{"success":true,"database":"eegdash","data":{"_id":"696fdefaac44fa1028dc631a","dataset_id":"ds007118","associated_paper_doi":"10.64898/2025.12.17.25342490","authors":["Keisuke Hatano","Naoto Kuroda","Hiroshi Uda","Kazuki Sakakura","Michael J. Cools","Aimee F. Luat","Shin-Ichiro Osawa","Hitoshi Nemoto","Kazushi Ukishiro","Hidenori Endo","Nobukazu Nakasato","Yutaro Takayama","Keiya Iijima","Masaki Iwasaki","Eishi Asano"],"bids_version":"1.7.0","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds007118.v1.0.0","datatypes":["ieeg"],"demographics":{"subjects_count":65,"ages":[12,8,10,15,5,17,6,10,11,17,13,11,14,8,19,5,13,9,12,11,4,10,16,15,16,10,14,7,17,17,30,10,4,9,22,12,11,10,16,6,19,12,10,15,4,10,12,8,14,14,6,4,8,14,37,19,21,14,5,12,11,10,19,16,13,14,8,15,5,15,4,11,18,10,17,7,14,13,19,13,17,9,41,6,12,16,8,14,14,17,5,10,16,15,7,14,5,16,13,11,10,17,14,8,9,17,12,11,13,11,5,13,4,16,11,5,5,7,16,15,8,14,5,13,11,8,3,2,2,2,2,2,7,1,1,1,3,1,2,2,1,1,3,1,1,2,9,13,11,13,20,15,6,13,11,17,13,7,8,6,3,3,3,3,3,45,3,3,3,1,2,16,12,8,35,18,35,15,26,22,16,35,32,14,12,27,20,22,37,21,34,28,19,36,14,21,39,27,21,42,44,15,14,32,15,23,12,8,18,38,31,26,7,33,25,36,25,6,45,14,36,11,19,9,20,5,21,11,12,16],"age_min":1,"age_max":45,"age_mean":13.656521739130435,"species":null,"sex_distribution":{"f":119,"m":114},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://www.medrxiv.org/content/medrxiv/early/2025/12/19/2025.12.17.25342490.full.pdf"},"funding":["the National Institutes of Health (NIH; NS064033 to E.A.)","the Uehara Memorial Foundation Postdoctoral Fellowship (202441017 to K.H.; 20210301 to H.U.)","the Japan Society for the Promotion of Science (JP22J23281 and JP22KJ0323 to N.K.; 202560628 to H.U.; JP19K09494 and 22K09296 to M.I.)"],"ingestion_fingerprint":"c8ee94da8fdd8bde9f27bacf395ea43a931ce5db9c38db854950dd1282753f75","license":"CC0","n_contributing_labs":null,"name":"iEEG_comprehensive_HFA_model_part1","readme":"This dataset contains intracranial EEG data recorded during non-REM sleep and used in Hatano et al. (in press).\nAuthors:\nKeisuke Hatano, Naoto Kuroda, Hiroshi Uda, Kazuki Sakakura, Michael J. Cools, Aimee F. Luat, Shin-Ichiro Osawa, Hitoshi Nemoto, Kazushi Ukishiro, Hidenori Endo, Nobukazu Nakasato, Yutaro Takayama, Keiya Iijima, Masaki Iwasaki, Eishi Asano\nFunding:\nNational Institutes of Health (NIH; NS064033 to E.A.);\nUehara Memorial Foundation Postdoctoral Fellowship (202441017 to K.H.; 20210301 to H.U.);\nJapan Society for the Promotion of Science (JP22J23281, JP22KJ0323, and 202560576 to N.K.; 202560628 to H.U.; JP19K09494 and 22K09296 to M.I.)","recording_modality":["ieeg"],"senior_author":null,"sessions":["01"],"size_bytes":36318124244,"source":"openneuro","storage":{"backend":"s3","base":"s3://openneuro.org/ds007118","raw_key":"dataset_description.json","dep_keys":["CHANGES","README.md","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["sleep"],"timestamps":{"digested_at":"2026-05-31T16:27:39.389070+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":82,"computed_title":"iEEG_comprehensive_HFA_model_part1","nchans_counts":[{"val":128,"count":21},{"val":112,"count":17},{"val":124,"count":6},{"val":102,"count":5},{"val":120,"count":4},{"val":108,"count":4},{"val":138,"count":3},{"val":68,"count":3},{"val":116,"count":3},{"val":118,"count":3},{"val":144,"count":2},{"val":64,"count":2},{"val":106,"count":2},{"val":114,"count":1},{"val":132,"count":1},{"val":36,"count":1},{"val":74,"count":1},{"val":94,"count":1},{"val":122,"count":1},{"val":58,"count":1}],"sfreq_counts":[{"val":1000.0,"count":82}],"stats_computed_at":"2026-05-31T19:34:32.603299+00:00","total_duration_s":159174.0,"tagger_meta":{"model":"openai/gpt-4o","tagged_at":"2026-06-10T08:19:41Z","source":"eegdash-llm-tagger"},"tags":{"pathology":["Epilepsy"],"modality":["Sleep"],"type":["Sleep"],"confidence":{"pathology":0.9,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"The few-shot example with epilepsy explicitly labels the dataset as 'Epilepsy' in the 'Pathology' category. This example provides a style for labeling clinical datasets involving epilepsy. The dataset at hand involves intracranial EEG data recorded during non-REM sleep, which may relate to epileptic conditions, similar to the few-shot example labeled as 'Epilepsy'. However, the few-shot example focuses on pediatric patients, while this dataset's age range includes older participants as well. This example helps infer that the presence of seizure-related details and resection outcomes strongly ties to epilepsy in pathological classification.","metadata_analysis":"The dataset titled 'iEEG_comprehensive_HFA_model_part1' involves intracranial EEG data recorded during non-REM sleep ('This dataset contains intracranial EEG data recorded during non-REM sleep'). The participants' overview includes details like ASM (antiepileptic drug) number and daily seizure presence ('asm_number', 'daily_seizure'), suggesting a focus on epilepsy. There's also mention of seizure captures and resected hemispheres, indicating a surgical or pathological interest in epilepsy.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"1. Pathology: Metadata mentions intracranial EEG, seizure captures, and seizure resection, aligning with epilepsy-related data collection. Few-shot examples suggest labeling as 'Epilepsy' based on seizure-related focus in metadata. ALIGN.\n2. Modality: Metadata states intracranial EEG during sleep ('intracranial EEG data recorded during non-REM sleep'), suggesting 'Sleep' matches best as the modality. ALIGN with expected modality classification.\n3. Type: Sleep-state data without explicit cognitive or task engagement implies a 'Sleep' type. No cognitive condition or specific task purpose unrelated to sleep is highlighted. ALIGN.","decision_summary":"The best labels for this dataset are 'Epilepsy' for Pathology due to explicit seizure-related metadata, 'Sleep' for Modality as this recording occurs during non-REM sleep without specified task engagement, and 'Sleep' for Type due to lack of active cognitive tasks or interventions beyond sleep-state characterization. Metadata evidence strongly suggests these choices."}},"canonical_name":null,"name_confidence":0.55,"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":"Hatano2025_part1","bad_channels_info":null,"ethics_approvals":["IRBs of Wayne State University, Tohoku University, and National Center of Neurology and Psychiatry"],"how_to_acknowledge":"N/A","references_and_links":["","",""],"associated_paper_meta":{"channel":"search","confidence":"high","author_overlap":15,"is_oa":true,"oa_status":"green","source":"paper_resolver"}}}