{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a33a7","dataset_id":"ds004977","associated_paper_doi":null,"authors":["Harvey Huang","Gabriela Ojeda Valencia","Nicholas M Gregg","Gamaleldin M Osman","Morgan N Montoya","Gregory A Worrell","Kai J Miller","Dora Hermes"],"bids_version":"v 1.14.0","contact_info":["Harvey Huang"],"contributing_labs":null,"data_processed":true,"dataset_doi":"doi:10.18112/openneuro.ds004977.v1.2.0","datatypes":["ieeg"],"demographics":{"subjects_count":4,"ages":[18,19,19,16],"age_min":16,"age_max":19,"age_mean":18.0,"species":null,"sex_distribution":{"m":2,"f":2},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds004977","osf_url":null,"github_url":null,"paper_url":null},"funding":["R01 MH122258 CRCNS: Processing speed in the human connectome across the lifespan","T32 GM145408: Medical Scientist Training Program at Mayo Clinic","937450: AES Predoctoral Research Fellowship"],"ingestion_fingerprint":"8d8357d4dab560189cb8bc625770616e937163e8b0aed81deda777f64ba9545a","license":"CC0","n_contributing_labs":null,"name":"CARLA: Adjusted common average referencing for cortico-cortical evoked potential data","readme":"# CARLA: Adjusted common average referencing for cortico-cortical evoked potential data\nThis dataset contains intracranial EEG recordings from four patients during single pulse electrical stimulation as described in:\n* H Huang, G Ojeda Valencia, NM Gregg, GM Osman, MN Montoya, GA Worrell, KJ Miller, and D Hermes. (2024). CARLA: Adjusted common average referencing for cortico-cortical evoked potential data. Journal of Neuroscience Methods, 110153. DOI: https://doi.org/10.1016/j.jneumeth.2024.110153.\nCurrently, this dataset contains the raw data needed to generate all results EXCEPT for those pertaining to figures 7 and 8 (unavailable data samples are censored with 0). The complete data are currently being used to answer other scientific questions, and will be released in time with other manuscripts.\nPlease cite this work when using the data. These data were recorded at the Mayo Clinic in Rochester, MN, as part of the NIH Brain Initiative supported project R01 MH122258 \"CRCNS: Processing speed in the human connectome across the lifespan\". Research reported in this publication was supported by the National Institute Of Mental Health of the National Institutes of Health under Award Number R01MH122258, by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number T32GM145408, and by the American Epilepsy Society under award number 937450. The project was also supported by the Mayo Clinic DERIVE Office and the Mayo Clinic Center for Biomedical Discovery. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The data were collected by Harvey Huang, Dora Hermes, Nicholas M. Gregg, Gamaleldin M. Osman, and Cindy Nelson. The BIDS formatting was performed by Harvey Huang, Dora Hermes, Gabriela Ojeda Valencia, and Morgan Montoya. The iEEG data collection was facilitated by Gregory A. Worrell and Kai J. Miller.\nData can be analyzed using the Matlab code at:\n* https://github.com/hharveygit/CARLA_JNM\n## Format\nData are formatted according to BIDS version 1.14.0\n## Single pulse stimulation\nThe patient were resting in the hospital bed, while single pulse stimulation was performed with a frequency of ~0.2 Hz. The stimulation had a duration of 200 microseconds, was biphasic and had an amplitude of 6mA.\n## Contact\nPlease contact Harvey Huang (huang.harvey@mayo.edu) or Dora Hermes (hermes.dora@mayo.edu) for questions.","recording_modality":["ieeg"],"senior_author":"Dora Hermes","sessions":["ieeg01"],"size_bytes":1604950022,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["ccep"],"timestamps":{"digested_at":"2026-04-21T23:07:38.527127+00:00","dataset_created_at":"2024-02-19T19:52:02.163Z","dataset_modified_at":"2024-05-13T17:47:41.000Z"},"total_files":6,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004977","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.tsv","task-ccep_events.json"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"f8ffddd124ce516e","model":"openai/gpt-5.2","tagged_at":"2026-01-20T17:38:10.497229+00:00"},"tags":{"pathology":["Epilepsy"],"modality":["Other"],"type":["Other"],"confidence":{"pathology":0.65,"modality":0.8,"type":0.6},"reasoning":{"few_shot_analysis":"Closest few-shot by paradigm is the intraoperative stimulation/SEP dataset (\"Intraoperative EEG dataset during medianus-tibialis stimulation...