{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a33fe","dataset_id":"ds005545","associated_paper_doi":null,"authors":["Aya Kanno","Ryuzaburo Kochi","Kazuki Sakakura","Yu Kitazawa","Hiroshi Uda","Riyo Ueda","Masaki Sonoda","Min-Hee Lee","Jeong-Won Jeong","Aimee F. Luat","Eishi Asano"],"bids_version":"1.7.0","contact_info":["Aya Kanno"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005545.v1.0.3","datatypes":["ieeg"],"demographics":{"subjects_count":106,"ages":[16,17,15,14,16,17,10,8,8,11,16,18,17,8,17,14,10,10,15,19,8,14,11,13,10,5,16,16,37,11,21,15,5,14,28,14,13,41,12,8,10,12,28,27,17,14,15,6,17,4,12,5,9,30,13,17,16,8,13,14,12,13,11,15,14,11,12,17,11,17,10,13,11,16,15,15,10,10,16,12,8,14,19,6,8,16,19,15,14,5,16,13,16,9,13,11,13,20,15,8,6,16,17,13,17,15],"age_min":4,"age_max":41,"age_mean":13.943396226415095,"species":null,"sex_distribution":{"m":57,"f":49},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds005545","osf_url":null,"github_url":null,"paper_url":null},"funding":["N/A"],"ingestion_fingerprint":"ec47ec785876521d8e089f13b9114702ef79c589930358ece731c838ed21b472","license":"CC0","n_contributing_labs":null,"name":"Auditory naming","readme":"This dataset, used in the analysis reported by Kanno et al., (2025), contains intracranial EEG recordings from 106 individuals who performed an auditory‑naming task. The corresponding MATLAB analysis code is available at https://github.com/a8k8nn0/TractographyAtlas, and electrode coordinates are provided in MNI‑305 space.\nEach EDF file is tagged for the auditory naming task with the following event codes:\n401 – stimulus onset\n402 – stimulus offset\n501 – response onset\nReference:\nAya Kanno, Ryuzaburo Kochi, Kazuki Sakakura, Yu Kitazawa, Hiroshi Uda, Riyo Ueda, Masaki Sonoda, Min-Hee Lee, Jeong-Won Jeong, Robert Rothermel, Aimee F. Luat, Eishi Asano. Dynamic Causal Tractography Analysis of Auditory Descriptive Naming: An Intracranial Study of 106 Patients. bioRxiv 2025.03.07.641428; doi: https://doi.org/10.1101/2025.03.07.641428","recording_modality":["ieeg"],"senior_author":"Eishi Asano","sessions":["01","02","03","04","05"],"size_bytes":42905692557,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["auditory"],"timestamps":{"digested_at":"2026-04-22T12:28:35.759512+00:00","dataset_created_at":"2024-09-30T21:57:55.144Z","dataset_modified_at":"2025-04-23T16:00:00.000Z"},"total_files":336,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005545","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"e726aa210002ab89","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Surgery"],"modality":["Auditory"],"type":["Other"],"confidence":{"pathology":0.6,"modality":0.85,"type":0.7},"reasoning":{"few_shot_analysis":"Closest few-shot matches by convention:\n- The digit-span dataset (Healthy / Auditory / Memory) shows that when the stimulus is spoken items, Modality is labeled \"Auditory\" (stimulus channel drives modality).\n- The ABR music/speech dataset (Healthy / Auditory / Perception) reinforces \"Auditory\" modality for sound-based stimulation.\n- The pediatric epilepsy HFO dataset (Epilepsy / Resting State / Clinical/Intervention) is relevant for the *population* convention around clinical EEG, but this target dataset does not explicitly state epilepsy; so that example can only guide how we would label if epilepsy were clearly stated.\nOverall, few-shot examples strongly guide the Modality mapping (sound stimuli → Auditory). They do not provide a direct Type match for an auditory naming/language-production paradigm, so Type must be determined from the target metadata.","metadata_analysis":"Key metadata facts:\n- Population/recording context: \"contains intracranial EEG recordings from 106 individuals\" and the cited paper title includes \"An Intracranial Study of 106 Patients\" (implies a clinical/surgical iEEG cohort, but no explicit diagnosis is stated).\n- Task/stimulus-response structure: participants \"performed an auditory‑naming task\" with event codes \"401 – stimulus onset\" / \"402 – stimulus offset\" / \"501 – response onset\" (clear auditory stimulus with overt response).\n- Age range suggests mixed pediatric/adult clinical cohort: \"Age range: 4-41\".