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Tamburro G, Bruña R, Fiedler P, De Fano A, Raeisi K, Khazaei M, Zappasodi F, Comani S. An Analytical Approach for Naturalistic Cooperative and Competitive EEG-Hyperscanning Data: A Proof-of-Concept Study. SENSORS (BASEL, SWITZERLAND) 2024; 24:2995. [PMID: 38793851 PMCID: PMC11125252 DOI: 10.3390/s24102995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/03/2024] [Accepted: 05/02/2024] [Indexed: 05/26/2024]
Abstract
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.
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Affiliation(s)
- Gabriella Tamburro
- Behavioral Imaging and Neural Dynamics Center, G. d’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy; (A.D.F.); (F.Z.); (S.C.)
- Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti–Pescara, 66100 Chieti, Italy; (K.R.); (M.K.)
| | - Ricardo Bruña
- 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
| | - Patrique Fiedler
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, 98693 Ilmenau, Germany
| | - Antonio De Fano
- Behavioral Imaging and Neural Dynamics Center, G. d’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy; (A.D.F.); (F.Z.); (S.C.)
- Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti–Pescara, 66100 Chieti, Italy; (K.R.); (M.K.)
| | - Khadijeh Raeisi
- Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti–Pescara, 66100 Chieti, Italy; (K.R.); (M.K.)
| | - Mohammad Khazaei
- Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti–Pescara, 66100 Chieti, Italy; (K.R.); (M.K.)
| | - Filippo Zappasodi
- Behavioral Imaging and Neural Dynamics Center, G. d’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy; (A.D.F.); (F.Z.); (S.C.)
- Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti–Pescara, 66100 Chieti, Italy; (K.R.); (M.K.)
- Institute for Advanced Biomedical Technologies, University “Gabriele d’Annunzio” of Chieti–Pescara, 66100 Chieti, Italy
| | - Silvia Comani
- Behavioral Imaging and Neural Dynamics Center, G. d’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy; (A.D.F.); (F.Z.); (S.C.)
- Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti–Pescara, 66100 Chieti, Italy; (K.R.); (M.K.)
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Pinheiro AP, Schwartze M, Kotz SA. Cerebellar circuitry and auditory verbal hallucinations: An integrative synthesis and perspective. Neurosci Biobehav Rev 2020; 118:485-503. [DOI: 10.1016/j.neubiorev.2020.08.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 06/30/2020] [Accepted: 08/07/2020] [Indexed: 02/06/2023]
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Courson M, Tremblay P. Neural correlates of manual action language: Comparative review, ALE meta-analysis and ROI meta-analysis. Neurosci Biobehav Rev 2020; 116:221-238. [DOI: 10.1016/j.neubiorev.2020.06.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Revised: 03/30/2020] [Accepted: 06/18/2020] [Indexed: 10/24/2022]
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Brain source imaging based on movement-related cortical potentials induced by fatigue during self-paced handgrip contractions. Neuroreport 2020; 31:300-304. [PMID: 31895748 DOI: 10.1097/wnr.0000000000001395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE By using standard low resolution electromagnetic tomography (sLORETA), we sought to explore the changes in brain source localization when performing right handgrip contractions in the condition of muscular fatigue. METHODS Ten healthy adults volunteered for this study, and were asked to perform repeated and intermittent self-paced right handgrip contractions at 30% maximal voluntary contraction based on visual feedback leading to fatigue of right flexor digitorum profundus. Motor potentials from the movement-related cortical potentials were extracted from the electroencephalogram and were further analyzed by sLORETA. RESULTS The activated cortical regions were mainly the Brodmann area 6 on the superior frontal and medial frontal gyri, and the BA 10 on the frontal and medial frontal gyri. With the development of muscular fatigue, current density of the motor potential significantly increased and the activated cortical areas markedly enlarged. CONCLUSION In an attempt to maintain a target level of force during upper limb muscle fatigue induced by low intensity repetitive activation, the brain enhances the activation of sensorimotor cortex and enlarges the sensorimotor cortex area, especially in the ipsilateral hemisphere.
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Morris A, Ravishankar M, Pivetta L, Chowdury A, Falco D, Damoiseaux JS, Rosenberg DR, Bressler SL, Diwadkar VA. Response Hand and Motor Set Differentially Modulate the Connectivity of Brain Pathways During Simple Uni-manual Motor Behavior. Brain Topogr 2018; 31:985-1000. [PMID: 30032347 DOI: 10.1007/s10548-018-0664-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 07/17/2018] [Indexed: 01/02/2023]
Abstract
We investigated the flexible modulation of undirected functional connectivity (uFC) of brain pathways during simple uni-manual responding. Two questions were central to our interests: (1) does response hand (dominant vs. non-dominant) differentially modulate connectivity and (2) are these effects related to responding under varying motor sets. fMRI data were acquired in twenty right-handed volunteers who responded with their right (dominant) or left (non-dominant) hand (blocked across acquisitions). Within acquisitions, the task oscillated between periodic responses (promoting the emergence of motor sets) or randomly induced responses (disrupting the emergence of motor sets). Conjunction analyses revealed eight shared nodes across response hand and condition, time series from which were analyzed. For right hand responses connectivity of the M1 ←→ Thalamus and SMA ←→ Parietal pathways was more significantly modulated during periodic responding. By comparison, for left hand responses, connectivity between five network pairs (including M1 and SMA, insula, basal ganglia, premotor cortex, parietal cortex, thalamus) was more significantly modulated during random responding. uFC analyses were complemented by directed FC based on multivariate autoregressive models of times series from the nodes. These results were complementary and highlighted significant modulation of dFC for SMA → Thalamus, SMA → M1, basal ganglia → Insula and basal ganglia → Thalamus. The results demonstrate complex effects of motor organization and task demand and response hand on different connectivity classes of fMRI data. The brain's sub-networks are flexibly modulated by factors related to motor organization and/or task demand, and our results have implications for assessment of medical conditions associated with motor dysfunction.
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Affiliation(s)
- Alexandra Morris
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Suite 5A, Tolan Park Medical Building, 3901 Chrysler Service Drive, Detroit, MI, 48201, USA
| | - Mathura Ravishankar
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Suite 5A, Tolan Park Medical Building, 3901 Chrysler Service Drive, Detroit, MI, 48201, USA
| | - Lena Pivetta
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Suite 5A, Tolan Park Medical Building, 3901 Chrysler Service Drive, Detroit, MI, 48201, USA
| | - Asadur Chowdury
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Suite 5A, Tolan Park Medical Building, 3901 Chrysler Service Drive, Detroit, MI, 48201, USA
| | - Dimitri Falco
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, USA
| | - Jessica S Damoiseaux
- Department of Psychology, Wayne State University, Detroit, USA.,Institute of Gerontology, Wayne State University, Detroit, USA
| | - David R Rosenberg
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Suite 5A, Tolan Park Medical Building, 3901 Chrysler Service Drive, Detroit, MI, 48201, USA
| | - Steven L Bressler
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, USA
| | - Vaibhav A Diwadkar
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Suite 5A, Tolan Park Medical Building, 3901 Chrysler Service Drive, Detroit, MI, 48201, USA.
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