Multimodal mobile brain and body imaging for quantification of dance motor sequence learning

Russell W Chan; Victoria Lakomski; Johannes V R Pannermayr; Emma Wiechmann; Jan-Willem J R van 't Klooster; Willem B Verwey

doi:10.1016/j.mex.2025.103324

Multimodal mobile brain and body imaging for quantification of dance motor sequence learning

MethodsX. 2025 Apr 19:14:103324. doi: 10.1016/j.mex.2025.103324. eCollection 2025 Jun.

Authors

Russell W Chan¹, Victoria Lakomski¹, Johannes V R Pannermayr¹, Emma Wiechmann^{1

2}, Jan-Willem J R van 't Klooster¹, Willem B Verwey¹

Affiliations

¹ Faculty of Behavioural, Management and Social Sciences, Section Cognition, Data and Education, University of Twente, Enschede, Netherlands.
² Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden.

Abstract

Understanding motor learning in naturalistic settings presents a key challenge in neuroscience. While paradigms like the Discrete Sequence Production (DSP) task have advanced our knowledge, investigating more naturalistic tasks like dance with multi-limbed coordination can help further advance the understanding of complex mechanisms. It can advance motor learning by providing more profound insights into coordination dynamics, movement execution, balance, and decision-making. We have developed a modified DSP methodology that replaces keyboard pressing with dance-stepping, allowing simultaneous electroencephalography (EEG), behavioral, and kinematic recordings to quantify neurophysiological and motor dynamics. Using an E-Prime^Ⓡ script in a go/no-go approach, our method accommodates both a setup with minimal hardware and also a scalable approach with markerless motion capture and mobile EEG for neuroimaging. By leveraging Mobile Brain and Body Imaging (MOBI), we enhance the investigation of neuro-mechanisms underlying motor learning. We also discuss future directions and accessibility, including a publicly available video of the experimental procedure (https://youtu.be/zFP1rWJ2FJ8?si=DJ8q7fbfhltSLehz), enabling broader replication and application of our methodology.•Conversion of the key-press Discrete Sequence Production task to a dance version, as an applied way to investigate motor sequence learning•Multimodal investigation with motion capture and electroencephalography for kinematics and neuroimaging•Full scripts in E-Prime^Ⓡ are freely downloadable and video link showcases experiment conduct.

Keywords: 3D modelling; Centre of mass; Discrete sequence performance task; EEG; Kinematics; MoBI; Motor neuroscience; Motor sequence learning; Multimodal mobile brain and body imaging for the quantification of dance motor sequence learning.