{"success":true,"database":"eegdash","data":{"_id":"69d16e05897a7725c66f4ca7","dataset_id":"nm000210","associated_paper_doi":null,"authors":["Marco Simoes","Davide Borra","Eduardo Santamaria-Vazquez","Mayra Bittencourt-Villalpando","Dominik Krzeminski","Aleksandar Miladinovic","Carlos Amaral","Bruno Direito","Miguel Castelo-Branco"],"bids_version":"1.9.0","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":null,"datatypes":["eeg"],"demographics":{"subjects_count":15,"ages":[22,22,22,22,22,22,22,22,22,22,22,22,22,22,22],"age_min":22,"age_max":22,"age_mean":22.0,"species":null,"sex_distribution":{"m":15},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://nemar.org/dataexplorer/detail/nm000210","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"63f7a66f46395629c7f616c6ee406b8914455a2708a5595adbd4e1032829cbe5","license":"CC-BY-4.0","n_contributing_labs":null,"name":"BCIAUT-P300 dataset for autism from Simoes et al 2020","readme":"# BCIAUT-P300 dataset for autism from Simoes et al 2020\nBCIAUT-P300 dataset for autism from Simoes et al 2020.\n## Dataset Overview\n- **Code**: Simoes2020\n- **Paradigm**: p300\n- **DOI**: 10.3389/fnins.2020.568104\n- **Subjects**: 15\n- **Sessions per subject**: 7\n- **Events**: Target=2, NonTarget=1\n- **Trial interval**: [0, 1.2] s\n- **Runs per session**: 2\n- **File format**: MATLAB (epoched)\n- **Data preprocessed**: True\n## Acquisition\n- **Sampling rate**: 250.0 Hz\n- **Number of channels**: 8\n- **Channel types**: eeg=8\n- **Channel names**: C3, Cz, C4, CPz, P3, Pz, P4, POz\n- **Montage**: standard_1020\n- **Hardware**: g.Nautilus (g.tec, wireless)\n- **Reference**: right ear\n- **Ground**: AFz\n- **Line frequency**: 50.0 Hz\n## Participants\n- **Number of subjects**: 15\n- **Health status**: patients\n- **Clinical population**: autism spectrum disorder (ASD)\n- **Age**: mean=22.17, std=5.5, min=16, max=38\n- **Gender distribution**: male=15\n- **Species**: human\n## Experimental Protocol\n- **Paradigm**: p300\n- **Number of classes**: 2\n- **Class labels**: Target, NonTarget\n- **Trial duration**: 1.2 s\n- **Study design**: P300 BCI joint-attention training in virtual environment; 8 flashing objects; 15 ASD subjects across 7 sessions (clinical trial NCT02445625)\n- **Feedback type**: visual\n- **Stimulus type**: object flash\n- **Stimulus modalities**: visual\n- **Primary modality**: visual\n- **Mode**: online\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## Data Structure\n- **Trials**: 1600 train + 400*K test per session (K=3-10)\n- **Trials context**: per_session\n## Signal Processing\n- **Classifiers**: EEGNet, LDA, SVM, MLP\n- **Feature extraction**: temporal_features, deep_learning\n- **Frequency bands**: bandpass=[2.0, 30.0] Hz\n## Cross-Validation\n- **Method**: calibration_vs_online\n- **Evaluation type**: within_subject, cross_session, cross_subject\n## BCI Application\n- **Applications**: joint_attention_training\n- **Environment**: clinical\n- **Online feedback**: True\n## Tags\n- **Pathology**: Autism\n- **Modality**: ERP\n- **Type**: P300\n## Documentation\n- **DOI**: 10.3389/fnins.2020.568104\n- **License**: CC-BY-4.0\n- **Investigators**: Marco Simoes, Davide Borra, Eduardo Santamaria-Vazquez, Mayra Bittencourt-Villalpando, Dominik Krzeminski, Aleksandar Miladinovic, Carlos Amaral, Bruno Direito, Miguel Castelo-Branco\n- **Institution**: University of Coimbra\n- **Country**: PT\n- **Data URL**: https://zenodo.org/records/19005186\n- **Publication year**: 2020\n## References\nSimoes, M., Borra, D., Santamaria-Vazquez, E., et al. (2020). BCIAUT-P300: A Multi-Session and Multi-Subject Benchmark Dataset on Autism for P300-Based Brain-Computer- Interfaces. Frontiers in Neuroscience, 14, 568104. https://doi.org/10.3389/fnins.2020.568104\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","3","4","5","6"],"size_bytes":4090792989,"source":"nemar","storage":{"backend":"nemar","base":"s3://nemar/nm000210","raw_key":"dataset_description.json","dep_keys":["README.md","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["p300"],"timestamps":{"digested_at":"2026-04-30T14:09:04.774306+00:00","dataset_created_at":null,"dataset_modified_at":"2026-03-24T03:24:50Z"},"total_files":210,"computed_title":"BCIAUT-P300 