{"dataset":{"id":"224","dataset_id":"nm000191","name":"BigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects)","description":"BigP3BCI Study F is a derivative EEG dataset comprising P300-based brain-computer interface recordings from 10 ALS patients across 3 sessions using a 6x6 character grid speller paradigm. This dataset is extracted from the larger BigP3BCI benchmark (DOI: 10.13026/0byy-ry86) and processed using MOABB 1.5.0. The dataset contains 16-channel EEG data sampled at 256 Hz with visual stimulus presentations classified as target and non-target events, designed for evaluating P300 detection algorithms and BCI speller applications.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000191","concept_doi":"10.82901/nemar.nm000191","latest_version_doi":"10.82901/nemar.nm000191.v1.0.2","created_at":"2026-03-24 00:07:04","updated_at":"2026-08-18 18:17:44","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"BigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects)\",\n  \"description\": \"BigP3BCI Study F is a derivative EEG dataset comprising P300-based brain-computer interface recordings from 10 ALS patients across 3 sessions using a 6x6 character grid speller paradigm. This dataset is extracted from the larger BigP3BCI benchmark (DOI: 10.13026/0byy-ry86) and processed using MOABB 1.5.0. The dataset contains 16-channel EEG data sampled at 256 Hz with visual stimulus presentations classified as target and non-target events, designed for evaluating P300 detection algorithms and BCI speller applications.\",\n  \"methods_description\": \"EEG data were acquired from ALS patients using a g.USBamp amplifier (g.tec) with 16 channels arranged in a standard 10-20 montage at a sampling rate of 256 Hz with 60 Hz line frequency filtering. Subjects performed a visual P300 speller task with a 6x6 character grid across 3 sessions. Trial intervals were defined from 0 to 1.0 seconds post-stimulus. Data were processed and organized using MOABB 1.5.0 (Mother of All BCI Benchmarks).\",\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\": \"P300\"\n    },\n    {\n      \"term\": \"Brain-Computer Interfaces\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D062207\"\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\": \"Visual Perception\",\n 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\"10.1038/s41597-019-0104-8\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/nm000191\",\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    \"2.0 GB (541 files)\"\n  ],\n  \"formats\": [\n    \".bdf\",\n    \".edf\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"5e114cc32f26d9c2705cf2ab88d1a2a62caa4cfef293df6b064866d0dccbedb0\"\n}","last_activity_at":"2026-08-16 13:35:12","source":null,"source_id":null,"subject_count":10,"modalities":"eeg","age_min":38,"age_max":63,"file_size":2046568423,"total_files":2051,"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.nm000191-blue)](https://doi.org/10.82901/nemar.nm000191)\n\n# BigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects)\n\nBigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects).\n\n## Dataset Overview\n\n- **Code**: Mainsah2025-F\n- **Paradigm**: p300\n- **DOI**: 10.13026/0byy-ry86\n- **Subjects**: 10\n- **Sessions per subject**: 3\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**: 10\n- **Health status**: patients\n- **Clinical population**: ALS\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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