Large-scale fMRI dataset for the design of motor-based Brain-Computer Interfaces
Publication date
2025-05-16
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Abstract
Functional Magnetic Resonance Imaging (fMRI) data is commonly used to map sensorimotor cortical organization and to localise electrode target sites for implanted Brain-Computer Interfaces (BCIs). Functional data recorded during motor and somatosensory tasks from both adults and children specifically designed to map and localise BCI target areas throughout the lifespan is rare. Here, we describe a large-scale dataset collected from 155 human participants while they performed motor and somatosensory tasks involving the fingers, hands, arms, feet, legs, and mouth region. The dataset includes data from both adults and children (age range: 6–89 years) performing a set of standardized tasks. This dataset is particularly relevant to study developmental patterns in motor representation on the cortical surface and for the design of paediatric motor-based implanted BCIs.
Keywords
Statistics and Probability, Information Systems, Education, Computer Science Applications, Statistics, Probability and Uncertainty, Library and Information Sciences
Citation
Bom, M S, Brak, A M A, Raemaekers, M, Ramsey, N F, Vansteensel, M J & Branco, M P 2025, 'Large-scale fMRI dataset for the design of motor-based Brain-Computer Interfaces', Scientific data, vol. 12, no. 1, 804. https://doi.org/10.1038/s41597-025-05134-1