Investigating EEG Interbrain Synchrony: Methods to Gather Meaningful Evidence

Synchrony has been proposed as a relevant phenomenon for investigating social neurophysiological and psychological processes, with interbrain synchrony, in particular, presumed to facilitate the functional integration of multiple brains. However, the lack of an accepted definition and a cohesive theoretical corpus that allows hypothesis-based approaches, often combined with less robust empirical methods, might hinder progress in this field. To address this, we propose a definition of interbrain synchrony and link various theoretical contributions that might justify the existence of meaningful temporal alignment between different brain activities. Furthermore, we propose a set of methods aimed at minimizing bias in the collection of evidence supporting this neural mechanism. Our approach entails extracting instantaneous phase data from Hilbert-transformed EEG time series recorded from individuals under different experimental conditions that account for the synchrony's confounding factors such as shared attention, cognitive, and motor dependencies, while also relying on simulation-based insight to refine the methodological specifics. We then propose multiple data analysis strategies, including circular statistics combined with permutation testing, the sliding technique for time-lagged dependencies, and mutual information. Finally, we present an example of a potential application within the context of cooperation in nuclear families. We believe that, by employing such methods consistently, the concept of interbrain synchrony is falsifiable. Whether this phenomenon is empirically supported or not, its investigation will contribute to advancing our understanding of the social brain.