\") which was labeled Modality=Other and Type=Other, reflecting that the primary 'input' is electrical stimulation rather than a classic sensory (visual/auditory/tactile) stimulus. Another relevant few-shot is the pediatric epilepsy dataset labeled Pathology=Epilepsy, showing that when recordings come from clinical intracranial/sleep EEG collected for epilepsy-related contexts, Epilepsy is the appropriate pathology label when supported by metadata. These examples guide (a) mapping stimulation paradigms to Modality=Other, and (b) mapping patient EEG acquired in epilepsy clinical contexts to Pathology=Epilepsy when evidenced.","metadata_analysis":"Key metadata indicating intracranial stimulation paradigm and patient context: (1) \"This dataset contains intracranial EEG recordings from four patients during single pulse electrical stimulation\" (defines iEEG + stimulation, and that participants are patients). (2) \"The patient were resting in the hospital bed, while single pulse stimulation was performed with a frequency of ~0.2 Hz.\" (clinical bedside context; not a cognitive task). (3) \"...cortico-cortical evoked potential data\" (CCEPs are typically obtained via intracranial stimulation in clinical patients). (4) Funding/support context includes \"American Epilepsy Society\" and involvement of epilepsy/iEEG clinicians (e.g., \"The iEEG data collection was facilitated by Gregory A. Worrell and Kai J. Miller\"), which supports (but does not explicitly state) an epilepsy presurgical monitoring population.","paper_abstract_analysis":"No useful paper information (abstract text not provided in the input).","evidence_alignment_check":"Pathology: Metadata SAYS \"intracranial EEG recordings from four patients\" but does not explicitly name epilepsy; it also mentions \"American Epilepsy Society\" support and typical epilepsy iEEG investigators, which suggests epilepsy but is not a direct diagnosis statement. Few-shot pattern SUGGESTS that clinically-acquired iEEG/stimulation datasets are often epilepsy-related (aligns weakly). No direct conflict; decision is inference-based.\n\nModality: Metadata SAYS \"single pulse electrical stimulation\" and \"cortico-cortical evoked potential\" (non-sensory, direct stimulation). Few-shot pattern (intraoperative stimulation/SEP example) SUGGESTS Modality=Other for electrical stimulation paradigms. ALIGN.\n\nType: Metadata SAYS this is about \"Adjusted common average referencing for cortico-cortical evoked potential data\" and describes stimulation during rest in hospital bed (methodological/clinical mapping rather than a standard cognitive construct task). Few-shot pattern (intraoperative stimulation/SEP example) SUGGESTS Type=Other for stimulation/evoked-potential optimization datasets; an alternative few-shot convention is using Clinical/Intervention for strongly clinical cohort studies, but here the main aim is a methods paper rather than disease characterization. Mostly ALIGN with Type=Other; slight ambiguity with Clinical/Intervention.","decision_summary":"Pathology (top-2): (A) Epilepsy — supported indirectly by iEEG patient context and epilepsy-linked support: \"intracranial EEG recordings from four patients\" + \"single pulse electrical stimulation\" (typical CCEP in epilepsy monitoring) + \"American Epilepsy Society\" and epilepsy iEEG investigators. (B) Unknown — because no explicit diagnosis term appears. Winner: Epilepsy (inference stronger than pure unknown, but not explicit). Alignment: partial (inference).\n\nModality (top-2): (A) Other — \"single pulse electrical stimulation\" / CCEP is not visual/auditory/tactile/motor. (B) Resting State — patient resting, but stimulation is the dominant input. Winner: Other. Alignment: strong with few-shot stimulation example.\n\nType (top-2): (A) Other — methods-focused CCEP referencing; no cognitive construct task (\"CARLA: Adjusted common average referencing...\"). (B) Clinical/Intervention — clinical iEEG stimulation data in patients. Winner: Other, because the primary purpose is methodological signal processing rather than clinical outcome/diagnosis study. Alignment: mostly aligns with few-shot stimulation/SEP convention.\n\nConfidence justification: Pathology confidence limited because epilepsy is not explicitly stated; Modality confidence higher due to explicit stimulation description; Type confidence moderate due to ambiguity between methodological 'Other' vs 'Clinical/Intervention'."}},"nemar_citation_count":2,"computed_title":"CARLA: Adjusted common average referencing for cortico-cortical evoked potential data","nchans_counts":[{"val":273,"count":4},{"val":232,"count":1},{"val":152,"count":1}],"sfreq_counts":[{"val":4800.0,"count":6}],"stats_computed_at":"2026-04-21T23:17:03.730949+00:00","total_duration_s":3150.2999999999997,"canonical_name":null,"name_confidence":0.93,"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":"Huang2024"}}