{"success":true,"database":"eegdash","data":{"_id":"69a33a3b897a7725c66f3eef","dataset_id":"ds007445","associated_paper_doi":"10.64898/2026.02.03.26345480","authors":["Saarang Panchavati","Atsuro Daida","Sotaro Kanai","Shingo Oana","Hiroya Ono","Masaki Izumi","Kikuko Kaneko","Aria Fallah","Joe X Qiao","Noriko Salamon","Raman Sankar","Corey Arnold","William Speier","Hiroki Nariai"],"bids_version":"1.9.0","contact_info":["Hiroki Nariai","Saarang Panchavati"],"contributing_labs":null,"data_processed":true,"dataset_doi":"doi:10.18112/openneuro.ds007445.v1.0.2","datatypes":["ieeg"],"demographics":{"subjects_count":19,"ages":[73],"age_min":73,"age_max":73,"age_mean":73.0,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://www.medrxiv.org/content/medrxiv/early/2026/02/04/2026.02.03.26345480.full.pdf"},"funding":["NIH/NINDS K23NS128318"],"ingestion_fingerprint":"a30ede383c7da4b7bdb0845ead972b7c8b537553d4d9779917b317097b775974","license":"CC0","n_contributing_labs":null,"name":"Thalamocortical ictal iEEG dataset","readme":"We investigated thalamocortical network dynamics using intracranial EEG (iEEG) recordings with thalamic sampling from 19 patients with focal epilepsy (1). The iEEG dataset analyzed in this study is publicly shared here.\nBIDS converstion was performed according to references (2) and (3).\nReferences\n(1) Panchavati S, Daida A, Kanai S, Oana S, Ono H, Izumi M, Kaneko K, Fallah A, Qiao JX, Salamon N, Sankar R, Arnold C, Speier W, Nariai H (2026). Distinct Spectral and Directional Thalamocortical Network Dynamics Define Focal Seizure Evolution. medRxiv, 2026 Feb 4:2026.02.03.26345480. doi: 10.64898/2026.02.03.26345480.\n(2) Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896).https://doi.org/10.21105/joss.01896\n(3) Holdgraf, C., Appelhoff, S., Bickel, S., Bouchard, K., D'Ambrosio, S., David, O., … Hermes, D. (2019). iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology. Scientific Data, 6, 102. https://doi.org/10.1038/s41597-019-0105-7","recording_modality":["ieeg"],"senior_author":"Hiroki Nariai","sessions":["sz1","sz10","sz11","sz12","sz1a","sz1b","sz2","sz3","sz4","sz5","sz6","sz7","sz8","sz9"],"size_bytes":54201403733,"source":"openneuro","storage":{"backend":"s3","base":"s3://openneuro.org/ds007445","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["seizure"],"timestamps":{"digested_at":"2026-02-28T18:51:30.081352+00:00","dataset_created_at":"2026-02-20T22:33:40.621Z","dataset_modified_at":"2026-02-21T05:03:36.000Z"},"total_files":66,"computed_title":"Thalamocortical ictal iEEG dataset","nchans_counts":[{"val":140,"count":10},{"val":138,"count":10},{"val":265,"count":6},{"val":83,"count":6},{"val":202,"count":5},{"val":216,"count":5},{"val":162,"count":4},{"val":112,"count":3},{"val":203,"count":3},{"val":68,"count":2},{"val":81,"count":2},{"val":49,"count":2},{"val":139,"count":1},{"val":201,"count":1},{"val":124,"count":1},{"val":137,"count":1},{"val":111,"count":1},{"val":120,"count":1},{"val":261,"count":1},{"val":263,"count":1}],"sfreq_counts":[{"val":200.0,"count":42},{"val":2000.0,"count":17},{"val":200.00000000000003,"count":6},{"val":1999.9999999999998,"count":1}],"stats_computed_at":"2026-10-22T17:07:00.409082+00:00","total_duration_s":265353.658,"tagger_meta":{"model":"gpt-6-sol","taxonomy":"v2","config_hash":"39931253008fe2df","tagged_at":"2026-10-06T13:13:11Z","source":"eegdash-llm-tagger"},"tags":{"pathology":["Epilepsy"],"modality":["No stimulus"],"type":["Clinical"],"confidence":{"pathology":0.9,"modality":0.8,"type":0.9},"reasoning":{"few_shot_analysis":"The pediatric epilepsy HFO example is the closest match: recordings from patients with epilepsy are labeled Epilepsy, No stimulus, and Clinical when the focus is an epilepsy biomarker rather than an externally presented task. The dementia resting-EEG example likewise shows that a clinical recording can be labeled Clinical rather than Resting-state. These examples guide label conventions, not participant facts.","metadata_analysis":"The readme states that the study used \"intracranial EEG (iEEG) recordings with thalamic sampling from 19 patients with focal epilepsy\" and \"investigated thalamocortical network dynamics.\" The title is \"Thalamocortical ictal iEEG dataset,\" and the listed task is \"seizure.\" These describe recordings of seizures, with no presented sensory stimulus or behavioral task identified.","paper_abstract_analysis":"The abstract confirms \"chronic stereo-EEG recordings from 19 patients with pediatric-onset, drug-resistant focal epilepsy\" and states that the study aimed to characterize dynamics \"from seizure onset to termination\" and classify seizure state. Neuromodulation is discussed as a potential application, not an intervention administered in this dataset. The participants overview's \"Age range: 73-73\" conflicts with the abstract's age range, but neither changes the recruited diagnosis.","evidence_alignment_check":"Pathology: Metadata SAYS \"19 patients with focal epilepsy\"; the epilepsy HFO few-shot SUGGESTS Epilepsy; ALIGN. Modality: Metadata SAYS \"intracranial EEG (iEEG) recordings\" and lists \"seizure,\" without describing delivered stimuli; the epilepsy HFO example SUGGESTS No stimulus for spontaneous clinical recordings; ALIGN, though stimulus absence is inferred rather than explicitly stated. Type: Metadata SAYS \"ictal iEEG dataset\" and \"investigated thalamocortical network dynamics\" in patients with epilepsy; the epilepsy HFO example SUGGESTS Clinical for disease-focused EEG analysis; ALIGN. There is no metadata-fact-versus-few-shot conflict.","decision_summary":"Pathology—Epilepsy versus Healthy: \"19 patients with focal epilepsy,\" \"ictal iEEG dataset,\" and \"seizure\" favor Epilepsy decisively; confidence 0.9, with a clear few-shot match. Modality—No stimulus versus Unknown: \"iEEG recordings\" and the \"seizure\" task support spontaneous recording, while no stimulus presentation is specified; No stimulus wins with confidence 0.8 based on these two features and the strong epilepsy HFO analog. Type—Clinical versus Resting-state: \"ictal iEEG dataset,\" \"thalamocortical network dynamics,\" and \"seizure\" support investigation of the condition itself, not passive rest; Clinical wins with confidence 0.9 and a clear few-shot match."}},"canonical_name":[],"name_confidence":0.74,"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":"Panchavati2026","associated_paper_meta":{"channel":"text/readme","confidence":"high","author_overlap":14,"is_oa":true,"oa_status":"green","source":"paper_resolver"},"bad_channels_info":null,"n_records":66}}