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

Title:
EEG of the Dancing Brain: Decoding Sensory, Motor, and Social Processes during Dyadic Dance.
Source:
Journal of Neuroscience; 5/21/2025, Vol. 45 Issue 21, p1-15, 15p
Database:
Complementary Index

Weitere Informationen

Real-world social cognition requires processing and adapting to multiple dynamic information streams. Interpreting neural activity in such ecological conditions remains a key challenge for neuroscience. This study leverages advancements in denoising techniques and multivariatemodeling to extract interpretable EEGsignals frompairs of (male and/or female) participants engaged in spontaneous dyadic dance. Using multivariate temporal response functions (mTRFs), we investigated how music acoustics, self-generated kinematics, othergenerated kinematics, and social coordination uniquely contributed to EEG activity. Electromyogram recordings from ocular, face, and neckmuscleswere alsomodeled to control for artifacts. ThemTRFs effectively disentangled neural signals associatedwith four processes: (I) auditory tracking of music, (II) control of self-generated movements, (III) visual monitoring of partner movements, and (IV) visual tracking of social coordination. We show that the first three neural signals are driven by event-related potentials: the P50-N100-P200 triggered by acoustic events, the central lateralizedmovement-related cortical potentials triggered bymovement initiation, and the occipital N170 triggered by movement observation. Notably, the (previously unknown) neuralmarker of social coordination encodes the spatiotemporal alignment between dancers, surpassing the encoding of self- or partner-related kinematics taken alone. This marker emerges when partners can see each other, exhibits a topographical distribution over occipital areas, and is specifically driven by movement observation rather than initiation. Using data-driven kinematic decomposition, we further show that vertical bounce movements best drive observers' EEG activity. These findings highlight the potential of real-world neuroimaging, combined with multivariate modeling, to uncover the mechanisms underlying complex yet natural social behaviors. [ABSTRACT FROM AUTHOR]

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