dataset for autism from Simoes et al 2020","nchans_counts":[{"val":8,"count":210}],"sfreq_counts":[{"val":250.0,"count":210}],"stats_computed_at":"2026-05-01T13:49:34.645708+00:00","total_duration_s":674767.16,"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"86ff4027921c8be4","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Development"],"modality":["Visual"],"type":["Clinical/Intervention"],"confidence":{"pathology":0.8,"modality":0.9,"type":0.8},"reasoning":{"few_shot_analysis":"Closest few-shot by paradigm is the “Cross-modal Oddball Task” example (Parkinson’s), which uses an oddball-style target/standard structure and is labeled with Modality=Multisensory and Type=Clinical/Intervention. The current dataset is explicitly a P300 (oddball/target vs nontarget ERP-BCI) with a clinical population and a training/clinical-trial framing, which by convention aligns well with Type=Clinical/Intervention rather than a purely cognitive label. The schizophrenia example is visual but is a discrimination/perceptual-decision task and labeled Type=Perception; that helps separate ‘visual stimuli’ from ‘P300/oddball clinical BCI training’, suggesting we should not default to Perception here.","metadata_analysis":"Key pathology facts: “Clinical population: autism spectrum disorder (ASD)” and “Health status: patients”. Task/paradigm facts: “Paradigm: p300” and “Events: Target=2, NonTarget=1”. Stimulus/modality facts: “Stimulus type: object flash” plus “Stimulus modalities: visual” / “Primary modality: visual”. Clinical/training framing: “Study design: P300 BCI joint-attention training in virtual environment” and “(clinical trial NCT02445625)”, with “Environment: clinical” and “Online feedback: True”.","paper_abstract_analysis":"No useful paper information (only DOI/citation present in metadata; no abstract text provided).","evidence_alignment_check":"Pathology: Metadata says “Clinical population: autism spectrum disorder (ASD)”. Few-shot pattern suggests using specific disorder labels when present; however ‘Autism’ is not an allowed Pathology label here. Given ASD is a neurodevelopmental condition, mapping to the allowed label “Development” is consistent with the instruction “Childhood/adolescence mental health → Development” and the explicit ASD recruitment fact. ALIGN (no conflict; only a controlled mapping to allowed labels).\n\nModality: Metadata says “Stimulus modalities: visual”, “Stimulus type: object flash”, and P300 target/nontarget flashes. Few-shot conventions for oddball-like tasks label modality by stimulus channel; this aligns with “Visual”. ALIGN.\n\nType: Metadata says “Paradigm: p300” and also frames it as “P300 BCI joint-attention training… (clinical trial…); Environment: clinical”. Few-shot oddball/clinical cohort example (Parkinson’s oddball) uses Type=Clinical/Intervention when the clinical context/intervention framing is central. This aligns more with Clinical/Intervention than purely Attention/Perception. ALIGN (few-shot supports clinical framing for similar oddball/ERP paradigms in clinical cohorts).","decision_summary":"Pathology top-2: (1) Development — supported by “Clinical population: autism spectrum disorder (ASD)” and ASD being neurodevelopmental; (2) Other — plausible fallback because ‘Autism’ is not an allowed label, but less specific than Development. Final: Development. Confidence justified by explicit ASD recruitment quote(s).\n\nModality top-2: (1) Visual — supported by “Stimulus modalities: visual”, “Primary modality: visual”, and “Stimulus type: object flash”; (2) Multisensory — unlikely since only visual is described. Final: Visual.\n\nType top-2: (1) Clinical/Intervention — supported by “joint-attention training”, “clinical trial NCT02445625”, and “Environment: clinical”; (2) Attention — plausible because P300/oddball target detection strongly engages attention, but training/clinical-trial purpose appears primary in the metadata. Final: Clinical/Intervention. Confidence moderate-high because multiple explicit clinical/training quotes support it."}},"canonical_name":null,"name_confidence":0.9,"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":"Simoes2020"}}