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Journal Article

Crowdsourcing neuroscience: Inter-brain coupling during face-to-face interactions outside the laboratory


Michalareas,  Giorgos
Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society;


Poeppel,  David
Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Max Planck - NYU Center for Language, Music and Emotion;
Department of Psychology, New York University;

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Dikker, S., Michalareas, G., Oostrik, M., Serafimaki, A., Kahraman, H. M., Struiksma, M. E., et al. (2021). Crowdsourcing neuroscience: Inter-brain coupling during face-to-face interactions outside the laboratory. NeuroImage, 227: 117436. doi:10.1016/j.neuroimage.2020.117436.

Cite as: https://hdl.handle.net/21.11116/0000-0005-6E0F-1
When we feel connected or engaged during social behavior, are our brains in fact “in sync” in a formal, quantifiable sense? Most studies addressing this question use highly controlled tasks with homogenous subject pools. In an effort to take a more naturalistic approach, we collaborated with art institutions to crowd-source neuroscience data: Over the course of 5 years, we collected electroencephalogram (EEG) data from thousands of museum and festival visitors who volunteered to engage in a 10-minute face-to-face interaction. Pairs of participants with various levels of familiarity sat inside the Mutual Wave Machine—an artistic Brain-Computer Interface (BCI) installation that translates real-time correlations of each pair’s EEG activity into light patterns. Because such inter-participant EEG correlations are prone to noise contamination, in subsequent offline analyses we computed inter-brain synchrony using Imaginary Coherence and Projected Power Correlations, two synchrony metrics that are largely immune to instantaneous, noise-driven correlations. When applying these methods to two subsets of recorded data with the most consistent protocols, we found that pairs’ trait empathy, social closeness, engagement, and social behavior (joint action and eye contact) consistently predicted the extent to which their brain activity became synchronized, most prominently in low alpha power (∼7-10 Hz) and beta oscillations (∼20-22 Hz). These findings support an account where shared engagement and joint action drive coupled neural activity and behavior during dynamic, naturalistic social interactions. To our knowledge, this work constitutes a first demonstration that an interdisciplinary, real-world, crowd-sourcing neuroscience approach may provide a promising method to collect large, rich datasets pertaining to real-life face-to-face interactions. Additionally, this work is a demonstration of how the general public can participate and engage in the scientific process outside of the laboratory. Institutions such as museums, galleries, or any other organization where the public actively engages out of self-motivation, can help facilitate this type of “citizen science” research, and support the collection of large datasets under scientifically controlled experimental conditions. To further enhance the public interest for this type of out-of-the-lab experimental approach, the data and results of this study are disseminated through a website tailored to the general public (wp.nyu.edu/mutualwavemachine)