Hyperscanning consists in the simultaneous recording of hemodynamic or neuroelectrical signals from two or more subjects acting in a social context. Well-established methodologies for connectivity estimation have already been adapted to hyperscanning purposes. The extension of graph theory approach to multi-subjects case is still a challenging issue. In the present work we aim to test the ability of the currently used graph theory global indices in describing the properties of a network given by two interacting subjects. The testing was conducted first on surrogate brain-to-brain networks reproducing typical social scenarios and then on real EEG hyperscanning data recorded during a Joint Action task. The results of the simulation study highlighted the ability of all the investigated indexes in modulating their values according to the level of interaction between subjects. However, only global efficiency and path length indexes demonstrated to be sensitive to an asymmetry in the communication between the two subjects. Such results were, then, confirmed by the application on real EEG data. Global efficiency modulated, in fact, their values according to the inter-brain density, assuming higher values in the social condition with respect to the non-social condition.

Graph theory in brain-to-brain connectivity: A simulation study and an application to an EEG hyperscanning experiment / Toppi, Jlenia; Ciaramidaro, Angela; Vogel, P.; Mattia, D.; Babiloni, Fabio; Siniatchkin, M.; Astolfi, Laura. - 2015-November:(2015), pp. 2211-2214. ((Intervento presentato al convegno 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 tenutosi a Milan; Itlay nel 25-29 August 2015 [10.1109/EMBC.2015.7318830].

Graph theory in brain-to-brain connectivity: A simulation study and an application to an EEG hyperscanning experiment

CIARAMIDARO, ANGELA;
2015-01-01

Abstract

Hyperscanning consists in the simultaneous recording of hemodynamic or neuroelectrical signals from two or more subjects acting in a social context. Well-established methodologies for connectivity estimation have already been adapted to hyperscanning purposes. The extension of graph theory approach to multi-subjects case is still a challenging issue. In the present work we aim to test the ability of the currently used graph theory global indices in describing the properties of a network given by two interacting subjects. The testing was conducted first on surrogate brain-to-brain networks reproducing typical social scenarios and then on real EEG hyperscanning data recorded during a Joint Action task. The results of the simulation study highlighted the ability of all the investigated indexes in modulating their values according to the level of interaction between subjects. However, only global efficiency and path length indexes demonstrated to be sensitive to an asymmetry in the communication between the two subjects. Such results were, then, confirmed by the application on real EEG data. Global efficiency modulated, in fact, their values according to the inter-brain density, assuming higher values in the social condition with respect to the non-social condition.
37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Milan; Itlay
25-29 August 2015
2015-November
2211
2214
Toppi, Jlenia; Ciaramidaro, Angela; Vogel, P.; Mattia, D.; Babiloni, Fabio; Siniatchkin, M.; Astolfi, Laura
Graph theory in brain-to-brain connectivity: A simulation study and an application to an EEG hyperscanning experiment / Toppi, Jlenia; Ciaramidaro, Angela; Vogel, P.; Mattia, D.; Babiloni, Fabio; Siniatchkin, M.; Astolfi, Laura. - 2015-November:(2015), pp. 2211-2214. ((Intervento presentato al convegno 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 tenutosi a Milan; Itlay nel 25-29 August 2015 [10.1109/EMBC.2015.7318830].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1175227
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