by Janet Kwazniak
A couple of years back I looked at a paper by G. Dumas etal. (here) and was impressed. Recently he commented on a posting. This prompted me to look at the recent work of the group. They have developed a method that allows them to look at the interaction between two brains in communication and advance from individual to social theories of cognition.
Two people communicate with hand movements via a video link and at the same time EEG traces are collected from both. This really is measurement of synchrony in social interaction.
Towards a two-body neuroscience (see citation) gives a good description of the method.
Our findings result from the close collaboration between experts who study neural dynamics and developmental psychology… A new technique called hyperscanning has made it possible to study the neural activity of two individuals simultaneously. However, this advanced methodology was not sufficient in itself. What remained to be found was a way to promote real-time reciprocal social interaction between two individuals during brain recording and analyze the neural and behavioral phenomenon from an inter-individual perspective. Approaches used in infancy research to study nonverbal communication and coordination, between a mother and her child for example, have so far been poorly applied to neuroimaging experiments. We thus adapted an ecological two-body experiment inspired by the use of spontaneous imitation in preverbal infants. Numerous methodological and theoretical problems had to be overcome, ranging from the choice of a common time-unit for behavioral and brain recordings to the creation of algorithms for data processing between distant brain regions in different brains.
Currently, the integration, coordination and sharing of information by brain areas is thought to be do to neural phase synchronization. In other words, information processing relies on oscillations.
The Phase Locking Value (PLV) is a practical method for the quantification of neural synchronization between two neuroelectric signals in a specific frequency band. The fact that the perception-action loops of the two participants were intertwined in our experiment leads us to hypothesize that neural synchronizations, as measured by PLV, may exist between their two brains during periods in which the two subjects imitated one another reciprocally. Rather than using the classical PLV used to measure synchrony in the individual brain, we measured synchrony between two separated brains using a hyper-phase locking value (h-PLV). What can this h-PLV measure?
Both sensory (visual motion) and motor (hand velocity) cause oscillatory activities and this low-level sensory-motor information is being communicated.
Thus, the h-PLV could reflect information being dynamically shared through an interindividual sensory-motor loop. These loops emerge from a bi-directional coupling between the participants, with the behavior of each one influencing the other’s behavior, and inter-brain synchronizations reflecting their perception-action entanglement.
So what has this methodology produced so far. Here are the abstracts of three of the group’s papers (see citations):
Inter-Brain Synchronization during Social Interaction
During social interaction, both participants are continuously active, each modifying their own actions in response to the continuously changing actions of the partner. This continuous mutual adaptation results in interactional synchrony to which both members contribute. Freely exchanging the role of imitator and model is a well-framed example of interactional synchrony resulting from a mutual behavioral negotiation. How the participants’ brain activity underlies this process is currently a question that hyperscanning recordings allow us to explore. In particular, it remains largely unknown to what extent oscillatory synchronization could emerge between two brains during social interaction. To explore this issue, 18 participants paired as 9 dyads were recorded with dual-video and dual-EEG setups while they were engaged in spontaneous imitation of hand movements. We measured interactional synchrony and the turn-taking between model and imitator. We discovered by the use of nonlinear techniques that states of interactional synchrony correlate with the emergence of an interbrain synchronizing network in the alpha-mu band between the right centroparietal regions. These regions have been suggested to play a pivotal role in social interaction. Here, they acted symmetrically as key functional hubs in the interindividual brainweb. Additionally, neural synchronization became asymmetrical in the higher frequency bands possibly reflecting a top-down modulation of the roles of model and imitator in the ongoing interaction.
Does the brain know who is at the origin of what in an imitative interaction?
Brain correlates of the sense of agency have recently received increased attention. However, the explorations remain largely restricted to the study of brains in isolation. The prototypical paradigm used so far consists of manipulating visual perception of own action while asking the subject to draw a distinction between self- versus externally caused action. However, the recent definition of agency as a multifactorial phenomenon combining bottom-up and top-down processes suggests the exploration of more complex situations. Notably there is a need of accounting for the dynamics of agency in a two-body context where we often experience the double faceted question of who is at the origin of what in an ongoing interaction. In a dyadic context of role switching indeed, each partner can feel body ownership, share a sense of agency and altogether alternate an ascription of the primacy of action to self and to other. To explore the brain correlates of these different aspects of agency, we recorded with dual EEG and video set-ups 22 subjects interacting via spontaneous versus induced imitation (II) of hand movements. The differences between the two conditions lie in the fact that the roles are either externally attributed (induced condition) or result from a negotiation between subjects (spontaneous condition). Results demonstrate dissociations between self- and other-ascription of action primacy in delta, alpha and beta frequency bands during the condition of II. By contrast a similar increase in the low gamma frequency band (38–47 Hz) was observed over the centro-parietal regions for the two roles in spontaneous imitation (SI). Taken together, the results highlight the different brain correlates of agency at play during live interactions.
Anatomical Connectivity Influences both Intra- and Inter- Brain Synchronizations
Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.
(I asked G. Dumas to comment on this post and point out where I may have given the wrong impression of the work. He kindly sent this comment and I am adding it here in the main posting - with a thank you to him.)
1. Since there are lot of other groups using hyperscanning, I will advise you to emphasize the real-time and reciprocal dimensions here. I think notably at the title where people could believe I have developed hyperscanning although it is not the case (for fMRI it’s Montague and for EEG it’s Babiloni).
2. Instead of saying “coordination and sharing of information by brain areas is thought to be do to neural phase synchronization.” I would be less speculative and mentioned that “phase synchronization has been proved to play a role in the integration of neural information between distributed areas”. It is proposed as one of the mechanisms at play for brain coordination, but others are also potentially implicated (active de-synchornization is for instance as much important).
3. The last abstract quoted is a neurocomputational work which uses past experimental data as matter of comparison. The goal here is slightly different since it tends to supports the extension of existing computational approaches to the two-body level, and meanwhile describes how the human connectome structure constrains intra-individual and inter-individual neural dynamics. At the intra-individual level, it show for instance how the peak of the alpha rhythm could be linked to the connectome size and the conduction of neural pathways. At the inter-individual level, it seems that the structural similarity could play a role in the dynamical similarity. This open new venues for approaching social disorders such as autism and schizophrenia where the anatomical structure seems globally changed.
Dumas, G. (2011). Towards a two-body neuroscience Communicative & Integrative Biology, 4 (3), 349-352 DOI: 10.4161/cib.4.3.15110
Dumas, G., Nadel, J., Soussignan, R., Martinerie, J., & Garnero, L. (2010). Inter-Brain Synchronization during Social Interaction PLoS ONE, 5 (8) DOI: 10.1371/journal.pone.0012166
Dumas, G., Martinerie, J., Soussignan, R., & Nadel, J. (2012). Does the brain know who is at the origin of what in an imitative interaction? Frontiers in Human Neuroscience, 6 DOI: 10.3389/fnhum.2012.00128
Dumas, G., Chavez, M., Nadel, J., & Martinerie, J. (2012). Anatomical Connectivity Influences both Intra- and Inter-Brain Synchronizations PLoS ONE, 7 (5) DOI: 10.1371/journal.pone.0036414