BCIAUT-P300 dataset for autism from Simoes et al 2020
This dataset comprises EEG recordings from 15 individuals with autism spectrum disorder (ASD) participating in a P300-based brain-computer interface (BCI) study focused on joint-attention training in a virtual environment. Data were collected across 7 sessions using 8 EEG channels sampled at 250 Hz, with participants responding to visual stimuli (flashing objects) in a two-class paradigm (target vs. non-target). The dataset includes preprocessed, epoched data suitable for benchmarking BCI classification algorithms and investigating neural correlates of attention in ASD populations.
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Coming soon. Per-file data-quality summaries are precomputed by the NEMAR processing pipeline. The static aggregate is on the way — tracked at nemar-cli#511.