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Zhang M, Yin Z, Zhang X, Zhang H, Bao M, Xuan B. Neural mechanisms distinguishing two types of cooperative problem-solving approaches: An fNIRS hyperscanning study. Neuroimage 2024; 291:120587. [PMID: 38548038 DOI: 10.1016/j.neuroimage.2024.120587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 03/18/2024] [Accepted: 03/25/2024] [Indexed: 04/13/2024] Open
Abstract
Collaborative cooperation (CC) and division of labor cooperation (DLC) are two prevalent forms of cooperative problem-solving approaches in daily life. Despite extensive research on the neural mechanisms underlying cooperative problem-solving approaches, a notable gap exists between the neural processes that support CC and DLC. The present study utilized a functional near-infrared spectroscopy (fNIRS) hyperscanning technique along with a classic cooperative tangram puzzle task to investigate the neural mechanisms engaged by both friends and stranger dyads during CC versus DLC. The key findings of this study were as follows: (1) Dyads exhibited superior behavioral performance in the DLC task than in the CC task. The CC task bolstered intra-brain functional connectivity and inter-brain synchrony (IBS) in regions linked to the mirror neuron system (MNS), spatial perception (SP) and cognitive control. (2) Friend dyads showed stronger IBS in brain regions associated with the MNS than stranger dyads. (3) Perspective-taking predicted not only dyads' behavioral performance in the CC task but also their IBS in brain regions associated with SP during the DLC task. Taken together, these findings elucidate the divergent behavioral performance and neural connection patterns between the two cooperative problem-solving approaches. This study provides novel insights into the various neurocognitive processes underlying flexible coordination strategies in real-world cooperative contexts.
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Affiliation(s)
- Mingming Zhang
- School of Psychology, Shanghai Normal University, 100, Guilin Road, Shanghai 200234, China
| | - Zijun Yin
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Xue Zhang
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Hui Zhang
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Mingjing Bao
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Bin Xuan
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China.
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Chuang TM, Peng PC, Su YK, Lin SH, Tseng YL. Exploring Inter-Brain Electroencephalogram Patterns for Social Cognitive Assessment During Jigsaw Puzzle Solving. IEEE Trans Neural Syst Rehabil Eng 2024; 32:422-430. [PMID: 38198273 DOI: 10.1109/tnsre.2024.3352036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2024]
Abstract
Social interaction enables the smooth progression of our daily lives. Mounting evidence from recent hyperscanning neuroimaging studies indicates that key components of social behavior can be evaluated using inter-brain oscillations and connectivity. However, mapping out inter-brain networks and developing neurocognitive theories that explain how humans co-create and share information during social interaction remains challenging. In this study, we developed a jigsaw puzzle-solving game with hyperscanning electroencephalography (EEG) signals recorded to investigate inter-brain activities during social interactions involving cooperation and competition. Participants were recruited and paired into dyads to participate in the multiplayer jigsaw puzzle game with 32-channel EEG signals recorded. The corresponding event-related potentials (ERPs), brain oscillations, and inter-brain functional connectivity were analyzed. The results showed different ERP morphologies of P3 patterns in competitive and cooperative contexts, and brain oscillations in the low-frequency band may be an indicator of social cognitive activities. Furthermore, increased inter-brain functional connectivity in the delta, theta, alpha, and beta frequency bands was observed in the competition mode compared to the cooperation mode. By presenting comparable and valid hyperscanning EEG results alongside those of previous studies using traditional paradigms, this study demonstrates the potential of utilizing hyperscanning techniques in real-life game-playing scenarios to quantitatively assess social cognitive interactions involving cooperation and competition. Our approach offers a promising platform with potential applications in the flexible assessment of psychiatric disorders related to social functioning.
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Li X, Jin M, Zhang N, Hongman W, Fu L, Qi Q. Neural correlates of fine motor grasping skills: Longitudinal insights into motor cortex activation using fNIRS. Brain Behav 2024; 14:e3383. [PMID: 38376039 PMCID: PMC10784192 DOI: 10.1002/brb3.3383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/01/2023] [Accepted: 12/20/2023] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND Motor learning is essential for performing specific tasks and progresses through distinct stages, including the rapid learning phase (initial skill acquisition), the consolidation phase (skill refinement), and the stable performance phase (skill mastery and maintenance). Understanding the cortical activation dynamics during these stages can guide targeted rehabilitation interventions. METHODS In this longitudinal randomized controlled trial, functional near-infrared spectroscopy was used to explore the temporal dynamics of cortical activation in hand-related motor learning. Thirty-one healthy right-handed individuals were randomly assigned to perform either easy or intricate motor tasks with their non-dominant hand over 10 days. We conducted 10 monitoring sessions to track cortical activation in the right hemisphere (according to lateralization principles, the primary hemisphere for motor control) and evaluated motor proficiency concurrently. RESULTS The study delineated three stages of nondominant hand motor learning: rapid learning (days 1 and 2), consolidation (days 3-7), and stable performance (days 8-10). There was a power-law enhancement of motor skills correlated with learning progression. Sustained activation was observed in the supplementary motor area (SMA) and parietal lobe (PL), whereas activation in the right primary motor cortex (M1R) and dorsolateral prefrontal cortex (PFCR) decreased. These cortical activation patterns exhibited a high correlation with the augmentation of motor proficiency. CONCLUSIONS The findings suggest that early rehabilitation interventions, such as transcranial magnetic stimulation and transcranial direct current stimulation (tDCS), could be optimally directed at M1 and PFC in the initial stages. In contrast, SMA and PL can be targeted throughout the motor learning process. This research illuminates the path for developing tailored motor rehabilitation interventions based on specific stages of motor learning. NEW AND NOTEWORTHY In an innovative approach, our study uniquely combines a longitudinal design with the robustness of generalized estimating equations (GEEs). With the synergy of functional near-infrared spectroscopy (fNIRS) and the Minnesota Manual Dexterity Test (MMDT) paradigm, we precisely trace the evolution of neural resources during complex, real-world fine-motor task learning. Centering on right-handed participants using their nondominant hand magnifies the intricacies of right hemisphere spatial motor processing. We unravel the brain's dynamic response throughout motor learning stages and its potent link to motor skill enhancement. Significantly, our data point toward the early-phase rehabilitation potential of TMS and transcranial direct current stimulation on the M1 and PFC regions. Concurrently, SMA and PL appear poised to benefit from ongoing interventions during the entire learning curve. Our findings carve a path for refined motor rehabilitation strategies, underscoring the importance of timely noninvasive brain stimulation treatments.
