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BigP3BCI Study D is a P300-based brain-computer interface dataset comprising EEG recordings from 17 healthy subjects performing a 6x6 character grid speller task using dynamic row-column stimulus presentation. 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 using HED 8.4.0 schema. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset, and is designed for machine learning model development and benchmarking in brain-computer interface research.
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.
The PURSUE N170 Face Perception dataset comprises event-related potential (ERP) recordings from a face perception task conducted across three undergraduate institutions. Data were collected from participants in 2017-2018 using a standardized task design documented in the ERP CORE resource. This dataset provides a multisite contribution to open-access human electrophysiological research on face processing and the N170 component.