{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a335f","dataset_id":"ds004551","associated_paper_doi":null,"authors":["Kazuki Sakakura","Naoto Kuroda","Masaki Sonoda","Takumi Mitsuhashi","Ethan Firestone","Aimee F. Luat","Neena I. Marupudi","Sandeep Sood","Eishi Asano"],"bids_version":"1.7.0","contact_info":["Kaz Sakakura"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004551.v1.0.6","datatypes":["ieeg"],"demographics":{"subjects_count":114,"ages":[16,4,10,5,14,9,17,15,8,14,14,14,17,10,8,8,11,16,18,17,5,9,17,14,15,6,3,11,4,10,10,5,16,16,2,5,21,15,14,41,12,10,10,7,12,9,17,15,6,4,19,5,10,9,2,30,13,12,11,10,1,17,8,17,1,14,8,12,11,11,15,3,1,19,11,12,17,2,11,1,17,1,11,15,6,15,10,3,10,1,12,8,1,14,19,4,16,5,15,8,14,5,2,13,9,13,11,13,16,11,17,13,7,8],"age_min":1,"age_max":41,"age_mean":10.894736842105264,"species":null,"sex_distribution":{"m":60,"f":54},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds004551","osf_url":null,"github_url":null,"paper_url":null},"funding":["N/A"],"ingestion_fingerprint":"107c9ca50c5388dbe2c8d4af2eaa7538a0392c0917a9395db3467f33af048cb1","license":"CC0","n_contributing_labs":null,"name":"iEEG on children during slow wave sleep\n","readme":"This dataset was curated for publication as part of the manuscript in Sakakura et al. (in preparation).\nIt contains iEEGs collected from 114 individuals during slow wave sleep.\nThe available Matlab code can be found at https://github.com/kaz1126/MI_HFO.\nThe iEEG coordinate system employed in this dataset is MNI305.","recording_modality":["ieeg"],"senior_author":"Eishi Asano","sessions":["01","02","03"],"size_bytes":74017379206,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["sleep"],"timestamps":{"digested_at":"2026-04-22T12:26:42.307172+00:00","dataset_created_at":"2023-04-07T02:24:47.402Z","dataset_modified_at":"2023-05-30T02:54:58.000Z"},"total_files":125,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004551","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"43864ea465826041","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Epilepsy"],"modality":["Sleep"],"type":["Sleep"],"confidence":{"pathology":0.6,"modality":0.9,"type":0.8},"reasoning":{"few_shot_analysis":"Most similar few-shot examples:\n1) “Surrey cEEGrid sleep data set” (Healthy / Sleep / Sleep): shows the convention that when the paradigm is sleep (no active task; sleep staging), the Modality is labeled “Sleep” and the Type is “Sleep”. This guides assigning Sleep/Sleep here because the dataset explicitly targets “slow wave sleep” and uses task “sleep”.\n2) “Dataset of EEG recordings of pediatric patients with epilepsy … HFO markings … first 3 hours of sleep EEG” (Epilepsy / Resting State / Clinical/Intervention): provides a convention that epilepsy/HFO sleep recordings often map Pathology to “Epilepsy” when the clinical population is explicit. Our dataset is iEEG and references an HFO-oriented code repository (MI_HFO), which weakly suggests an epilepsy presurgical context, but unlike the few-shot it is not explicitly stated in metadata; thus it is used only as a convention guide, not as a factual diagnosis.","metadata_analysis":"Key quoted metadata facts:\n- Title: \"iEEG on children during slow wave sleep\".\n- README: \"It contains iEEGs collected from 114 individuals during slow wave sleep.\" and \"The available Matlab code can be found at https://github.com/kaz1126/MI_HFO.\".\n- Tasks: \"sleep\".\n- Participants: \"Age range: 1-41\" and \"Subjects: 114\".\n\nInterpretation from metadata: the recording context is slow-wave sleep (sleep physiology). The population is described only by age range and iEEG recording, without an explicit diagnosis label.