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Affiliation(s)
- Xiaoli Li
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center)ShanghaiChina
| | - Minxia Jin
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center)ShanghaiChina
| | - Nan Zhang
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center)ShanghaiChina
| | - Wei Hongman
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center)ShanghaiChina
| | - LianHui Fu
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center)ShanghaiChina
| | - Qi Qi
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center)ShanghaiChina
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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: 0] [Impact Index Per Article: 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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Chatterjee I, Goršič M, Hossain MS, Clapp JD, Novak VD. Automated Classification of Dyadic Conversation Scenarios using Autonomic Nervous System Responses. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 2023; 14:3388-3395. [PMID: 38107015 PMCID: PMC10721131 DOI: 10.1109/taffc.2023.3236265] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Two people's physiological responses become more similar as those people talk or cooperate, a phenomenon called physiological synchrony. The degree of synchrony correlates with conversation engagement and cooperation quality, and could thus be used to characterize interpersonal interaction. In this study, we used a combination of physiological synchrony metrics and pattern recognition algorithms to automatically classify four different dyadic conversation scenarios: two-sided positive conversation, two-sided negative conversation, and two one-sided scenarios. Heart rate, skin conductance, respiration and peripheral skin temperature were measured from 16 dyads in all four scenarios, and individual as well as synchrony features were extracted from them. A two-stage classifier based on stepwise feature selection and linear discriminant analysis achieved a four-class classification accuracy of 75.0% in leave-dyad-out crossvalidation. Removing synchrony features reduced accuracy to 65.6%, indicating that synchrony is informative. In the future, such classification algorithms may be used to, e.g., provide real-time feedback about conversation mood to participants, with applications in areas such as mental health counseling and education. The approach may also generalize to group scenarios and adjacent areas such as cooperation and competition.
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Affiliation(s)
| | - Maja Goršič
- University of Cincinnati, Cincinnati, OH 45221
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Balters S, Miller JG, Li R, Hawthorne G, Reiss AL. Virtual (Zoom) Interactions Alter Conversational Behavior and Interbrain Coherence. J Neurosci 2023; 43:2568-2578. [PMID: 36868852 PMCID: PMC10082458 DOI: 10.1523/jneurosci.1401-22.2023] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 01/10/2023] [Accepted: 01/14/2023] [Indexed: 03/05/2023] Open
Abstract
A growing number of social interactions are taking place virtually on videoconferencing platforms. Here, we explore potential effects of virtual interactions on observed behavior, subjective experience, and neural "single-brain" and "interbrain" activity via functional near-infrared spectroscopy neuroimaging. We scanned a total of 36 human dyads (72 participants, 36 males, 36 females) who engaged in three naturalistic tasks (i.e., problem-solving, creative-innovation, socio-emotional task) in either an in-person or virtual (Zoom) condition. We also coded cooperative behavior from audio recordings. We observed reduced conversational turn-taking behavior during the virtual condition. Given that conversational turn-taking was associated with other metrics of positive social interaction (e.g., subjective cooperation and task performance), this measure may be an indicator of prosocial interaction. In addition, we observed altered patterns of averaged and dynamic interbrain coherence in virtual interactions. Interbrain coherence patterns that were characteristic of the virtual condition were associated with reduced conversational turn-taking. These insights can inform the design and engineering of the next generation of videoconferencing technology.SIGNIFICANCE STATEMENT Videoconferencing has become an integral part of our lives. Whether this technology impacts behavior and neurobiology is not well understood. We explored potential effects of virtual interaction on social behavior, brain activity, and interbrain coupling. We found that virtual interactions were characterized by patterns of interbrain coupling that were negatively implicated in cooperation. Our findings are consistent with the perspective that videoconferencing technology adversely affects individuals and dyads during social interaction. As virtual interactions become even more necessary, improving the design of videoconferencing technology will be crucial for supporting effective communication.
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Affiliation(s)
- Stephanie Balters
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305
| | - Jonas G Miller
- Department of Psychology, Stanford University, Stanford, California 94305
| | - Rihui Li
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305
| | - Grace Hawthorne
- Department of Mechanical Engineering, Stanford University, Stanford, California 94305
| | - Allan L Reiss
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305
- Department of Pediatrics, Stanford University, Stanford, California 94305
- Department of Radiology, Stanford University, Stanford, California 94305
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