Name:Félix, Bigand

School/Affiliation:Italian Institute of Technology, Rome, Italy.

Co-Authors:Roberta, Bianco; Sara, Abalde; Trinh, Nguyen; Giacomo, Novembre

Virtual or In-person:In-person

Abstract:

Though dance is a universal form of human expression, the brain mechanisms supporting it are still poorly understood. The neuroscientific study of naturalistic dance is challenging due to its inherent complexity, involving social interaction and multimodal processes. To address this challenge, we applied multivariate temporal response functions (mTRFs) to electroencephalography (EEG) and full-body kinematics data collected from pairs of participants engaging in spontaneous dance to music. Using TRF encoding models, we were able to separate EEG modulations specifically associated with various aspects of dance: (i) music acoustics, (ii) self-generated movements, (iii) other-generated movements, and notably even (iv) interpersonal synchrony. Each model revealed distinct brain responses significantly contributing to EEG activity, elucidating the intricate neural encoding of collective dance. Our findings demonstrate the effectiveness of mTRFs in disentangling the simultaneous yet distinct neural processes involved in complex naturalistic interactions like dyadic dance. This paves the way for further research integrating hyperscanning techniques and kinematic analyses to deepen our understanding of the neuroscience of dance.