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n- Metadata says: does NOT name a diagnosis; only \"iEEGs\" and age-focused description (\"children\" / \"Age range: 1-41\").\n- Few-shot pattern suggests: iEEG + HFO-related keywords often occur in epilepsy cohorts (as in the pediatric epilepsy HFO example), which would suggest “Epilepsy”.\n- Alignment: PARTIAL/UNCERTAIN (no explicit diagnosis in metadata).\n- Resolution: Since no explicit diagnosis is stated, pathology is inferred with low-moderate confidence; we select “Epilepsy” based on contextual cues (iEEG and MI_HFO), but acknowledge uncertainty.\n\nModality:\n- Metadata says: \"during slow wave sleep\" (title; README) and task \"sleep\".\n- Few-shot pattern suggests: sleep recordings are labeled Modality = “Sleep”.\n- Alignment: ALIGNS.\n\nType:\n- Metadata says: sleep context explicitly (\"slow wave sleep\"; task \"sleep\").\n- Few-shot pattern suggests: sleep-focused datasets map Type to “Sleep” (Surrey sleep example).\n- Alignment: ALIGNS (though potential alternative is Clinical/Intervention if the primary intent were epilepsy biomarker characterization, which is not explicit in metadata).","decision_summary":"Top-2 comparative selection per category:\n\nPathology candidates:\n1) Epilepsy (selected): Evidence: invasive \"iEEG\" recording strongly suggests a clinical presurgical epilepsy monitoring context; HFO-oriented repository name \"MI_HFO\" is consistent with epilepsy biomarker work.\n2) Unknown (runner-up): Evidence: metadata never explicitly states \"epilepsy\", \"seizure\", or presurgical monitoring; only provides sleep and demographics.\nHead-to-head: Epilepsy is more plausible given iEEG + HFO cue, but lack of explicit diagnosis keeps confidence moderate.\nConfidence justification: inference-based, no direct diagnostic quote.\n\nModality candidates:\n1) Sleep (selected): Evidence quotes: title \"slow wave sleep\"; README \"during slow wave sleep\"; tasks include \"sleep\".\n2) Resting State (runner-up): would apply if it were merely eyes-closed rest without sleep staging; contradicted by explicit slow-wave sleep.\nHead-to-head: Sleep clearly wins.\nConfidence justification: 3 explicit metadata indicators + strong few-shot convention match.\n\nType candidates:\n1) Sleep (selected): Evidence quotes: \"slow wave sleep\" (title/README) and task \"sleep\"; aligns with sleep-focused few-shot labeling.\n2) Clinical/Intervention (runner-up): plausible if primary purpose is clinical biomarker mapping (suggested only indirectly by \"MI_HFO\"), but not explicit.\nHead-to-head: Sleep wins because the only explicit stated purpose/context is sleep (slow-wave sleep recordings).\nConfidence justification: multiple explicit sleep quotes; remaining uncertainty about primary research aim prevents maximum confidence."}},"nemar_citation_count":3,"computed_title":"iEEG on children during slow wave sleep","nchans_counts":[{"val":128,"count":82},{"val":112,"count":5},{"val":118,"count":3},{"val":138,"count":3},{"val":142,"count":2},{"val":144,"count":2},{"val":108,"count":2},{"val":124,"count":2},{"val":130,"count":2},{"val":134,"count":2},{"val":110,"count":2},{"val":122,"count":2},{"val":102,"count":2},{"val":148,"count":2},{"val":104,"count":2},{"val":132,"count":1},{"val":116,"count":1},{"val":120,"count":1},{"val":106,"count":1},{"val":136,"count":1},{"val":146,"count":1},{"val":126,"count":1},{"val":96,"count":1},{"val":84,"count":1},{"val":58,"count":1}],"sfreq_counts":[{"val":1000.0,"count":125}],"stats_computed_at":"2026-04-22T23:16:00.307857+00:00","total_duration_s":null,"canonical_name":null,"name_confidence":0.62,"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":"Sakakura2023_children_slow_wave"}}