{"success":true,"database":"eegdash","data":{"_id":"69d16e05897a7725c66f4cb1","dataset_id":"nm000221","associated_paper_doi":null,"authors":["Grégoire Cattan","Pedro Luiz Coelho Rodrigues","Marco Congedo"],"bids_version":"1.9.0","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":null,"datatypes":["eeg"],"demographics":{"subjects_count":19,"ages":[25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25],"age_min":25,"age_max":25,"age_mean":25.0,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://nemar.org/dataexplorer/detail/nm000221","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"221c340660a241c5ef59ef5694acded2c7f6d422b992af7003c68f1fd6f6769e","license":"CC-BY-4.0","n_contributing_labs":null,"name":"Alphawaves dataset","readme":"# Alphawaves dataset\nAlphawaves dataset\n## Dataset Overview\n- **Code**: Rodrigues2017\n- **Paradigm**: rstate\n- **DOI**: https://doi.org/10.5281/zenodo.2348892\n- **Subjects**: 19\n- **Sessions per subject**: 1\n- **Events**: closed=1, open=2\n- **Trial interval**: [0, 10] s\n## Acquisition\n- **Sampling rate**: 512.0 Hz\n- **Number of channels**: 16\n- **Channel types**: eeg=16\n- **Channel names**: Cz, Fc5, Fc6, Fp1, Fp2, Fz, O1, O2, Oz, P3, P4, P7, P8, Pz, T7, T8\n- **Montage**: standard_1010\n- **Hardware**: g.tec g.USBamp\n- **Software**: OpenViBE\n- **Reference**: right earlobe\n- **Sensor type**: wet electrodes\n- **Line frequency**: 50.0 Hz\n- **Online filters**: no digital filter\n## Participants\n- **Number of subjects**: 19\n- **Health status**: healthy\n- **Age**: mean=25.8\n- **Gender distribution**: female=7, male=13\n## Experimental Protocol\n- **Paradigm**: rstate\n- **Number of classes**: 2\n- **Class labels**: closed, open\n- **Trial duration**: 10 s\n- **Study design**: Subjects alternated between keeping eyes closed (condition 1) and eyes open (condition 2) while EEG was recorded\n## HED Event Annotations\nSchema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n```\n  closed\n    ├─ Experiment-structure\n    └─ Rest\n       └─ Close, Eye\n  open\n    ├─ Experiment-structure\n    └─ Rest\n       └─ Open, Eye\n```\n## Paradigm-Specific Parameters\n- **Detected paradigm**: resting_state\n## Data Structure\n- **Trials**: 10\n## Preprocessing\n- **Data state**: raw\n- **Preprocessing applied**: False\n## Signal Processing\n- **Feature extraction**: ERS\n- **Frequency bands**: alpha=[8, 12] Hz\n## Tags\n- **Pathology**: Healthy\n- **Modality**: Resting State\n- **Type**: Resting-state\n## Documentation\n- **DOI**: 10.5281/zenodo.2348891\n- **Associated paper DOI**: hal-02086581\n- **License**: CC-BY-4.0\n- **Investigators**: Grégoire Cattan, Pedro Luiz Coelho Rodrigues, Marco Congedo\n- **Senior author**: Marco Congedo\n- **Contact**: pedro-luiz.coelho-rodrigues@grenoble-inp.fr\n- **Institution**: GIPSA-lab, CNRS, University Grenoble-Alpes, Grenoble INP\n- **Department**: GIPSA-lab\n- **Address**: 11 rue des Mathématiques, Grenoble Campus BP46, F-38402, France\n- **Country**: FR\n- **Repository**: Zenodo\n- **Data URL**: https://doi.org/10.5281/zenodo.2348891\n- **Publication year**: 2018\n- **Ethics approval**: All participants provided written informed consent\n- **How to acknowledge**: Please cite: Cattan, Rodrigues & Congedo (2018). EEG Alpha Waves Dataset. GIPSA-lab Research Report. https://hal.science/hal-02086581\n## References\nG. Cattan, P. L. Coelho Rodrigues, and M. Congedo, ‘EEG Alpha Waves Dataset’, 2018. Available: https://hal.archives-ouvertes.fr/hal-02086581\nRodrigues PLC. Alpha-Waves-Dataset [Internet]. Grenoble: GIPSA-lab; 2018. Available from: https://github.com/plcrodrigues/Alpha-Waves-Dataset\nNotes\n.. versionadded:: 1.1.0\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":85643546,"source":"nemar","storage":{"backend":"nemar","base":"s3://nemar/nm000221","raw_key":"dataset_description.json","dep_keys":["README.md","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["rstate"],"timestamps":{"digested_at":"2026-04-30T14:09:09.123304+00:00","dataset_created_at":null,"dataset_modified_at":"2026-03-24T08:46:44Z"},"total_files":19,"computed_title":"Alphawaves