{"success":true,"database":"eegdash","data":{"_id":"69d16e05897a7725c66f4c9a","dataset_id":"nm000197","associated_paper_doi":null,"authors":["Boyla Mainsah","Chance Fleeting","Thomas Balmat","Eric Sellers","Leslie Collins"],"bids_version":"1.9.0","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":null,"datatypes":["eeg"],"demographics":{"subjects_count":21,"ages":[21,27,20,21,25,22,20,23,21,22,21,20,21,23,22,23,24,27,28,19,27],"age_min":19,"age_max":28,"age_mean":22.714285714285715,"species":null,"sex_distribution":{"f":12,"m":9},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://nemar.org/dataexplorer/detail/nm000197","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"e9b41064bc0739e8724fae2dc7d103efb5e6bb8a05736bba3976ecee0ab7687e","license":"CC-BY-4.0","n_contributing_labs":null,"name":"BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)","readme":"# BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)\nBigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects).\n## Dataset Overview\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## Acquisition\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## Participants\n- **Number of subjects**: 21\n- **Health status**: healthy\n## Experimental Protocol\n- **Paradigm**: p300\n- **Number of classes**: 2\n- **Class labels**: Target, NonTarget\n## HED Event Annotations\nSchema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n```\n  Target\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Target\n  NonTarget\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Non-target\n```\n## Paradigm-Specific Parameters\n- **Detected paradigm**: p300\n## Signal Processing\n- **Feature extraction**: P300_ERP_detection\n## Cross-Validation\n- **Method**: calibration-then-test\n- **Evaluation type**: within_subject\n## BCI Application\n- **Applications**: speller\n- **Environment**: laboratory\n- **Online feedback**: True\n## Tags\n- **Modality**: visual\n- **Type**: perception\n## Documentation\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## References\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\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. Scientific Data, 6, 103. https://doi.org/10.1038/s41597-019-0104-8\n---\nGenerated by MOABB 1.5.0 (Mother of All BCI Benchmarks)\nhttps://github.com/NeuroTechX/moabb","recording_modality":["eeg"],"senior_author":null,"sessions":["0"],"size_bytes":515452479,"source":"nemar","storage":{"backend":"nemar","base":"s3://nemar/nm000197","raw_key":"dataset_description.json","dep_keys":["README.md","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["p300"],"timestamps":{"digested_at":"2026-04-30T14:08:57.289845+00:00","dataset_created_at":null,"dataset_modified_at":"2026-03-24T00:56:44Z"},"total_files":420,"computed_title":"BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)","nchans_counts":[{"val":16,"count":420}],"sfreq_counts":[{"val":256.0,"count":420}],"stats_computed_at":"2026-05-01T13:49:34.645572+00:00","total_duration_s":40388.109375,"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"4982931e6d70df5a","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Other"],"modality":["Visual"],"type":["Attention"],"confidence":{"pathology":0.7,"modality":0.9,"type":0.75},"reasoning":{"few_shot_analysis":"Most similar few-shot conventions are the Oddball/P300-like paradigms. Example: “Cross-modal Oddball Task” (Parkinson’s) describes a standard vs oddball cue structure and is labeled with Modality=Multisensory and Type=Clinical/Intervention (because the main focus is PD cognitive dysfunction). Example: “EEG: Three-Stim Auditory Oddball and Rest in Acute and Chronic TBI” is an oddball target/standard paradigm and is labeled Modality=Auditory and Type=Decision-making. These examples guide that target vs non-target / oddball-style ERP paradigms are treated as P300-type stimulus classification tasks, and that pathology labeling follows the recruited clinical group (PD/TBI) rather than generic ‘control’ language. For this dataset, the paradigm is explicitly “p300” and a “speller”, aligning with the oddball/P300 convention; the stimulus channel is visual (like the schizophrenia visual discrimination example, which maps visual stimuli to Modality=Visual).","metadata_analysis":"Key dataset facts from metadata/readme:\n- Clinical population signal: title says “(21 ALS subjects)” (\"BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)\").\n- But a conflicting line in participants section: “Health status: healthy”.\n- Task/paradigm: “Paradigm: p300” and “Applications: speller”.\n- Event structure: “Events: Target=2, NonTarget=1” plus HED labels “Visual-presentation” under both Target and NonTarget.\n- Also explicit tag: “Modality: visual”.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n1) Metadata says: title explicitly states “(21 ALS subjects)”. It also (conflict) says “Health status: healthy”.\n2) Few-shot pattern suggests: use the explicitly recruited clinical population when named (e.g., PD/TBI examples recruit PD/TBI and are labeled Parkinson’s/TBI).\n3) Alignment/Conflict: CONFLICT within metadata (ALS vs “healthy”), but few-shot convention aligns with prioritizing explicit clinical recruitment mention.\n4) Winner: ALS mention wins as the more specific recruitment fact; since ALS is not an allowed pathology label, map to “Other”.\n\nModality:\n1) Metadata says: HED annotations include “Visual-presentation”; also “Modality: visual”.\n2) Few-shot pattern suggests: modality follows stimulus channel (e.g., visual discrimination -> Visual; oddball with auditory+visual -> Multisensory).\n3) Alignment/Conflict: ALIGN.\n4) Winner: Visual.\n\nType:\n1) Metadata says: “Paradigm: p300”, “Applications: speller”, and target/non-target stimulus classes (“Target, NonTarget”).\n2) Few-shot pattern suggests: oddball/P300-like paradigms are categorized by the primary cognitive construct; similar examples label oddball either as Decision-making (TBI oddball) or Clinical/Intervention when clinical dysfunction is the primary focus (PD oddball).\n3) Alignment/Conflict: Partially ambiguous (Attention vs Perception vs Decision-making). The dataset is a P300 speller where participants typically attend to a target character among non-target flashes, which most directly reflects attentional selection.\n4) Winner: Attention (closer to P300 target detection/selection than value-based choice; not Resting-state/Motor/Sleep).","decision_summary":"Top-2 selections and final decisions:\n\nPathology:\n- Candidate 1: Other — supported by explicit title “(21 ALS subjects)” (ALS not in allowed list, so map to Other).\n- Candidate 2: Healthy — supported by the conflicting metadata line “Health status: healthy”.\nHead-to-head: “ALS subjects” is a specific recruitment descriptor in the dataset title and overrides the generic ‘healthy’ field; choose Other.\nConfidence basis: 1 strong explicit quote for ALS plus 1 conflicting quote (“healthy”) -> moderate confidence.\n\nModality:\n- Candidate 1: Visual — supported by “Visual-presentation” in HED and “Modality: visual”, plus “9x8 … checkerboard” speller context.\n- Candidate 2: Multisensory — weak; no auditory/tactile stimuli indicated.\nHead-to-head: Visual clearly dominates.\nConfidence basis: 3+ direct supports (HED Visual-presentation; “Modality: visual”; checkerboard speller description).\n\nType:\n- Candidate 1: Attention — P300 speller with “Target” vs “NonTarget” implies selective attention to targets.\n- Candidate 2: Perception — could be framed as visual target detection/discrimination.\nHead-to-head: P300 speller is more classically an attention/target selection paradigm than a pure perceptual threshold/discrimination task.\nConfidence basis: explicit “p300” + “speller” + target/non-target event structure, but no direct ‘attention’ wording -> moderate-high."}},"canonical_name":null,"name_confidence":0.78,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"canonical","author_year":"Mainsah2025_BigP3BCI_M"}}