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Tamburro G, Fiedler P, De Fano A, Raeisi K, Khazaei M, Vaquero L, Bruña R, Oppermann H, Bertollo M, Filho E, Zappasodi F, Comani S. An ecological study protocol for the multimodal investigation of the neurophysiological underpinnings of dyadic joint action. Front Hum Neurosci 2023; 17:1305331. [PMID: 38125713 PMCID: PMC10730734 DOI: 10.3389/fnhum.2023.1305331] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 11/15/2023] [Indexed: 12/23/2023] Open
Abstract
A novel multimodal experimental setup and dyadic study protocol were designed to investigate the neurophysiological underpinnings of joint action through the synchronous acquisition of EEG, ECG, EMG, respiration and kinematic data from two individuals engaged in ecologic and naturalistic cooperative and competitive joint actions involving face-to-face real-time and real-space coordinated full body movements. Such studies are still missing because of difficulties encountered in recording reliable neurophysiological signals during gross body movements, in synchronizing multiple devices, and in defining suitable study protocols. The multimodal experimental setup includes the synchronous recording of EEG, ECG, EMG, respiration and kinematic signals of both individuals via two EEG amplifiers and a motion capture system that are synchronized via a single-board microcomputer and custom Python scripts. EEG is recorded using new dry sports electrode caps. The novel study protocol is designed to best exploit the multimodal data acquisitions. Table tennis is the dyadic motor task: it allows naturalistic and face-to-face interpersonal interactions, free in-time and in-space full body movement coordination, cooperative and competitive joint actions, and two task difficulty levels to mimic changing external conditions. Recording conditions-including minimum table tennis rally duration, sampling rate of kinematic data, total duration of neurophysiological recordings-were defined according to the requirements of a multilevel analytical approach including a neural level (hyperbrain functional connectivity, Graph Theoretical measures and Microstate analysis), a cognitive-behavioral level (integrated analysis of neural and kinematic data), and a social level (extending Network Physiology to neurophysiological data recorded from two interacting individuals). Four practical tests for table tennis skills were defined to select the study population, permitting to skill-match the dyad members and to form two groups of higher and lower skilled dyads to explore the influence of skill level on joint action performance. Psychometric instruments are included to assess personality traits and support interpretation of results. Studying joint action with our proposed protocol can advance the understanding of the neurophysiological mechanisms sustaining daily life joint actions and could help defining systems to predict cooperative or competitive behaviors before being overtly expressed, particularly useful in real-life contexts where social behavior is a main feature.
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Affiliation(s)
- Gabriella Tamburro
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Patrique Fiedler
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Antonio De Fano
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Khadijeh Raeisi
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Mohammad Khazaei
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Lucia Vaquero
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Pschology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Radiology, Universidad Complutense de Madrid, IdISSC, Madrid, Spain
| | - Hannes Oppermann
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Maurizio Bertollo
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Department of Medicine and Sciences of Aging, “University G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Edson Filho
- Wheelock College of Education and Human Development, Boston University, Boston, MA, United States
| | - Filippo Zappasodi
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Silvia Comani
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
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2
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Zhang W, Qiu L, Tang F, Sun HJ. Gender differences in cognitive and affective interpersonal emotion regulation in couples: an fNIRS hyperscanning. Soc Cogn Affect Neurosci 2023; 18:nsad057. [PMID: 37837406 PMCID: PMC10612568 DOI: 10.1093/scan/nsad057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 08/24/2023] [Accepted: 10/07/2023] [Indexed: 10/16/2023] Open
Abstract
Emotion regulation is vital in maintaining romantic relationships in couples. Although gender differences exist in cognitive and affective strategies during 'intrapersonal' emotion regulation, it is unclear how gender differences through affective bonds work in 'interpersonal' emotion regulation (IER) in couples. Thirty couple dyads and 30 stranger dyads underwent functional near-infrared spectroscopy hyperscanning recordings when targets complied with their partner's cognitive engagement (CE) and affective engagement (AE) strategies after viewing sad and neutral videos. Behaviorally, for males, CE was less effective than AE in both groups, but little difference occurred for females between AE and CE. For couples, Granger causality analysis showed that male targets had less neural activity than female targets in CH06, CH13 and CH17 during CE. For inflow and outflow activities on CH06 and CH13 (frontopolar cortex), respectively, male targets had less activity in the CE condition than in the AE condition, while for outflow activities on CH 17 (dorsolateral prefrontal cortex), female targets had more activity in the CE condition than in the AE condition. However, these differences were not observed in strangers. These results suggest gender differences in CE but not in AE and dissociable flow patterns in male and female targets in couples during sadness regulation.
