  Brain Sci       Date:  2019-10-18

Review 10.  Hyperscanning: A Valid Method to Study Neural Inter-brain Underpinnings of Social Interaction.

Authors:  Artur Czeszumski; Sara Eustergerling; Anne Lang; David Menrath; Michael Gerstenberger; Susanne Schuberth; Felix Schreiber; Zadkiel Zuluaga Rendon; Peter König
Journal:  Front Hum Neurosci       Date:  2020-02-28       Impact factor: 3.169

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1.  Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators.

Authors:  Yuri Antonacci; Ludovico Minati; Luca Faes; Riccardo Pernice; Giandomenico Nollo; Jlenia Toppi; Antonio Pietrabissa; Laura Astolfi
Journal:  PeerJ Comput Sci       Date:  2021-05-18

2.  Being 'in sync'-is interactional synchrony the key to understanding the social brain?

Authors:  Annett Schirmer; Merle Fairhurst; Stefanie Hoehl
Journal:  Soc Cogn Affect Neurosci       Date:  2021-01-18       Impact factor: 3.436

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