{"success":true,"database":"eegdash","data":{"_id":"6965f3e1ac44fa1028dc6318","dataset_id":"ds007176","associated_paper_doi":null,"authors":["Verónica Henao Isaza","Valeria Cadavid Castro","Luisa María Zapata Saldarriaga","Yorguin-Jose Mantilla-Ramos","Jazmín Ximena Suarez Revelo","Carlos Andrés Tobón Quintero","John Fredy Ochoa Gómez"],"bids_version":"1.8.0","contact_info":["Verónica Henao Isaza"],"contributing_labs":null,"data_processed":true,"dataset_doi":"doi:10.18112/openneuro.ds007176.v1.0.2","datatypes":["eeg"],"demographics":{"subjects_count":45,"ages":[55,52,46,42,55,52,48,46,62,59,24,28,29,25,23,28,21,25,26,28,23,33,39,46,31,29,30,29,34,42,34,34,39,35,35,34,31,30,41,42,25,45,32,40,30],"age_min":21,"age_max":62,"age_mean":36.37777777777778,"species":null,"sex_distribution":{"m":17,"f":28},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds007176","osf_url":null,"github_url":null,"paper_url":null},"funding":["Comité para el Desarrollo de la Investigación - CODI, Universidad de Antioquia"],"ingestion_fingerprint":"1b3eb9d0e8c6ab09d4152a6396c470c2381e9b4a749dfd9bf68072ccb7c2b979","license":"CC0","n_contributing_labs":null,"name":"Longitudinal EEG Test-Retest Reliability in Healthy Individuals","readme":"Longitudinal EEG Test-Retest Reliability in Healthy Individuals\n================================================================\nDataset Description\n-------------------\nThis dataset contains longitudinal resting-state EEG recordings from 43 healthy adults,\ncollected over four sessions spanning approximately two years, with an average interval\nof 7.2 months between sessions. The dataset includes raw EEG data and relevant metadata\nfollowing the BIDS standard.\nPurpose\n-------\nThe dataset was acquired to assess the test-retest reliability of EEG signals using\nan automated preprocessing pipeline, including independent component analysis and\nwavelet-enhanced artifact removal. It allows for analysis of neural components,\nrelative power in regions of interest (ROIs), and longitudinal stability of EEG measures.\nData Structure\n--------------\n- `dataset_description.json` : Dataset metadata and authorship information.\n- `participants.tsv` : Participant demographics and IDs.\n- `sub-XX/eeg/` : Folder for each participant containing EEG data files.\nEEG Data\n--------\nEach participant folder contains EEG recordings in BIDS-compliant format. Data\ninclude:\n- Raw EEG signals (`.eeg`, `.vhdr`, `.vmrk`)\n- Associated metadata files (`.json`) describing recording parameters and task information.\nUsage Notes\n-----------\n- All participants provided written informed consent.\n- Data are de-identified and do not contain personally identifiable information.\n- Users should cite the following paper when using this dataset:\n  Henao Isaza V, et al. Longitudinal test-retest reliability of quantitative EEG in\n  healthy individuals using an automated preprocessing approach. DOI: 10.1016/j.bspc.2026.109484\nLicense\n-------\nThis dataset is publicly available under a Creative Commons CC0 license.","recording_modality":["eeg"],"senior_author":"John Fredy Ochoa Gómez","sessions":["V0","V1","V2","V3","V4"],"size_bytes":22616298900,"source":"openneuro","storage":{"backend":"s3","base":"s3://openneuro.org/ds007176","raw_key":"dataset_description.json","dep_keys":["CHANGES","README.md","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["CE","OE"],"timestamps":{"digested_at":"2026-04-22T12:30:06.265800+00:00","dataset_created_at":"2026-01-06T17:08:15.190Z","dataset_modified_at":"2026-04-07T14:12:56.000Z"},"total_files":300,"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"c588cdbeef2fea8e","model":"openai/gpt-5.2","tagged_at":"2026-01-20T19:31:26.989007+00:00"},"tags":{"pathology":["Healthy"],"modality":["Resting State"],"type":["Resting-state"],"confidence":{"pathology":0.9,"modality":0.9,"type":0.85},"reasoning":{"few_shot_analysis":"Most similar few-shot conventions are the resting-state datasets:\n- Example “A Resting-state EEG Dataset for Sleep Deprivation” is labeled Pathology=Healthy, Modality=Resting State, Type=Resting-state; it shows that when the paradigm is explicitly resting-state (eyes open/closed) in healthy participants, the catalog uses Modality=Resting State and Type=Resting-state.