EEG hyperscanning : influence of the haptic channel on inter-brain synchrony

When pairs of participants work together, an exchange of information is possible through different modalities (visual, auditory...). These sensory channels of information transmission support communication, making it more efficient. Although the influence of the visual and auditory modalities have been widely described, the role of kinesthetic cues in the interaction between two participants remains little studied. Our current study aims to fill this gap and proposes to inspect the influence of the physical link, which translates into an exchange of haptic information, in the effectiveness of dyadic collaboration. To this end, pairs of individuals will be subjected to collaborative movement tasks by means of a robotic system allowing an exchange of haptic information only. We rely on measures of brain synchronization between two individuals, an emerging metric in the field of interaction neuroscience, and established to be related to the quality of collaboration. (1) To evaluate inter-brain synchronization, we use a method called hyperscanning, in which the electroencephalograms of two participants are measured simultaneously, and we compute connectivity indices from their brain signals. In addition, we propose to assess the sense of joint agency, defined as a conscious sensation of acting jointly/having joint control in an action, which is informative of collaboration quality. (2) A better understanding of the mechanisms by which collaboration emerges and can be optimized will inform models applicable to automatic devices. Expected role of the intern : During this internship, the student will actively contribute to this ongoing research project by supporting a PhD student in the collection, analysis, and interpretation of EEG hyperscanning data. The internship will be structured around the following key phases: - Conducting a literature review on inter-brain synchrony and sensorimotor communication - Participating in EEG hyperscanning experiments for data acquisition - Analyzing EEG data using Python While prior experience in EEG data collection, robotics, or programming is appreciated, it is not a prerequisite. Above all, curiosity, enthusiasm, and a strong motivation to learn are considered essential for this role. Interested candidates should send an email to : guillemet@isir.upmc.fr (1) Redcay, E., & Schilbach, L. (2019). Using second-person neuroscience to elucidate the mechanisms of social interaction. Nature Reviews Neuroscience, 20(8), 495–505. (2) Engel, C., Riek, S., & van der Weiden, H. (2022). The sense of agency in joint action: An integrative review. Neuroscience & Biobehavioral Reviews, 29(2), 1089–1117.