Humans operate within a social context. The study of social synchronization or ‘hyperscanning’ using EEG is beginning to reveal insight into human interactions.
Humans are a remarkably social species. We live our lives within a dynamic social context where the people around us have a considerable impact on our own thoughts, emotions and actions. But despite this, the majority of neuroscientific studies to date have examined behavior and brain activity at the level of the single individual, devoid of any real-world social context.
Simultaneous EEG recordings.
As the field of Social Neuroscience has expanded over the past few decades there has been a shift in thinking and the development of new methodological approaches which allow the simultaneous measurement of brain activity from more than one individual at a time. This methodological approach, known today as hyperscanning, was first documented in the 1960s by Duane and Behrendt who used EEG to examine the “extrasensory” communication between pairs of identical twins [1]. However it wasn’t until 40 years later, in 2006, that researchers again attempted simultaneous EEG recordings [2], following in the footsteps of work conducted in the field of fMRI [3].
Since then, there has been a steady progression of EEG hyperscanning studies which have tried to understand the neural mechanisms underpinning a variety of different social behaviors. Because of the high temporal resolution of EEG, as well as its portability and use in more normal paradigms of interaction (rather than lying flat in a scanner), it is well suited to hyperscanning applications where there is a rapid, continuous and dynamic interplay between two (or more) people. Whilst some of these studies have been conducted in the lab, others have attempted to operate these hyperscanning setups within more naturalistic settings.
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Hyperscanning in the classroom.
Suzanne Dikker and colleagues from New York University measured brain synchrony in a classroom setting with 12 students who worked together on a variety of semi-naturalistic tasks [4]. One objective of the study was to determine the factors that led to greater brain synchronization between pairs of students. To do this they used the EEG metric of Total Independence which was estimated by computing the magnitude squared coherence for paired combinations of electrodes over the frequency range of 1-20 Hz. They showed that this measure of brain synchronization varied according to a number of situational variables. For example, student-to-student brain synchrony was enhanced when students engaged in 2 minutes of face to face contact prior to the test session, something that was also correlated with ratings of social closeness and suggesting the non-verbal behaviors are important mediators of brain synchrony. Furthermore, the researchers suggested that joint attention is a key factor in the neural synchrony between individuals.
See related post Factors that Impact Coherence in the EEG
From [4] Overview of the Experimental Setup
Gamma synchrony during conversation
Other studies have also used naturalistic hyperscanning setups. For example, one recent study videotaped 104 adults, who were either romantic couples or strangers, taking part in a free conversation about a positive theme, whilst their EEG was recorded [5]. Their analysis showed gamma synchrony (as shown by a correlation in spectral power between the couples/pairs) between romantic couples when conversing, but not between strangers, an effect that was localized using LORETA to temporo-parietal regions. In addition, gamma synchrony was greater during moments of social gaze between romantic couples, something not found between strangers. Their finding that the gamma synchrony was independent of the conversational content or duration again suggests that it was primarily driven by nonverbal rather than verbal aspects of the social interaction. Beyond this one example, other studies have also taken hyperscanning into a flight simulator to measure cooperative behavior between commercial pilots [6], and used it to measure the synchrony between guitarists playing a duet [7].
From [5]. Top Panel: Example of a spatial distribution of gamma power correlations in one couple dyad and one stranger dyad over the entire scalp. Bottom Panel: Dyadic Correlation Spectral analysis.
Methodological challenges and future opportunities
The progress being made with EEG hyperscanning is opening up an exciting new avenue for researching the social behaviors which define so much of our daily life. However these studies are also revealing the methodological challenges that come with employing such a complex setup, the most basic of which is making sure that the synchronization observed isn’t simply because the individuals have simultaneously experienced the same stimuli [8]. Beyond this it also raises questions about the best ways for measuring and analyzing brain synchrony between individuals: What tasks should be used? What analysis techniques are the most appropriate? How do you interpret the different forms of synchronous activity observed?
As this field continues to grow and more studies are added into the mix, the answers to these, and other questions, will start to become clearer. In addition, consistent findings across multiple studies will hopefully start to emerge, contributing to our understanding of social concepts such as empathy and collaboration as well as helping us to understand, from a mental health perspective, why some people find it difficult to connect with others, or fail to form close attachments with family or friends.
References:
[1] Duane, T., & Behrendt, T. (1965). Extrasensory Electroencephalographic Induction between Identical Twins. Science, 150(3694), 367-367. doi: 10.1126/science.150.3694.367
[2] Babiloni, F., Cincotti, F., Mattia, D., Mattiocco, M., De Vico Fallani, F., & Tocci, A. et al. (2006). Hypermethods for EEG hyperscanning. 2006 International Conference Of The IEEE Engineering In Medicine And Biology Society. doi: 10.1109/iembs.2006.260754
[3] Montague, P. (2002). Hyperscanning: Simultaneous fMRI during Linked Social Interactions. Neuroimage, 16(4), 1159-1164. doi: 10.1006/nimg.2002.1150
[4] Dikker, S., Wan, L., Davidesco, I., Kaggen, L., Oostrik, M., & McClintock, J. et al. (2017). Brain-to-Brain Synchrony Tracks Real-World Dynamic Group Interactions in the Classroom. Current Biology, 27(9), 1375-1380. doi: 10.1016/j.cub.2017.04.002
[5] Kinreich, S., Djalovski, A., Kraus, L., Louzoun, Y., & Feldman, R. (2017). Brain-to-Brain Synchrony during Naturalistic Social Interactions. Scientific Reports, 7(1). doi: 10.1038/s41598-017-17339-5
[6] Toppi, J., Borghini, G., Petti, M., He, E., De Giusti, V., & He, B. et al. (2016). Investigating Cooperative Behavior in Ecological Settings: An EEG Hyperscanning Study. PLOS ONE, 11(4), e0154236. doi: 10.1371/journal.pone.0154236
[7] Sänger, J., Müller, V., & Lindenberger, U. (2012). Intra- and interbrain synchronization and network properties when playing guitar in duets. Frontiers In Human Neuroscience, 6. doi: 10.3389/fnhum.2012.00312
[8] Burgess, A. (2013). On the interpretation of synchronization in EEG hyperscanning studies: a cautionary note. Frontiers In Human Neuroscience, 7. doi: 10.3389/fnhum.2013.00881