\n- Example “A dataset of EEG recordings from: Alzheimer's disease, Frontotemporal dementia and Healthy subjects” is labeled Modality=Resting State and Type=Clinical/Intervention because a clinical cohort is the primary focus; this guides that Type should switch to Clinical/Intervention only when the clinical population is central.\nThe current dataset is explicitly healthy and resting-state, so it follows the former convention (Healthy + Resting State + Resting-state).","metadata_analysis":"Key facts from the provided README:\n1) Population: explicitly healthy: \"longitudinal resting-state EEG recordings from 43 healthy adults\".\n2) Paradigm: explicitly resting-state: \"longitudinal resting-state EEG recordings\".\n3) Purpose emphasizes reliability of EEG measures (but still resting-state data): \"acquired to assess the test-retest reliability of EEG signals\".\nAdditional supportive detail: \"collected over four sessions spanning approximately two years\" reinforces longitudinal/reliability framing but does not change the paradigm label.","paper_abstract_analysis":"No useful paper information. (Only a citation/DOI is provided in the README; no abstract text is included.)","evidence_alignment_check":"Pathology:\n- Metadata says: \"43 healthy adults\".\n- Few-shot pattern suggests: resting-state datasets in healthy cohorts map to Pathology=Healthy.\n- Alignment: ALIGN.\n\nModality:\n- Metadata says: \"resting-state EEG recordings\".\n- Few-shot pattern suggests: resting paradigms map to Modality=Resting State.\n- Alignment: ALIGN.\n\nType:\n- Metadata says: \"resting-state EEG recordings\" and the aim is \"test-retest reliability\" of EEG measures.\n- Few-shot pattern suggests: if the dataset is resting-state and not centered on a disorder/intervention, Type=Resting-state.\n- Alignment: ALIGN (reliability aim does not override that the recorded condition/paradigm is resting-state).","decision_summary":"Top-2 candidates per category (with decision):\n\nPathology:\n1) Healthy (selected) — Evidence: \"43 healthy adults\"; \"Healthy Individuals\" in the title line; \"healthy individuals\" in the cited paper title.\n2) Unknown (runner-up) — Would apply if recruitment criteria were not stated, but they are.\nFinal: Healthy. Confidence supported by 3 explicit phrases indicating healthy cohort.\n\nModality:\n1) Resting State (selected) — Evidence: \"resting-state EEG recordings\"; \"longitudinal resting-state EEG recordings\"; \"resting-state\" explicitly repeated.\n2) Unknown (runner-up) — Not needed because resting-state is explicit.\nFinal: Resting State. Confidence supported by multiple explicit mentions.\n\nType:\n1) Resting-state (selected) — Evidence: \"resting-state EEG recordings\" (paradigm); dataset is for stability/reliability of resting EEG measures rather than a cognitive task.\n2) Other (runner-up) — Could be argued because the stated goal is methodological (test-retest reliability), but the catalog convention (per few-shot) labels resting paradigms as Resting-state unless clinical/intervention dominates.\nFinal: Resting-state. Confidence high due to explicit resting-state paradigm and strong few-shot alignment."}},"computed_title":"Longitudinal EEG Test-Retest Reliability in Healthy Individuals","nchans_counts":[{"val":60,"count":300}],"sfreq_counts":[{"val":1000.0,"count":300}],"stats_computed_at":"2026-04-22T23:16:00.312303+00:00","total_duration_s":94226.46,"author_year":"Isaza2026_Longitudinal","canonical_name":null}}