on007137
PURSUE N2pc Visual Search
EEG
[
- Size
- 12.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "independent component analysis" · page 6 of 10 · ranked by relevance
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- nm000212
BNCI 2015-007 Motion VEP (mVEP) Speller dataset
EEG…gaze-independent communication - **Feedback type**: visual - **Stimulus type**: motion VEP (mVEP) - **Stimulus…
- Participants
- 16
- Channels
- 63 (10-10)
- Citations
- 44
- HED
- v8.4.0
- Size
- 3.79 GB
- Version
- v1.0.2
- Updated
- Aug 18, 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
- on002336
A multi-modal human neuroimaging dataset for data integration: simultaneous EEG and fMRI acquisition during a motor imagery neurofeedback task: XP1
ANAT EEG FUNCThis dataset comprises simultaneous EEG and fMRI recordings from 10 subjects performing motor imagery and neurofeedback tasks. Participants completed six runs including motor localization, pre- and post-neurofeedback motor imagery, and three neurofeedback conditions (bimodal EEG-fMRI, unimodal EEG, and unimodal fMRI). The dataset provides both raw and preprocessed EEG data (64 channels at 5 kHz), structural and functional MRI data (3T Siemens, 2×2×4 mm³ resolution), and computed neurofeedback scores, enabling multi-modal neuroimaging data integration studies.
- Participants
- 10
- Size
- 18.0 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000219
BNCI 2020-002 Attention Shift (Covert Spatial Attention) dataset
EEG…features, N2pc, canonical correlation analysis, gaze-independent, BCI ## References Reichert, C., Tellez…
- Participants
- 18
- Channels
- 30 (10-10)
- Citations
- 26
- HED
- v8.4.0
- Size
- 1.82 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on004118
BCIT Calibration Driving
EEG…Calibration data sets were designed to be the first component of every…
- Participants
- 156
- Channels
- 64 (10-10)
- Citations
- 29
- HED
- v8.0.0
- Size
- 124 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004078
A synchronized multimodal neuroimaging dataset to study brain language processing
ANAT DWI FUNC MEG…And then the independent component analysis (ICA) method was applied to remove…
- Participants
- 12
- Citations
- 6
- Size
- 1.36 TB
- Version
- v1.0.0
- Updated
- Jul 22, 2026
- on007554
Multimodal dataset from the CMx7-MM Experiment
BEH EEG NIRSThis dataset comprises raw multimodal recordings from 30 healthy right-handed adults performing a hierarchy of cognitive, motor, and combined cognitive-motor tasks across three sessions. Data include EEG, fNIRS, ECG, EMG, torque/kinematic, behavioral (push-button), and subjective (sleepiness, cognitive load) measures, organized according to the BIDS standard. The dataset supports research into neurophysiological correlates of cognitive-motor interactions and dual-task performance.
- Participants
- 30
- Channels
- 32 (10-10)
- Citations
- 1
- Size
- 4.21 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- on003947
EEG: First Episode Psychosis vs. Control Resting Task 2
EEG…data was gathered for two independently collected samples of healthy and First…
- Participants
- 61
- Channels
- 61 (10-10)
- Citations
- 10
- Size
- 12.5 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on002814
A Multimodal Neuroimaging Dataset to Study Spatiotemporal Dynamics of Visual Processing in Humans
ANAT EEG FUNCA multimodal neuroimaging dataset designed to investigate the spatiotemporal dynamics of visual processing in humans. The dataset combines multiple neuroimaging modalities—electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and structural MRI—to characterize neural responses during visual tasks. This comprehensive resource provides simultaneous EEG-fMRI recordings that enable investigation of the temporal and spatial organization of visual cortical processing, bridging the high temporal resolution of EEG with the high spatial resolution of fMRI.
- Participants
- 21
- Size
- 48.6 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026