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Affiliation(s)
- Wenhai Zhang
- School of Education Science, Hengyang Normal University, Hengyang 421002, China
- The Big Data Centre for Neuroscience and AI, Hengyang Normal University, Hengyang 421002, China
| | - Lanting Qiu
- School of Education Science, Hengyang Normal University, Hengyang 421002, China
| | - Fanggui Tang
- School of Education Science, Hengyang Normal University, Hengyang 421002, China
| | - Hong-Jin Sun
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON L8S 4L8, Canada
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3
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Antonacci Y, Barà C, Zaccaro A, Ferri F, Pernice R, Faes L. Time-varying information measures: an adaptive estimation of information storage with application to brain-heart interactions. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1242505. [PMID: 37920446 PMCID: PMC10619917 DOI: 10.3389/fnetp.2023.1242505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 10/02/2023] [Indexed: 11/04/2023]
Abstract
Network Physiology is a rapidly growing field of study that aims to understand how physiological systems interact to maintain health. Within the information theory framework the information storage (IS) allows to measure the regularity and predictability of a dynamic process under stationarity assumption. However, this assumption does not allow to track over time the transient pathways occurring in the dynamical activity of a physiological system. To address this limitation, we propose a time-varying approach based on the recursive least squares algorithm (RLS) for estimating IS at each time instant, in non-stationary conditions. We tested this approach in simulated time-varying dynamics and in the analysis of electroencephalographic (EEG) signals recorded from healthy volunteers and timed with the heartbeat to investigate brain-heart interactions. In simulations, we show that the proposed approach allows to track both abrupt and slow changes in the information stored in a physiological system. These changes are reflected in its evolution and variability over time. The analysis of brain-heart interactions reveals marked differences across the cardiac cycle phases of the variability of the time-varying IS. On the other hand, the average IS values exhibit a weak modulation over parieto-occiptal areas of the scalp. Our study highlights the importance of developing more advanced methods for measuring IS that account for non-stationarity in physiological systems. The proposed time-varying approach based on RLS represents a useful tool for identifying spatio-temporal dynamics within the neurocardiac system and can contribute to the understanding of brain-heart interactions.
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Affiliation(s)
- Yuri Antonacci
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Chiara Barà
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Andrea Zaccaro
- Department of Neuroscience, Imaging and Clinical Sciences, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy
| | - Francesca Ferri
- Department of Neuroscience, Imaging and Clinical Sciences, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies (ITAB), “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy
| | - Riccardo Pernice
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Luca Faes
- Department of Engineering, University of Palermo, Palermo, Italy
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Hakim U, De Felice S, Pinti P, Zhang X, Noah JA, Ono Y, Burgess PW, Hamilton A, Hirsch J, Tachtsidis I. Quantification of inter-brain coupling: A review of current methods used in haemodynamic and electrophysiological hyperscanning studies. Neuroimage 2023; 280:120354. [PMID: 37666393 DOI: 10.1016/j.neuroimage.2023.120354] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/06/2023] Open
Abstract
Hyperscanning is a form of neuroimaging experiment where the brains of two or more participants are imaged simultaneously whilst they interact. Within the domain of social neuroscience, hyperscanning is increasingly used to measure inter-brain coupling (IBC) and explore how brain responses change in tandem during social interaction. In addition to cognitive research, some have suggested that quantification of the interplay between interacting participants can be used as a biomarker for a variety of cognitive mechanisms aswell as to investigate mental health and developmental conditions including schizophrenia, social anxiety and autism. However, many different methods have been used to quantify brain coupling and this can lead to questions about comparability across studies and reduce research reproducibility. Here, we review methods for quantifying IBC, and suggest some ways moving forward. Following the PRISMA guidelines, we reviewed 215 hyperscanning studies, across four different brain imaging modalities: functional near-infrared spectroscopy (fNIRS), functional magnetic resonance (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG). Overall, the review identified a total of 27 different methods used to compute IBC. The most common hyperscanning modality is fNIRS, used by 119 studies, 89 of which adopted wavelet coherence. Based on the results of this literature survey, we first report summary statistics of the hyperscanning field, followed by a brief overview of each signal that is obtained from each neuroimaging modality used in hyperscanning. We then discuss the rationale, assumptions and suitability of each method to different modalities which can be used to investigate IBC. Finally, we discuss issues surrounding the interpretation of each method.
