{"success":true,"database":"eegdash","data":{"_id":"696fdefaac44fa1028dc631e","dataset_id":"ds007180","associated_paper_doi":null,"authors":["Águeda Fuentes-Guerra","Elisa Martín Arévalo","Freek van Ede","Carlos González-García"],"bids_version":"1.4.0","contact_info":["Águeda Fuentes-Guerra"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds007180.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":25,"ages":[30,22,23,23,25,31,21,21,23,23,22,24,23,21,23,20,21,23,18,23,18,21,23,21,29],"age_min":18,"age_max":31,"age_mean":22.88,"species":null,"sex_distribution":{"f":18,"m":7},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds007180","osf_url":null,"github_url":null,"paper_url":null},"funding":["This work was supported by the Spanish Ministry of Science and Innovation and the State Research Agency [research Project PID2020-116342GA-I00 to EMA and CGG, PID2023-149428NB-I00 to CGG, and PID2024-157672NB-I00 to EMA, funded MICIU/AEI/10.13039/501100011033/FEDER, EU]. CGG was also supported by Grant Ramón y Cajal RYC2021-033536-I funded by MCIN/AEI/10.13039/501100011033 and by the European Union Next Generation EU/PRTR. FvE was supported by an ERC Starting Grant from the European Research Council (MEMTICIPATION, 850636) and an NWO Vidi Grant by the Dutch Research Council (grant number 14721). AFG was supported by Grant PRE2021-100351, funded by MCIN/AEI/10.13039/501100011033. Additionally, this publication was funded by the European Social Fund Plus ESF+, CEX2023-001312-M by MCIN/AEI/10.13039/501100011033 and by the UCE-PP2023-11 by the University of Granada as an Excellence Unit Program. This work is part of the doctoral thesis of AFG, under the supervision of EMA and CGG."],"ingestion_fingerprint":"1b1ae8a039c50ce6186f80abd0fedc555858b29ddc88e1e65822c66187c68177","license":"CC0","n_contributing_labs":null,"name":"Exo-EEG Experiment","readme":"Exo-EEG Experiment\nParticipants: see participants.tsv\nTask: exo (see *_eeg.json)\nContact: aguedafgt@ugr.es","recording_modality":["eeg"],"senior_author":"Carlos González-García","sessions":[],"size_bytes":15755538005,"source":"openneuro","storage":{"backend":"s3","base":"s3://openneuro.org/ds007180","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["exo"],"timestamps":{"digested_at":"2026-04-22T12:30:08.292273+00:00","dataset_created_at":"2026-01-07T17:29:16.115Z","dataset_modified_at":"2026-01-07T18:48:28.000Z"},"total_files":25,"computed_title":"Exo-EEG Experiment","nchans_counts":[{"val":63,"count":25}],"sfreq_counts":[{"val":500.0,"count":25}],"stats_computed_at":"2026-04-22T23:16:00.312401+00:00","total_duration_s":125012.12,"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"fd1aae1e70c61360","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Healthy"],"modality":["Unknown"],"type":["Unknown"],"confidence":{"pathology":0.6,"modality":0.4,"type":0.4},"reasoning":{"few_shot_analysis":"Closest few-shot guidance is from datasets where no clinical recruitment is indicated and participants are described simply as volunteers/participants, which are labeled as Healthy (e.g., \"EEG Motor Movement/Imagery Dataset\" labeled Pathology=Healthy; and \"A Resting-state EEG Dataset for Sleep Deprivation\" labeled Pathology=Healthy). These examples guide the convention that, absent any stated diagnosis-based recruitment, the default Pathology label is Healthy rather than a specific disorder label. For Modality and Type, the few-shot examples rely on explicit task/stimulus descriptions (e.g., auditory digits, visual motor imagery, resting eyes-closed). In this dataset, task/stimulus details are not provided beyond the task name \"exo\", so the few-shot convention suggests using Unknown when stimulus channel and cognitive construct are not explicitly described.","metadata_analysis":"Key available metadata is sparse and does not specify stimuli or paradigm. Quotes: (1) readme: \"Task: exo (see *_eeg.json)\"; (2) participants_overview: \"Subjects: 25; Sex: {'f': 18, 'm': 7}; Age range: 18-31\"; (3) dataset_description: \"Name: Exo-EEG Experiment\". None of these lines mention a clinical population, stimulus modality (visual/auditory/etc.), or the cognitive construct (attention/memory/motor/etc.).","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata says nothing about a disorder-based recruitment (e.g., only \"Subjects: 25\" and age/sex demographics). Few-shot pattern suggests labeling as Healthy when there is no explicit clinical cohort description. ALIGN (no conflict).\nModality: Metadata only provides \"Task: exo\" without stimulus description. Few-shot pattern requires explicit stimulus information to label Visual/Auditory/Tactile/etc.; otherwise use Unknown. ALIGN.\nType: Metadata does not describe whether the study is perception/attention/motor/resting/etc. Few-shot pattern labels Type based on explicit paradigm descriptions; absent that, use Unknown. ALIGN.","decision_summary":"Top-2 candidates:\n- Pathology: (1) Healthy—supported by absence of any diagnosis-based recruitment language and only general demographics (\"Subjects: 25... Age range: 18-31\"); (2) Unknown—possible because metadata never explicitly says \"healthy\". Winner: Healthy (convention: non-clinical participant description defaults to Healthy). Confidence=0.6 because it is contextual inference without an explicit \"healthy\" statement.\n- Modality: (1) Unknown—no stimulus channel described (only \"Task: exo\"); (2) Other—could be non-standard but still unspecified. Winner: Unknown. Confidence=0.4 due to lack of evidence.\n- Type: (1) Unknown—no task goal/construct described beyond name \"exo\"; (2) Other—possible but still unsupported. Winner: Unknown. Confidence=0.4 due to lack of evidence."}},"canonical_name":null,"name_confidence":0.79,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"author_year","author_year":"FuentesGuerra2026"}}