| Autor: |
Tamburro G; Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy.; Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy., Bruña R; Center for Cognitive and Computational Neuroscience (C3N), Universidad Complutense de Madrid, 28040 Madrid, Spain.; Department of Radiology, Rehabilitation and Physiotherapy, School of Medicine, Universidad Complutense de Madrid, IdISSC, 28040 Madrid, Spain., Fiedler P; Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, 98693 Ilmenau, Germany., De Fano A; Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy.; Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy., Raeisi K; Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy., Khazaei M; Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy., Zappasodi F; Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy.; Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy.; Institute for Advanced Biomedical Technologies, University 'Gabriele d'Annunzio' of Chieti-Pescara, 66100 Chieti, Italy., Comani S; Behavioral Imaging and Neural Dynamics Center, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy.; Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, 66100 Chieti, Italy. |
| Abstrakt: |
Investigating the neural mechanisms underlying both cooperative and competitive joint actions may have a wide impact in many social contexts of human daily life. An effective pipeline of analysis for hyperscanning data recorded in a naturalistic context with a cooperative and competitive motor task has been missing. We propose an analytical pipeline for this type of joint action data, which was validated on electroencephalographic (EEG) signals recorded in a proof-of-concept study on two dyads playing cooperative and competitive table tennis. Functional connectivity maps were reconstructed using the corrected imaginary part of the phase locking value (ciPLV), an algorithm suitable in case of EEG signals recorded during turn-based competitive joint actions. Hyperbrain, within-, and between-brain functional connectivity maps were calculated in three frequency bands (i.e., theta, alpha, and beta) relevant during complex motor task execution and were characterized with graph theoretical measures and a clustering approach. The results of the proof-of-concept study are in line with recent findings on the main features of the functional networks sustaining cooperation and competition, hence demonstrating that the proposed pipeline is promising tool for the analysis of joint action EEG data recorded during cooperation and competition using a turn-based motor task. |