dataset","nchans_counts":[{"val":16,"count":19}],"sfreq_counts":[{"val":512.0,"count":19}],"stats_computed_at":"2026-05-01T13:49:34.645842+00:00","total_duration_s":3462.775390625,"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"dfdfdb3a0340234e","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Healthy"],"modality":["Resting State"],"type":["Resting-state"],"confidence":{"pathology":0.9,"modality":0.9,"type":0.9},"reasoning":{"few_shot_analysis":"Most similar few-shot example by paradigm is the resting-state dataset labeled Healthy / Resting State / Resting-state (few-shot: “A Resting-state EEG Dataset for Sleep Deprivation”), which uses eyes-open/eyes-closed resting recordings and maps that paradigm to Modality=Resting State and Type=Resting-state. The current dataset is also an eyes open vs eyes closed resting-state alpha recording, so the same convention applies. Other few-shot examples show that when a clinical diagnosis is present (e.g., Dementia, Epilepsy, Parkinson’s), Pathology switches away from Healthy; here the metadata explicitly states “healthy,” so we keep Healthy.","metadata_analysis":"Key metadata facts:\n- Population: \"Health status: healthy\" and also \"Tags\\n- **Pathology**: Healthy\".\n- Task/paradigm: \"Paradigm: rstate\" and \"Detected paradigm: resting_state\".\n- Resting eyes open/closed: \"Events: closed=1, open=2\" and \"Subjects alternated between keeping eyes closed (condition 1) and eyes open (condition 2) while EEG was recorded\".\n- HED confirms rest: under HED annotations both conditions are nested under \"Rest\" (\"Rest -> Close, Eye\" and \"Rest -> Open, Eye\").","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n- Metadata says: \"Health status: healthy\"; also \"Tags - Pathology: Healthy\".\n- Few-shot suggests: Resting-state datasets without a named disorder are labeled Healthy.\n- Alignment: ALIGN.\n\nModality:\n- Metadata says: \"Paradigm: rstate\"; \"Detected paradigm: resting_state\"; and protocol is eyes open/closed while recording (no external stimulus stream).\n- Few-shot suggests: Eyes-open/eyes-closed resting paradigms map to Modality=Resting State.\n- Alignment: ALIGN.\n\nType:\n- Metadata says: \"Detected paradigm: resting_state\"; HED tags place both events under \"Rest\"; and design is alternating eyes open/closed during recording.\n- Few-shot suggests: Passive resting recordings map to Type=Resting-state (distinct from Sleep).\n- Alignment: ALIGN.","decision_summary":"Top-2 candidate labels and selection:\n\nPathology:\n1) Healthy (selected) — supported by: \"Health status: healthy\"; \"Tags - Pathology: Healthy\"; no clinical recruitment/diagnosis described.\n2) Unknown (runner-up) — would apply if health status were missing/unclear.\nDecision: Healthy clearly wins. Alignment status: aligned with few-shot conventions.\n\nModality:\n1) Resting State (selected) — supported by: \"Paradigm: rstate\"; \"Detected paradigm: resting_state\"; \"Subjects alternated between keeping eyes closed ... and eyes open ... while EEG was recorded\".\n2) Visual (runner-up) — eyes open/closed involves vision state, but there is no explicit visual stimulus; convention treats this as Resting State.\nDecision: Resting State wins based on explicit resting-state paradigm statements and few-shot convention.\n\nType:\n1) Resting-state (selected) — supported by: \"Detected paradigm: resting_state\"; HED shows \"Rest\" for both conditions; protocol is passive alternating eyes state.\n2) Attention (runner-up) — could be argued since eyes open/closed manipulates vigilance, but dataset is explicitly described/structured as resting-state.\nDecision: Resting-state wins with direct metadata support and matching few-shot example.\n\nConfidence justification (evidence count):\n- Pathology 0.9: explicit quotes include \"Health status: healthy\" and \"Tags - Pathology: Healthy\" plus consistent non-clinical participant description.\n- Modality 0.9: explicit quotes include \"Paradigm: rstate\", \"Detected paradigm: resting_state\", and the eyes open/closed alternation protocol.\n- Type 0.9: explicit quotes include \"Detected paradigm: resting_state\", HED \"Rest\" annotations, and the explicit study design description (eyes open/closed resting)."}},"canonical_name":null,"name_confidence":0.7,"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":"Cattan2017"}}