{"success":true,"database":"eegdash","data":{"_id":"69d16e05897a7725c66f4c94","dataset_id":"nm000191","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":10,"ages":[38,63,57,56,49,44,60,59,59,62],"age_min":38,"age_max":63,"age_mean":54.7,"species":null,"sex_distribution":{"m":6,"f":4},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://nemar.org/dataexplorer/detail/nm000191","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"405d544d6d34288d3c7e0d4a28a7f9ed3355b12210794bc2be6b3ebc8ab237f9","license":"CC-BY-4.0","n_contributing_labs":null,"name":"BigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects)","readme":"# BigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects)\nBigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects).\n## Dataset Overview\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## 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**: 10\n- **Health status**: patients\n- **Clinical population**: ALS\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","1","2"],"size_bytes":578707193,"source":"nemar","storage":{"backend":"nemar","base":"s3://nemar/nm000191","raw_key":"dataset_description.json","dep_keys":["README.md","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["p300"],"timestamps":{"digested_at":"2026-04-30T14:08:53.322739+00:00","dataset_created_at":null,"dataset_modified_at":"2026-04-02T21:18:47Z"},"total_files":270,"computed_title":"BigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects)","nchans_counts":[{"val":16,"count":270}],"sfreq_counts":[{"val":256.0,"count":270}],"stats_computed_at":"2026-05-01T13:49:34.645484+00:00","total_duration_s":46125.9453125,"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"2ebd8d7c84444660","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":0.85,"type":0.75},"reasoning":{"few_shot_analysis":"No few-shot example is an exact P300 speller/BCI dataset. The closest convention guide is the oddball-style example “Cross-modal Oddball Task” (Parkinson’s; multisensory; Clinical/Intervention) and “EEG: Three-Stim Auditory Oddball…” (TBI; auditory; oddball with Target/Standard/Novel). These examples show that (a) explicit clinical recruitment determines Pathology, and (b) oddball/target-vs-nontarget paradigms map Type toward attentional/perceptual constructs depending on the primary aim. Here, the dataset is explicitly a P300 BCI speller with Target vs NonTarget events and visual presentation, which by convention aligns best with Visual modality and an Attention-related construct (attend-to-target to elicit P300) rather than motor execution.","metadata_analysis":"Key facts from provided metadata:\n1) Clinical population: the README explicitly states \"Health status: patients\" and \"Clinical population: ALS\".\n2) Paradigm and event structure: \"Paradigm: p300\" and \"Events: Target=2, NonTarget=1\".\n3) Stimulus modality: HED annotations include \"Visual-presentation\" under both Target and NonTarget, and tags include \"Modality: visual\".\n4) BCI purpose: \"Applications: speller\" and \"Online feedback: True\" indicate a P300 speller BCI setting.\nNote: there is an internal conflict because the title says \"10 healthy subjects\" while the README says \"Clinical population: ALS\" and \"Health status: patients\".","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n- Metadata SAYS: \"Clinical population: ALS\" and \"Health status: patients\" (explicit clinical recruitment).\n- Few-shot pattern SUGGESTS: when a clinical population is named (e.g., Parkinson’s, TBI, epilepsy), Pathology should reflect that clinical recruitment.\n- ALIGN/CONFLICT: Title conflicts (\"10 healthy subjects\") vs README. Few-shot convention aligns with using the explicit clinical recruitment statement. Metadata clinical fact wins over the title.\n\nModality:\n- Metadata SAYS: HED shows \"Visual-presentation\" and tags list \"Modality: visual\".\n- Few-shot pattern SUGGESTS: stimulus channel determines Modality (e.g., auditory stimuli -> Auditory; tactile braille -> Tactile). P300 speller flashing grid implies Visual.\n- ALIGN/CONFLICT: Align.\n\nType:\n- Metadata SAYS: \"Paradigm: p300\", \"Events: Target=2, NonTarget=1\", and \"Applications: speller\" indicate an oddball-like attention-to-target ERP/BCI paradigm.\n- Few-shot pattern SUGGESTS: oddball/target detection often maps to perceptual/attentional constructs depending on emphasis; clinical-biomarker cohorts map to Clinical/Intervention.\n- ALIGN/CONFLICT: Aligns more with Attention than Perception because P300 spellers require sustained/selective attention to target items to evoke the P300; not primarily about sensory thresholds/discrimination.","decision_summary":"Top-2 selections with head-to-head comparisons:\n\nPathology candidates:\n1) Other — Supported by explicit recruitment/clinical statement: \"Clinical population: ALS\" and \"Health status: patients\". ALS is not an allowed Pathology label, so it maps to Other.\n2) Healthy — Supported only by conflicting title text: \"10 healthy subjects\".\nDecision: Other (metadata explicit clinical population overrides the title conflict). Confidence lowered due to internal inconsistency.\n\nModality candidates:\n1) Visual — Supported by \"Visual-presentation\" in HED and \"Modality: visual\" tag; also consistent with P300 speller grids.\n2) Multisensory/Unknown — Weak; no evidence of auditory/tactile stimuli.\nDecision: Visual.\n\nType candidates:\n1) Attention — Supported by P300 target vs non-target structure (\"Events: Target=2, NonTarget=1\") and speller BCI use (\"Applications: speller\"), which relies on attending to targets to elicit P300.\n2) Perception — Plausible because it is stimulus-evoked and involves detecting target flashes; also the README tag says \"Type: perception\".\nDecision: Attention, because the primary construct for eliciting P300 in spellers is selective attention to targets, not perceptual discrimination per se.\n\nConfidence justification features/quotes:\n- Pathology: uses two explicit quotes (\"Clinical population: ALS\", \"Health status: patients\") but conflicts with title.\n- Modality: uses two explicit indicators (\"Visual-presentation\" and \"Modality: visual\").\n- Type: uses multiple explicit paradigm cues (\"Paradigm: p300\", \"Events: Target=2, NonTarget=1\", \"Applications: speller\") but construct-level mapping remains somewhat ambiguous vs Perception."}},"canonical_name":null,"name_confidence":0.76,"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_F"}}