EEG of the Dancing Brain: Decoding Sensory, Motor, and Social Processes during Dyadic Dance

Area of Science:

• Neuroscience
• Cognitive Science
• Social Interaction

Background:

• Real-world social cognition involves processing multiple dynamic information streams.
• Interpreting neural activity during natural social interactions is a significant challenge.
• Advancements in denoising and multivariate modeling offer new approaches.

Purpose of the Study:

• To extract interpretable electroencephalography (EEG) signals from spontaneous dyadic dance.
• To investigate the unique contributions of music, self-kinematics, other-kinematics, and social coordination to neural activity.
• To identify neural markers of social coordination during dyadic interaction.

Main Methods:

• Utilized multivariate temporal response functions (mTRFs) to analyze EEG data.
• Modeled electromyogram (EMG) recordings to control for artifacts.
• Employed data-driven kinematic decomposition to analyze movement patterns.

Main Results:

• Successfully disentangled neural signals for auditory tracking, self-movement control, partner movement observation, and social coordination.
• Identified specific event-related potentials (ERPs) for auditory and motor processes.
• Discovered a novel neural marker for social coordination, driven by spatiotemporal alignment and partner observation, particularly vertical bounce movements.

Conclusions:

• Real-world neuroimaging combined with multivariate modeling can reveal mechanisms of complex social behaviors.
• A unique neural marker for social coordination was identified during dyadic dance.
• Neural activity reflects auditory, motor, and social processing during naturalistic interaction.