on005356
MEG: Major Depression & Probabilistic Learning Task
MEG
…Cognitive Neuroscience and Neuroimaging An MEG study (306-sensor Elekta Neuromag System…
- Participants
- 85
- Citations
- 2
- Size
- 162 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
Discover datasets
100 results for "mobile neuroimaging" · page 10 of 10 · ranked by relevance
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- nm000141
Motor execution dataset from Wairagkar et al 2018
EEG Zarr verifiedA preprocessed EEG dataset comprising motor imagery recordings from 14 healthy participants performing imagined right-hand tapping, left-hand tapping, and rest tasks. The dataset contains 1,665 trials acquired at 1024 Hz using a 19-channel montage with standard 10-20 electrode placement. Data have been preprocessed with ICA artifact removal and frequency filtering, and include annotations for motor imagery classification and brain-computer interface applications.
- Participants
- 14
- Channels
- 19 (10-20)
- Citations
- 9
- HED
- v8.4.0
- Size
- 1.23 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on002799
Human es-fMRI Resource: Concurrent deep-brain stimulation and whole-brain functional MRI
ANAT FMAP FUNC iEEGThis dataset comprises concurrent deep-brain electrical stimulation and whole-brain functional MRI data from 26 patients with medically refractory epilepsy. Patients underwent intracranial electrode implantation for clinical purposes, with one or multiple electrode contacts stimulated during fMRI acquisition using block design protocols. The resource includes anatomical imaging (T1, T2), resting-state fMRI, electrical stimulation-fMRI (es-fMRI) scans, field maps, electrode coordinates, and stimulation parameters, along with preprocessed derivatives.
- Participants
- 26
- Citations
- 8
- Size
- 176 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004012
BRAR_NQ
MEG[
- Size
- 27.8 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
- nm000167
Motor imagery dataset from Ma et al. 2020
EEG Zarr verifiedThis dataset contains 62-channel EEG recordings from 25 healthy, right-handed subjects performing kinesthetic motor imagery of the right hand versus right elbow, a within-limb discrimination paradigm. Each subject completed 15 sessions over 3 days, yielding 600 trials total, designed to study brain-computer interface (BCI) decoding of different joint movements from the same limb. The dataset supports research into motor rehabilitation and prosthetic control applications using EEG-based BCI systems.
- Participants
- 25
- Channels
- 62 (10-10)
- Citations
- 52
- HED
- v8.4.0
- Size
- 53.8 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on000117
Multisubject, multimodal face processing
ANAT BEH DWI FMAP FUNC MEG…Multi-subject, multi-modal (sMRI+fMRI+MEG+EEG) neuroimaging dataset on face…
- Participants
- 17
- Citations
- 83
- Size
- 169 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- on002725
A dataset recording joint EEG-fMRI during affective music listening
ANAT EEG FUNC[
- Size
- 15.3 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026