BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)
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- Citations
- 2
- HED
- v8.4.0
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- 2.38 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
[ dataset captures intracranial neural activity from 9 participants (1,330 grid, depth, and strip electrodes) who listened to a 30-minute naturalistic story containing over 5,000 words. It includes raw recordings, a minimally preprocessed high-gamma version, the auditory stimuli, an aligned word-level transcript, and linguistic features ranging from acoustic properties to large language model embeddings. Tutorials replicating prior findings are provided to support research on natural language comprehension.
…Machine Learning Laboratory - **Address**: Machine Learning Laboratory, Berlin Institute of Technology, FR6…
Time-domain functional near-infrared spectroscopy (TD-fNIRS) recordings collected with the Kernel system to assess the reliability of brain metrics derived from this device. The dataset accompanies a Scientific Reports study evaluating the test-retest reliability of TD-fNIRS measures. It is mirrored on NEMAR from OpenNeuro (ds006545).
…Defitech Chair in Brain-Machine Interface, CNBI, Center for Neuroprosthetics - **Country**: CH…
…The absent LPC effect despite the behavioral task difference challenges existing assumptions…
This dataset contains raw EEG and transcranial magnetic stimulation (TMS) data from healthy adults, collected to test real-time, personalized brain state-dependent stimulation. Whole-brain activity patterns were decoded in real time to predict activation of the corticospinal tract, with motor evoked potentials as the outcome measure. The companion publication (Khatri, Pulliam, Manesiya, Cortez, Millán and Hussain, 'Personalized whole-brain activity patterns predict human corticospinal tract activation in real-time', Brain Stimulation, 2024) is in press and has no DOI yet.
…framework leveraging deep learning and speech synthesis. Nature Machine Intelligence 6, 467…