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Affiliation(s)
- U Hakim
- Department of Medical Physics and Biomedical Engineering, University College London, Malet Place Engineering Building, Gower Street, London WC1E 6BT, United Kingdom.
| | - S De Felice
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom; Department of Psychology, University of Cambridge, United Kingdom
| | - P Pinti
- Department of Medical Physics and Biomedical Engineering, University College London, Malet Place Engineering Building, Gower Street, London WC1E 6BT, United Kingdom; Centre for Brain and Cognitive Development, Birkbeck, University of London, London, United Kingdom
| | - X Zhang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - J A Noah
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Y Ono
- Department of Electronics and Bioinformatics, School of Science and Technology, Meiji University, Kawasaki, Kanagawa, Japan
| | - P W Burgess
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - A Hamilton
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - J Hirsch
- Department of Medical Physics and Biomedical Engineering, University College London, Malet Place Engineering Building, Gower Street, London WC1E 6BT, United Kingdom; Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States; Departments of Neuroscience and Comparative Medicine, Yale School of Medicine, New Haven, CT, United States; Yale University, Wu Tsai Institute, New Haven, CT, United States
| | - I Tachtsidis
- Department of Medical Physics and Biomedical Engineering, University College London, Malet Place Engineering Building, Gower Street, London WC1E 6BT, United Kingdom
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Chuang C, Hsu H. Pseudo-mutual gazing enhances interbrain synchrony during remote joint attention tasking. Brain Behav 2023; 13:e3181. [PMID: 37496332 PMCID: PMC10570487 DOI: 10.1002/brb3.3181] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/29/2023] [Accepted: 07/13/2023] [Indexed: 07/28/2023] Open
Abstract
INTRODUCTION Mutual gaze enables people to share attention and increase engagement during social interactions through intentional and implicit messages. Although previous studies have explored gaze behaviors and neural mechanisms underlying in-person eye contact, the growing prevalence of remote communication has raised questions about how to establish mutual gaze remotely and how the brains of interacting individuals synchronize. METHODS To address these questions, we conducted a study using eye trackers to create a pseudo-mutual gaze channel that mirrors the gazes of each interacting dyad on their respective remote screens. To demonstrate fluctuations in coupling across brains, we incorporated electroencephalographic hyperscanning techniques to simultaneously record the brain activity of interacting dyads engaged in a joint attention task in player-observer, collaborative, and competitive modes. RESULTS Our results indicated that mutual gaze could improve the efficiency of joint attention activities among remote partners. Moreover, by employing the phase locking value, we could estimate interbrain synchrony (IBS) and observe low-frequency couplings in the frontal and temporal regions that varied based on the interaction mode. While dyadic gender composition significantly affected gaze patterns, it did not impact the IBS. CONCLUSION These results provide insight into the neurological mechanisms underlying remote interaction through the pseudo-mutual gaze channel and have significant implications for developing effective online communication environments.
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Affiliation(s)
- Chun‐Hsiang Chuang
- Research Center for Education and Mind Sciences, College of EducationNational Tsing Hua UniversityHsinchuTaiwan
- Institute of Information Systems and ApplicationsCollege of Electrical Engineering and Computer ScienceNational Tsing Hua UniversityHsinchuTaiwan
| | - Hao‐Che Hsu
- Research Center for Education and Mind Sciences, College of EducationNational Tsing Hua UniversityHsinchuTaiwan
- Department of Computer ScienceNational Yang Ming Chiao Tung UniversityHsinchuTaiwan
- Department of Computer Science and EngineeringNational Taiwan Ocean UniversityKeelungTaiwan
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Schwartz L, Levy J, Endevelt-Shapira Y, Djalovski A, Hayut O, Dumas G, Feldman R. Technologically-assisted communication attenuates inter-brain synchrony. Neuroimage 2022; 264:119677. [PMID: 36244598 DOI: 10.1016/j.neuroimage.2022.119677] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 10/06/2022] [Accepted: 10/07/2022] [Indexed: 11/06/2022] Open
Abstract
The transition to technologically-assisted communication has permeated all facets of human social life; yet, its impact on the social brain is still unknown and the effects may be particularly intense during periods of developmental transitions. Applying a two-brain perspective, the current preregistered study utilized hyperscanning EEG to measure brain-to-brain synchrony in 62 mother-child pairs at the transition to adolescence (child age; M = 12.26, range 10-14) during live face-to-face interaction versus technologically-assisted remote communication. The live interaction elicited 9 significant cross-brain links between densely inter-connected frontal and temporal areas in the beta range [14-30 Hz]. Mother's right frontal region connected with the child's right and left frontal, temporal, and central regions, suggesting its regulatory role in organizing the two-brain dynamics. In contrast, the remote interaction elicited only 1 significant cross-brain-cross-hemisphere link, attenuating the robust right-to-right-brain connectivity during live social moments that communicates socio-affective signals. Furthermore, while the level of social behavior was comparable between the two interactions, brain-behavior associations emerged only during the live exchange. Mother-child right temporal-temporal synchrony linked with moments of shared gaze and the degree of child engagement and empathic behavior correlated with right frontal-frontal synchrony. Our findings indicate that human co-presence is underpinned by specific neurobiological processes that should be studied in depth. Much further research is needed to tease apart whether the "Zoom fatigue" experienced during technological communication may stem, in part, from overload on more limited inter-brain connections and to address the potential cost of social technology for brain maturation, particularly among youth.
