Healthy Brain Network EEG - Not for Commercial Use
NEMAR Dataset nm000103: HBN-EEG NC - Healthy Brain Network EEG data
- Size
- 250 GB
- Updated
- May 16, 2026
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NEMAR Dataset nm000103: HBN-EEG NC - Healthy Brain Network EEG data
A multi-session EEG dataset acquired from 15 healthy participants performing resting state and graded cognitive tasks (MATB-II at three difficulty levels). The dataset comprises 62-channel EEG recordings at 500 Hz sampling rate designed for passive brain-computer interface applications and mental workload estimation in neuroergonomic contexts. Raw EEG data are provided with standardized event annotations using HED 8.4.0 schema and MOABB-compatible feature extraction pipelines (bandpower analysis and Riemannian covariance methods) for benchmarking purposes.
This dataset comprises multi-session, multi-task EEG recordings from 15 healthy participants performing resting state and graded difficulty levels of the MATB-II task. Acquired at 500 Hz using 62 active electrodes, the dataset includes 90 trials per participant across two sessions and is designed to support passive brain-computer interface applications and mental workload estimation in neuroergonomic contexts. The dataset is in raw, unpreprocessed state and has been formatted according to BIDS standards for accessibility and reproducibility.
A motor imagery EEG dataset comprising 31 healthy participants performing left and right hand grasping imagery tasks across multiple sessions. The dataset includes 2,520 trials recorded at 1000 Hz using a 64-channel Neuroscan system with standardized electrode montage, designed for brain-computer interface research and motor control applications.
BigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, annotated with target and non-target event labels for machine learning applications. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.
Imported from OpenNeuro ds005515