on004122
BCIT Speed Control
EEG
…fatigue-based performance through novel biomarkers. Similar to the Baseline Driving study…
- Participants
- 32
- Channels
- 64 (10-10)
- Citations
- 41
- HED
- v8.0.0
- Size
- 36.2 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
Discover datasets
51 results for "predictive biomarkers" · page 2 of 6 · ranked by relevance
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- on005779
Real-time personalized brain state-dependent TMS in healthy adults
EEGThis dataset contains raw EEG data from a study investigating real-time, personalized brain state-dependent transcranial magnetic stimulation (TMS) in healthy adults. The research demonstrates that personalized whole-brain activity patterns can predict human corticospinal tract activation in real-time, with potential applications for brain stimulation therapies. Data includes EEG recordings collected during TMS-guided brain state-dependent stimulation protocols, where TMS serves as the intervention guided by real-time EEG decoding.
- Participants
- 19
- Channels
- 70 (10-10)
- Citations
- 12
- Size
- 88.7 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000199
Learning from label proportions for a visual matrix speller (ERP)
EEGThis dataset comprises event-related potential (ERP) recordings from 13 healthy subjects performing a visual matrix speller task using a calibrationless brain-computer interface approach. The study introduces learning from label proportions (LLP), an unsupervised classification method that exploits known target/non-target stimulus ratios to enable online BCI operation without prior calibration. Subjects performed copy-spelling tasks using a 6×7 character grid across three sessions, achieving 84.5% character accuracy without labeled training data.
- Participants
- 13
- Channels
- 31 (10-10)
- Citations
- 46
- HED
- v8.4.0
- Size
- 5.15 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on002218
Auditory and Visual Rhythm Omission EEG
EEG…of a study of the predictive mechanisms of rhythm perception by using…
- Participants
- 18
- Channels
- 32 (10-10)
- Size
- 1.95 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000274
BEETL Competition 2021 Motor Imagery Dataset B — transfer learning benchmark
EEGBeetl2021-B is a preprocessed EEG dataset from the NeurIPS 2021 BEETL competition, focused on transfer learning for motor imagery decoding. It contains 32-channel EEG recordings from 2 healthy subjects performing a 4-class motor imagery task (left hand, right hand, feet, rest) sampled at 200 Hz. The dataset is designed to benchmark transfer learning and domain adaptation algorithms addressing cross-subject and cross-dataset generalization challenges in brain-computer interfaces.
- Participants
- 2
- Channels
- 32 (10-10)
- Citations
- 2
- HED
- v8.4.0
- Size
- 1.99 GB
- Version
- v1.0.5
- Updated
- Aug 20, 2026
- on007870
Appleseed Audiobook MEG
MEG…However, previous evidence supports two seemingly contradictory models of how a predictive…
- Participants
- 13
- Size
- 41.6 GB
- Version
- v1.0.0
- Updated
- Sep 8, 2026
- on005398
Open iEEG Dataset (Pediatric iEEG, Wayne State University and UCLA)
iEEG…Objective interictal electrophysiology biomarkers optimize prediction of epilepsy surgery outcome. Brain Commun…
- Participants
- 185
- Citations
- 14
- Size
- 165 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000200
BigP3BCI Study I — 9x8 checkerboard/performance-based (13 healthy subjects)
EEGThis dataset comprises EEG recordings from 13 healthy subjects performing a P300-based brain-computer interface task using a 9x8 checkerboard stimulus paradigm. Participants completed a single session of visual perception tasks designed for speller applications, with 16-channel EEG data sampled at 256 Hz. This derivative dataset is part of the BigP3BCI study, the largest public P300 BCI dataset containing recordings from approximately 267 subjects across multiple studies.
- Participants
- 13
- Channels
- 16 (10-10)
- HED
- v8.4.0
- Size
- 1.57 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on007020
EEG Mortality Dataset in Parkinson's Disease
EEG…This dataset can be used to explore EEG biomarkers of mortality risk…
- Participants
- 94
- Channels
- 63 (10-10)
- Citations
- 3
- Size
- 1.74 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000220
BEETL Competition 2021 Motor Imagery Dataset A — transfer learning benchmark
EEGBeetl2021-A is a preprocessed motor imagery EEG dataset derived from the BEETL Competition 2021 (NeurIPS Task 2), comprising 63-channel, 500 Hz recordings from healthy subjects performing a four-class motor imagery task (rest, left hand, right hand, feet) during an online BCI racing game (Cybathlon2020IC). The dataset was designed to benchmark transfer learning and domain adaptation methods for subject-independent, cross-dataset EEG-based brain-computer interfacing.
- Participants
- 3
- Channels
- 63 (10-10)
- Citations
- 2
- HED
- v8.4.0
- Size
- 2.17 GB
- Version
- v1.0.6
- Updated
- Aug 20, 2026