From social behaviour to brain synchronization: Review and perspectives in hyperscanning

Dumas, Guillaume; Lachat, Fanny; Martinerie, Jacques; Nadel, Jacqueline; George, Nathalie

doi:10.1016/j.irbm.2011.01.002

Cited by 176 publications

(124 citation statements)

References 34 publications

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“…Often, participants watch videos but do not interact with real social partners (e.g., Cochin et al, 1998;Caetano et al, 2007;Iacoboni, 2009). Recent studies have begun to examine realtime brain activity during social interactions (Makeig et al, 2002;Dumas et al, 2010Dumas et al, , 2011Konvalinka and Roepstorff, 2012). However, observational mu suppression has been studied almost exclusively using disembodied, non-social stimuli.…”

Section: Behavioral and Brain Dynamics Of Social Interactionsmentioning

confidence: 99%

EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions

Acar

Makeig

et al. 2015

NeuroImage

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Contemporary active-EEG and EEG-imaging methods show particular promise for studying the development of action planning and social-action representation in infancy and early childhood. Action-related mu suppression was measured in eleven 3-year-old children and their mothers during a 'live,' largely unscripted social interaction. High-density EEG was recorded from children and synchronized with motion-captured records of children's and mothers' hand actions, and with video recordings. Independent Component Analysis (ICA) was used to separate brain and non-brain source signals in toddlers' EEG records. EEG source dynamics were compared across three kinds of epochs: toddlers' own actions (execution), mothers' actions (observation), and between-turn intervals (no action). Mu (6-9 Hz) power was suppressed in left and right somatomotor cortex during both action execution and observation, as reflected by independent components of individual children's EEG data. These mu rhythm components were accompanied by beta-harmonic (~16 Hz) suppression, similar to findings from adults. The toddlers' power spectrum and scalp density projections provide converging evidence of adult-like musuppression features. Mu-suppression components' source locations were modeled using an age-specific 4-layer forward head model. Putative sources clustered around somatosensory cortex, near the hand/arm region. The results demonstrate that action-locked, event-related EEG dynamics can be measured, and sourceresolved, from toddlers during social interactions with relatively unrestricted social behaviors.

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Section: Behavioral and Brain Dynamics Of Social Interactionsmentioning

confidence: 99%

EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions

Acar

Makeig

et al. 2015

NeuroImage

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“…Although these “fake” social interactive tasks allow this hypothesis to be indirectly tested, recent developments in neuroimaging have allowed the creation of new techniques to be applied to fMRI (Montague et al, 2002), EEG (Astolfi et al, 2010, 2011), and NIRS (Cui et al, 2012), enabling two (and sometimes more) people to be tested at the same time. These “hyper-scanning” techniques (Dumas et al, 2011) allow ecologically valid interactions to be studied in a number of tasks, which could then also be applied to interactive learning paradigms. The clear advantage is that they allow a direct comparison of processes happening in two brains at the same time, a comparison which could otherwise only be inferred.…”

Section: Brain Imaging In Interacting Individuals: Issues and Solutionsmentioning

confidence: 99%

How relevant is social interaction in second language learning?

Verga¹,

Kotz²

2013

Front. Hum. Neurosci.

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Verbal language is the most widespread mode of human communication, and an intrinsically social activity. This claim is strengthened by evidence emerging from different fields, which clearly indicates that social interaction influences human communication, and more specifically, language learning. Indeed, research conducted with infants and children shows that interaction with a caregiver is necessary to acquire language. Further evidence on the influence of sociality on language comes from social and linguistic pathologies, in which deficits in social and linguistic abilities are tightly intertwined, as is the case for Autism, for example. However, studies on adult second language (L2) learning have been mostly focused on individualistic approaches, partly because of methodological constraints, especially of imaging methods. The question as to whether social interaction should be considered as a critical factor impacting upon adult language learning still remains underspecified. Here, we review evidence in support of the view that sociality plays a significant role in communication and language learning, in an attempt to emphasize factors that could facilitate this process in adult language learning. We suggest that sociality should be considered as a potentially influential factor in adult language learning and that future studies in this domain should explicitly target this factor.

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“…Assessing the level of between-brain neural coupling requires mea-suring brain activity for two (or more) participants involved in a social interaction, a technique called hyperscanning (brain activation is measured for both participants at the same time) or pseudo-hyperscanning (measuring brain activity for both participants in the interaction, but sequentially, one participant at a time). Since the first application of the hyperscanning method in fMRI (Montague et al, 2002), it has been applied to other neuroimaging methods as well (EEG, fNIRS and MEG) and used to investigate different aspects of social interaction (for overviews see Babiloni and Astolfi, 2014;Dumas et al, 2011;Konvalinka and Roepstorff, 2012). …”

Section: Introductionmentioning

confidence: 99%

What can we learn from a two-brain approach to verbal interaction?

Schoot

Hagoort

Segaert

2016

Neuroscience & Biobehavioral Reviews

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a b s t r a c tVerbal interaction is one of the most frequent social interactions humans encounter on a daily basis. In the current paper, we zoom in on what the multi-brain approach has contributed, and can contribute in the future, to our understanding of the neural mechanisms supporting verbal interaction. Indeed, since verbal interaction can only exist between individuals, it seems intuitive to focus analyses on interindividual neural markers, i.e. between-brain neural coupling. To date, however, there is a severe lack of theoretically-driven, testable hypotheses about what between-brain neural coupling actually reflects. In this paper, we develop a testable hypothesis in which between-pair variation in between-brain neural coupling is of key importance. Based on theoretical frameworks and empirical data, we argue that the level of between-brain neural coupling reflects speaker-listener alignment at different levels of linguistic and extra-linguistic representation. We discuss the possibility that between-brain neural coupling could inform us about the highest level of inter-speaker alignment: mutual understanding.

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From social behaviour to brain synchronization: Review and perspectives in hyperscanning

Cited by 176 publications

References 34 publications

EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions

EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions

How relevant is social interaction in second language learning?

What can we learn from a two-brain approach to verbal interaction?

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