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Affiliation(s)
- Linoy Schwartz
- Center for Developmental Social Neuroscience, Reichman University, Herzliya, Israel
| | - Jonathan Levy
- Center for Developmental Social Neuroscience, Reichman University, Herzliya, Israel; Department of Neuroscience and Biomedical Engineering, Aalto University, Finland
| | | | - Amir Djalovski
- Center for Developmental Social Neuroscience, Reichman University, Herzliya, Israel
| | - Olga Hayut
- Center for Developmental Social Neuroscience, Reichman University, Herzliya, Israel
| | - Guillaume Dumas
- Precision Psychiatry and Social Physiology laboratory, CHU Sainte-Justine Research Center, Department of Psychiatry, Université de Montréal, Montreal, QC, Canada
| | - Ruth Feldman
- Center for Developmental Social Neuroscience, Reichman University, Herzliya, Israel; Child Study Center, Yale University, United States.
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Borghini G, Arico P, Di Flumeri G, Sciaraffa N, Di Florio A, Ronca V, Giorgi A, Mezzadri L, Gasparini R, Tartaglino R, Trettel A, Babiloni F. Real-time Pilot Crew's Mental Workload and Arousal Assessment During Simulated Flights for Training Evaluation: a Case Study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:3568-3571. [PMID: 36086259 DOI: 10.1109/embc48229.2022.9871893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Training assessment is usually done by evaluating information derived from instructor's supervision related to the pilot's operational performance and behavior. However, this approach lacks objective measures, especially regarding the pilots' mental states while accomplishing the flight training tasks. The study therefore aimed at developing and testing a method for gathering and analyzing in real-time pilots' brain activity and skin conductance to improve the training evaluation. In this regard, Novice pilots' neurophysiological signals were acquired throughout multi-crew training sessions. The results demonstrated how the methodology proposed was able to endow real-time pilots' mental workload and arousal assessment for i) better evaluating training progress and operational behavior during the training session, and ii) for objectively comparing different training sessions.
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Inguscio BMS, Mancini P, Greco A, Nicastri M, Giallini I, Leone CA, Grassia R, Di Nardo W, Di Cesare T, Rossi F, Canale A, Albera A, Giorgi A, Malerba P, Babiloni F, Cartocci G. ‘Musical effort’ and ‘musical pleasantness’: a pilot study on the neurophysiological correlates of classical music listening in adults normal hearing and unilateral cochlear implant users. HEARING, BALANCE AND COMMUNICATION 2022. [DOI: 10.1080/21695717.2022.2079325] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
| | - Patrizia Mancini
- Department of Sense Organs, Sapienza University of Rome, Rome, Italy
| | - Antonio Greco
- Department of Sense Organs, Sapienza University of Rome, Rome, Italy
| | - Maria Nicastri
- Department of Sense Organs, Sapienza University of Rome, Rome, Italy
| | - Ilaria Giallini
- Department of Sense Organs, Sapienza University of Rome, Rome, Italy
| | - Carlo Antonio Leone
- Department of Otolaryngology/Head and Neck Surgery, Monaldi Hospital, Naples, Italy
| | - Rosa Grassia
- Department of Otolaryngology/Head and Neck Surgery, Monaldi Hospital, Naples, Italy
| | - Walter Di Nardo
- Otorhinolaryngology and Physiology, Catholic University of Rome, Rome, Italy
| | - Tiziana Di Cesare
- Otorhinolaryngology and Physiology, Catholic University of Rome, Rome, Italy
| | - Federica Rossi
- Otorhinolaryngology and Physiology, Catholic University of Rome, Rome, Italy
| | - Andrea Canale
- Division of Otorhinolaryngology, Department of Surgical Sciences, University of Turin, Italy
| | - Andrea Albera
- Division of Otorhinolaryngology, Department of Surgical Sciences, University of Turin, Italy
| | | | | | - Fabio Babiloni
- BrainSigns Srl, Rome, Italy
- Department of Computer Science, Hangzhou Dianzi University, Hangzhou, China
- Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy
| | - Giulia Cartocci
- BrainSigns Srl, Rome, Italy
- Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy
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Reindl V, Wass S, Leong V, Scharke W, Wistuba S, Wirth CL, Konrad K, Gerloff C. Multimodal hyperscanning reveals that synchrony of body and mind are distinct in mother-child dyads. Neuroimage 2022; 251:118982. [PMID: 35149229 DOI: 10.1016/j.neuroimage.2022.118982] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 12/15/2021] [Accepted: 02/07/2022] [Indexed: 02/06/2023] Open
Abstract