\nThese lines directly support Auditory modality and a task involving naming (language production).","paper_abstract_analysis":"No useful paper information. (Only a citation to a bioRxiv preprint is provided; no abstract text included in the metadata payload.)","evidence_alignment_check":"Pathology:\n- Metadata says: \"intracranial EEG recordings\" and \"Intracranial Study of 106 Patients\" (clinical patients, but diagnosis not named).\n- Few-shot pattern suggests: many intracranial EEG datasets are often epilepsy/surgical evaluations, but this is not explicitly stated in the provided metadata.\n- Alignment status: PARTIAL/WEAK (clinical implied, specific condition not stated). Decision leans on contextual inference rather than an explicit diagnosis.\n\nModality:\n- Metadata says: \"auditory‑naming task\" and event code \"401 – stimulus onset\" (auditory stimulus presentation).\n- Few-shot pattern suggests: sound-based paradigms (digit span; music/speech ABR) → \"Auditory\" modality.\n- Alignment status: ALIGNS strongly.\n\nType:\n- Metadata says: \"auditory‑naming task\" with \"response onset\" (naming/language production), but does not describe memory load, reinforcement learning, attention, or pure sensory discrimination.\n- Few-shot pattern suggests: when the goal is working memory (digit span) label \"Memory\"; when it is sensory/encoding (ABR) label \"Perception\". Naming/language is not directly covered by given few-shots.\n- Alignment status: NO DIRECT MATCH; must choose best fitting Type label from allowed set based on task purpose. \"Other\" fits best given the label set.","decision_summary":"Top-2 comparative selections:\n\n1) Pathology\n- Candidate A: \"Surgery\"\n  Evidence: \"intracranial EEG recordings\" + cited paper: \"An Intracranial Study of 106 Patients\" (intracranial implantation typically occurs in a surgical evaluation context).\n- Candidate B: \"Unknown\"\n  Evidence: no explicit diagnosis/condition is stated (no mention of epilepsy, tumor, etc.).\n- Head-to-head: Although no diagnosis is explicitly named, the dataset explicitly states intracranial EEG in \"patients\", which strongly implies a surgical implantation cohort; \"Surgery\" is more informative than \"Unknown\" given the provided facts.\n- Final: Surgery.\n\n2) Modality\n- Candidate A: \"Auditory\"\n  Evidence: \"auditory‑naming task\"; event codes include \"stimulus onset\"/\"offset\" for the naming stimuli.\n- Candidate B: \"Other\"\n  Evidence: could be argued if multimodal prompts existed, but none are described.\n- Head-to-head: Clear auditory stimulus description; aligns with few-shot auditory datasets.\n- Final: Auditory.\n\n3) Type\n- Candidate A: \"Other\"\n  Evidence: task is \"auditory‑naming\" (language production/lexical retrieval), which is not directly represented among allowed Type constructs like Memory/Attention/Perception/Motor.\n- Candidate B: \"Memory\"\n  Evidence: naming involves retrieval, but metadata does not frame it as a memory-capacity or encoding/manipulation study.\n- Head-to-head: The dataset’s stated purpose is naming, not a working-memory manipulation; \"Other\" best matches within the constrained label set.\n- Final: Other.\n\nConfidence justification (quotes/features):\n- Pathology (0.6): inference from \"intracranial EEG\" and \"patients\" without an explicit diagnosis.\n- Modality (0.85): explicit \"auditory‑naming task\" plus consistent stimulus-onset/offset event coding.\n- Type (0.7): explicit naming task, but mapping to allowed Type labels is coarse; \"Other\" chosen due to label-set limitations."}},"nemar_citation_count":0,"computed_title":"Auditory naming","nchans_counts":[{"val":128,"count":237},{"val":138,"count":14},{"val":136,"count":11},{"val":134,"count":11},{"val":140,"count":8},{"val":112,"count":6},{"val":110,"count":6},{"val":142,"count":5},{"val":156,"count":5},{"val":150,"count":5},{"val":148,"count":4},{"val":144,"count":4},{"val":164,"count":4},{"val":132,"count":4},{"val":116,"count":3},{"val":96,"count":3},{"val":118,"count":3},{"val":84,"count":3}],"sfreq_counts":[{"val":1000.0,"count":336}],"stats_computed_at":"2026-04-22T23:16:00.310560+00:00","total_duration_s":null,"canonical_name":null,"name_confidence":0.72,"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":"Kanno2024"}}