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arXiv · 2603.22933

An Open-Access Multi-modal Dataset for Cognitive, Motor, and Cognitive-Motor Tasks

Zaineb Ajra·Grégoire Vergotte·Stéphane Perrey·Lilian Evra·Simon Pla·Gérard Dray·Jacky Montmain·Binbin Xu
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Abstract

The incorporation of neuroimaging techniques such as electroenchephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has provided new opportunities for the analysis of dynamic brain processes involved in cognitive and motor functions. Despite the great contribution of the open-access neuroimaging datasets to neuroscience studies, they have mainly remained on a single modality and isolated task paradigms performed in a controlled environments. These limitations restrict the analysis of multi-task effects in real-world applications, thus creating a gap in the understanding of how cognitive and motor processes interact in daily life activities. To address these limitations, we present a multi-modal dataset containing neurophysiological (EEG, fNIRS), physiological (ECG), behavioral, and subjective measures collected from 30 healthy participants over three sessions. This dataset includes a hierarchical series of seven tasks ranging from single cognitive and motor activities, such as N-back, motor, passive motor, mental arithmetic and motor imagery, to combined cognitive-motor interactions simulating real life scenarios. This raw dataset provides a resource for developing advanced preprocessing methods and analysis pipelines, with potential applications in brain-computer interfaces, neurorehabilitation, and other fields requiring an understanding of multi-tasks brain dynamics. https://doi.org/10.18112/openneuro.ds007554.v1.0.0

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Zaineb Ajra, Grégoire Vergotte, Stéphane Perrey, Lilian Evra, Simon Pla, Gérard Dray, Jacky Montmain, Binbin Xu. 2026-03-24. An Open-Access Multi-modal Dataset for Cognitive, Motor, and Cognitive-Motor Tasks. https://arxiv.org/abs/2603.22933

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