Hyperscanning studies have begun to unravel the brain mechanisms underlying social interaction, indicating a functional role for interpersonal neural synchronization (INS), yet the mechanisms that drive INS are poorly understood. The current study, thus, addresses whether INS is functionally-distinct from synchrony in other systems - specifically the autonomic nervous system and motor behavior. To test this, we used concurrent functional near-infrared spectroscopy - electrocardiography recordings, while N = 34 mother-child and stranger-child dyads engaged in cooperative and competitive tasks. Only in the neural domain was a higher synchrony for mother-child compared to stranger-child dyads observed. Further, autonomic nervous system and neural synchrony were positively related during competition but not during cooperation. These results suggest that synchrony in different behavioral and biological systems may reflect distinct processes. Furthermore, they show that increased mother-child INS is unlikely to be explained solely by shared arousal and behavioral similarities, supporting recent theories that postulate that INS is higher in close relationships.
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Affiliation(s)
- Vanessa Reindl
- Department of Child and Adolescent Psychiatry, Child Neuropsychology Section, Psychosomatics and Psychotherapy, Medical Faculty, RWTH Aachen University, Germany; JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging, RWTH Aachen & Research Centre Juelich, Germany; Psychology, School of Social Sciences, Nanyang Technological University, Singapore S639818, Republic of Singapore.
| | - Sam Wass
- Division of Psychology, University of East London, London E16 2RD, United Kingdom
| | - Victoria Leong
- Psychology, School of Social Sciences, Nanyang Technological University, Singapore S639818, Republic of Singapore; Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom
| | - Wolfgang Scharke
- Department of Child and Adolescent Psychiatry, Child Neuropsychology Section, Psychosomatics and Psychotherapy, Medical Faculty, RWTH Aachen University, Germany; Chair of Cognitive and Experimental Psychology, Institute of Psychology, RWTH Aachen University, Germany
| | - Sandra Wistuba
- Department of Child and Adolescent Psychiatry, Child Neuropsychology Section, Psychosomatics and Psychotherapy, Medical Faculty, RWTH Aachen University, Germany
| | - Christina Lisa Wirth
- Department of Child and Adolescent Psychiatry, Child Neuropsychology Section, Psychosomatics and Psychotherapy, Medical Faculty, RWTH Aachen University, Germany
| | - Kerstin Konrad
- Department of Child and Adolescent Psychiatry, Child Neuropsychology Section, Psychosomatics and Psychotherapy, Medical Faculty, RWTH Aachen University, Germany; JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging, RWTH Aachen & Research Centre Juelich, Germany
| | - Christian Gerloff
- Department of Child and Adolescent Psychiatry, Child Neuropsychology Section, Psychosomatics and Psychotherapy, Medical Faculty, RWTH Aachen University, Germany; JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging, RWTH Aachen & Research Centre Juelich, Germany; Chair II of Mathematics, Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, Germany
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10
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Schirmer A, Fairhurst M, Hoehl S. Being 'in sync'-is interactional synchrony the key to understanding the social brain? Soc Cogn Affect Neurosci 2021; 16:1-4. [PMID: 33104804 PMCID: PMC7812616 DOI: 10.1093/scan/nsaa148] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 10/23/2020] [Indexed: 12/21/2022] Open
Abstract
The past couple of decades produced a surge of interest in interaction synchrony. Moving from the study of behavioral coordination to investigating the coordination of psychophysiological and brain activity, relevant research has tackled a broad range of interactional settings with a multitude of measurement and analysis tools. This method diversity produced a host of interesting results converging on the fact that individuals engaged in social exchange tend to temporally align external as well as internal processes. Moreover, there appears to be a reciprocal relationship between the individuals' affective bond and the extent of synchronization, which together benefit interaction outcomes. Notably, however, the current breadth of study approaches creates challenges for the field, including how to compare findings and how to develop a theoretical framework that unites and directs ongoing research efforts. More concerted efforts are called for to achieve the conceptual and methodological clarity needed to answer core questions and enabling a balanced pursuit of both synchronous and asynchronous processes.
