{"dataset":{"id":"230","dataset_id":"nm000197","name":"BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)","description":"This derivative dataset comprises EEG recordings from 21 ALS subjects participating in the BigP3BCI Study M, a P300-based brain-computer interface experiment using a 9x8 adaptive/checkerboard visual speller paradigm. The data were acquired at 256 Hz using 16-channel EEG montage and represent a subset of the largest public P300 BCI dataset containing recordings from approximately 267 subjects across 20 studies. This dataset is processed and organized according to BIDS standards for facilitating reproducible BCI research and benchmarking.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000197","concept_doi":"10.82901/nemar.nm000197","latest_version_doi":"10.82901/nemar.nm000197.v1.0.2","created_at":"2026-03-24 00:55:34","updated_at":"2026-08-18 21:12:11","zenodo_concept_id":"20500934","is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)\",\n  \"description\": \"This derivative dataset comprises EEG recordings from 21 ALS subjects participating in the BigP3BCI Study M, a P300-based brain-computer interface experiment using a 9x8 adaptive/checkerboard visual speller paradigm. The data were acquired at 256 Hz using 16-channel EEG montage and represent a subset of the largest public P300 BCI dataset containing recordings from approximately 267 subjects across 20 studies. This dataset is processed and organized according to BIDS standards for facilitating reproducible BCI research and benchmarking.\",\n  \"methods_description\": \"EEG data were acquired at a sampling rate of 256 Hz using 16 channels arranged in a standard 10-20 montage with g.USBamp hardware (g.tec). The experimental paradigm employed a P300-based visual speller with a 9x8 character grid using adaptive/checkerboard stimulus presentation. Each trial had a duration of 1.0 second, with target and non-target visual stimuli presented to elicit P300 event-related potentials. Data were recorded in a laboratory environment with online feedback provided to subjects.\",\n  \"license\": \"CC-BY-4.0\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"Boyla Mainsah\": {},\n    \"Chance Fleeting\": {\n      \"orcid\": \"0000-0002-6271-4952\",\n      \"affiliations\": [\n        {\n          \"name\": \"Duke University\"\n        }\n      ]\n    },\n    \"Thomas Balmat\": {},\n    \"Eric Sellers\": {},\n    \"Leslie Collins\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"brain-computer interface\"\n    },\n    {\n      \"term\": \"visual speller\"\n    },\n    {\n      \"term\": \"Event-Related Potentials, P300\",\n      \"subject_scheme\": \"MeSH\",\n      \"scheme_uri\": \"https://id.nlm.nih.gov/mesh/\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D018913\"\n    },\n    {\n      \"term\": \"Amyotrophic Lateral Sclerosis\",\n      \"subject_scheme\": \"MeSH\",\n      \"scheme_uri\": \"https://id.nlm.nih.gov/mesh/\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D000690\"\n    },\n    {\n      \"term\": \"adaptive paradigm\"\n    },\n    {\n      \"term\": \"checkerboard stimulus\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.13026/0byy-ry86\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000197\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.21105/joss.01896\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.1038/s41597-019-0104-8\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/nm000197\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"2.5 GB (841 files)\"\n  ],\n  \"formats\": [\n    \".bdf\",\n    \".edf\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"116265935623ca772aecb21ee794f247a0e662b0b9df1b0ee000419f6fbd8efa\"\n}","last_activity_at":"2026-08-16 13:35:06","source":null,"source_id":null,"subject_count":21,"modalities":"eeg","age_min":19,"age_max":28,"file_size":2551567368,"total_files":3056,"tasks":"p300","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Boyla Mainsah, Chance Fleeting, Thomas Balmat, Eric Sellers, Leslie Collins","license":"CC-BY-4.0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000197-blue)](https://doi.org/10.82901/nemar.nm000197)\n\n# BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)\n\nBigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects).\n\n## Dataset Overview\n\n- **Code**: Mainsah2025-M\n- **Paradigm**: p300\n- **DOI**: 10.13026/0byy-ry86\n- **Subjects**: 21\n- **Sessions per subject**: 1\n- **Events**: Target=2, NonTarget=1\n- **Trial interval**: [0, 1.0] s\n\n## Acquisition\n\n- **Sampling rate**: 256.0 Hz\n- **Number of channels**: 16\n- **Channel types**: eeg=16\n- **Montage**: standard_1020\n- **Hardware**: g.USBamp (g.tec)\n- **Line frequency**: 60.0 Hz\n\n## Participants\n\n- **Number of subjects**: 21\n- **Health status**: healthy\n\n## Experimental Protocol\n\n- **Paradigm**: p300\n- **Number of classes**: 2\n- **Class labels**: Target, NonTarget\n\n## HED Event Annotations\n\nSchema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n\n```\n  Target\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Target\n\n  NonTarget\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Non-target\n\n```\n## Paradigm-Specific Parameters\n\n- **Detected paradigm**: p300\n\n## Signal Processing\n\n- **Feature extraction**: P300_ERP_detection\n\n## Cross-Validation\n\n- **Method**: calibration-then-test\n- **Evaluation type**: within_subject\n\n## BCI Application\n\n- **Applications**: speller\n- **Environment**: laboratory\n- **Online feedback**: True\n\n## Tags\n\n- **Modality**: visual\n- **Type**: perception\n\n## Documentation\n\n- **Description**: BigP3BCI: the largest public P300 BCI dataset, containing EEG recordings from ~267 subjects across 20 studies using 6x6 or 9x8 character grids with various stimulus paradigms.\n- **DOI**: 10.13026/0byy-ry86\n- **License**: CC-BY-4.0\n- **Investigators**: Boyla Mainsah, Chance Fleeting, Thomas Balmat, Eric Sellers, Leslie Collins\n- **Institution**: Duke University; East Tennessee State University\n- **Country**: US\n- **Repository**: PhysioNet\n- **Data URL**: https://physionet.org/content/bigp3bci/1.0.0/\n- **Publication year**: 2025\n\n## References\n\nAppelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Hochenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896\n\nPernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. 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