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Affiliation(s)
- Annett Schirmer
- Department of Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR.,Brain and Mind Institute, The Chinese University of Hong Kong, Shatin, Hong Kong SAR.,Center for Cognition and Brain Studies, The Chinese University of Hong Kong, Shatin, Hong Kong SAR
| | - Merle Fairhurst
- Institute for Psychology, Bundeswehr University Munich, Munich, Germany.,Munich Center for Neuroscience, Ludwig Maximilian University, Munich, Germany
| | - Stefanie Hoehl
- Faculty of Psychology, University of Vienna, Vienna, Austria
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11
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Antonacci Y, Minati L, Faes L, Pernice R, Nollo G, Toppi J, Pietrabissa A, Astolfi L. Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators. PeerJ Comput Sci 2021; 7:e429. [PMID: 34084917 PMCID: PMC8157130 DOI: 10.7717/peerj-cs.429] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 02/15/2021] [Indexed: 05/13/2023]
Abstract
One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Square (OLS) estimation, a viable alternative is to use Artificial Neural Networks (ANNs) implemented in a simple structure with one input and one output layer and trained in a way such that the weights matrix corresponds to the matrix of VAR parameters. In this work, we introduce an ANN combined with SS models for the computation of GC. The ANN is trained through the Stochastic Gradient Descent L1 (SGD-L1) algorithm, and a cumulative penalty inspired from penalized regression is applied to the network weights to encourage sparsity. Simulating networks of coupled Gaussian systems, we show how the combination of ANNs and SGD-L1 allows to mitigate the strong reduction in accuracy of OLS identification in settings of low ratio between number of time series points and of VAR parameters. We also report how the performances in GC estimation are influenced by the number of iterations of gradient descent and by the learning rate used for training the ANN. We recommend using some specific combinations for these parameters to optimize the performance of GC estimation. Then, the performances of ANN and OLS are compared in terms of GC magnitude and statistical significance to highlight the potential of the new approach to reconstruct causal coupling strength and network topology even in challenging conditions of data paucity. The results highlight the importance of of a proper selection of regularization parameter which determines the degree of sparsity in the estimated network. Furthermore, we apply the two approaches to real data scenarios, to study the physiological network of brain and peripheral interactions in humans under different conditions of rest and mental stress, and the effects of the newly emerged concept of remote synchronization on the information exchanged in a ring of electronic oscillators. The results highlight how ANNs provide a mesoscopic description of the information exchanged in networks of multiple interacting physiological systems, preserving the most active causal interactions between cardiovascular, respiratory and brain systems. Moreover, ANNs can reconstruct the flow of directed information in a ring of oscillators whose statistical properties can be related to those of physiological networks.
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Affiliation(s)
- Yuri Antonacci
- Department of Physics and Chemistry “Emilio Segrè”, University of Palermo, Palermo, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Fondazione Santa Lucia, Rome, Italy
- Department of Computer, Control and Management Engineering “Antonio Ruberti”, University of Rome “La Sapienza”, Rome, Italy
| | - Ludovico Minati
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
- Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
| | - Luca Faes
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Riccardo Pernice
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Giandomenico Nollo
- Department of Industrial Engineering, University of Trento, Trento, Italy
| | - Jlenia Toppi
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Fondazione Santa Lucia, Rome, Italy
- Department of Computer, Control and Management Engineering “Antonio Ruberti”, University of Rome “La Sapienza”, Rome, Italy
| | - Antonio Pietrabissa
- Department of Computer, Control and Management Engineering “Antonio Ruberti”, University of Rome “La Sapienza”, Rome, Italy
| | - Laura Astolfi
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Fondazione Santa Lucia, Rome, Italy
- Department of Computer, Control and Management Engineering “Antonio Ruberti”, University of Rome “La Sapienza”, Rome, Italy
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