{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3427","dataset_id":"ds005931","associated_paper_doi":null,"authors":["Riyo Ueda","Eishi Asano"],"bids_version":"1.7.0","contact_info":["riyo ueda"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005931.v1.0.0","datatypes":["ieeg"],"demographics":{"subjects_count":8,"ages":[11,16,20,9,16,14,15,19],"age_min":9,"age_max":20,"age_mean":15.0,"species":null,"sex_distribution":{"m":4,"f":4},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds005931","osf_url":null,"github_url":null,"paper_url":null},"funding":["N/A"],"ingestion_fingerprint":"88d538ca63c0f9562a954d2358a0000c242ca749358336c736d18eaae552be16","license":"CC0","n_contributing_labs":null,"name":"Visuomotor_task","readme":"Dataset of intracranial EEG from human epilepsy patients performing a visuomotor task\nDescription:\nWe present an electrophysiological dataset recorded from ten subjects during a visuomotor task. Subjects were epilepsy patients undergoing intracranial monitoring for localization of epileptic seizures. Subjects completed five sessions of Speed Match - a visuomotor on the Lumosity platform (https://www.lumosity.com/; Lumos Labs, Inc, San Francisco, CA) - during interictal EEG recording.\nRepository structure:\nMain directory (interictal EEG from children during gameplay): Contains interictal EEG files of each participant in the study. Folders are explained below.\nSubfolders:\nsub-/: Contains folders for each subject, named sub-.\nsub-/ses-: Contains folders for visuomotor task.\nsub-/ses-/ieeg/: Contains the raw iEEG data in .edf format for each subject. Each subject performed visuomotor task (ses-task). Each *ieeg.edf file contains continuous iEEG data during the visuomotor task. Details about the channels are given in the corresponding .tsv file. We also provide the information on the timing of the finger tapping on ieeg/edf file by specifying the start and end sample of each trial. (101 is for finger tapping).","recording_modality":["ieeg"],"senior_author":"Eishi Asano","sessions":["01","02"],"size_bytes":857380965,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["game"],"timestamps":{"digested_at":"2026-04-22T12:29:00.021362+00:00","dataset_created_at":"2025-02-18T20:31:48.897Z","dataset_modified_at":"2025-03-06T22:41:58.000Z"},"total_files":16,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005931","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"5179b7726a615552","model":"openai/gpt-5.2","tagged_at":"2026-01-20T18:44:00.627229+00:00"},"tags":{"pathology":["Epilepsy"],"modality":["Visual"],"type":["Motor"],"confidence":{"pathology":0.9,"modality":0.7,"type":0.8},"reasoning":{"few_shot_analysis":"For Pathology, the few-shot example \"Dataset of EEG recordings of pediatric patients with epilepsy\" shows the convention that explicit recruitment of epilepsy patients leads to the label Epilepsy (even if the study purpose is biomarker-related). For Type/Modality, the few-shot \"EEG Motor Movement/Imagery Dataset\" illustrates that tasks involving instructed movements (e.g., fist/foot actions) are labeled Type=Motor, while the stimulus display can still be visual; similarly here the task is explicitly \"visuomotor\" with finger tapping responses.","metadata_analysis":"Key phrases indicating epilepsy recruitment and recording context: (1) \"Dataset of intracranial EEG from human epilepsy patients\" (2) \"Subjects were epilepsy patients undergoing intracranial monitoring for localization of epileptic seizures.\" (3) \"during interictal EEG recording.\" Task/stimulus/response indicators: (4) \"performing a visuomotor task\" and \"five sessions of Speed Match - a visuomotor\" (5) \"timing of the finger tapping ... (101 is for finger tapping).\"","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata says \"human epilepsy patients\" / \"Subjects were epilepsy patients\" (ALIGN) with few-shot epilepsy example convention (epilepsy recruitment -> Epilepsy). Modality: Metadata says \"visuomotor task\" and references a screen-based Lumosity task (suggesting visual stimuli); few-shot conventions align that visuomotor/game tasks with visual displays are labeled Visual for Modality (ALIGN). Type: Metadata says \"visuomotor task\" and explicitly tracks \"finger tapping\"; few-shot motor-task convention suggests labeling Motor when movement execution is a central component (ALIGN). No conflicts requiring overrides.","decision_summary":"Top-2 candidates per category and selection.\n\nPathology candidates: (1) Epilepsy vs (2) Healthy/Unknown. Epilepsy is strongly supported by: \"intracranial EEG from human epilepsy patients\", \"Subjects were epilepsy patients undergoing intracranial monitoring\", and \"localization of epileptic seizures\"; thus Epilepsy wins (alignment: YES).\n\nModality candidates: (1) Visual vs (2) Motor. Although there is motor output (finger tapping), Modality is based on stimulus channel; \"visuomotor\" Speed Match on Lumosity implies primarily visual stimuli. Visual wins (alignment: YES).\n\nType candidates: (1) Motor vs (2) Attention/Perception. The dataset description emphasizes a \"visuomotor task\" and provides explicit trial timing for \"finger tapping\"; this fits Motor better than pure perception/attention. Motor wins (alignment: YES).\n\nConfidence justification: Pathology has 3+ explicit epilepsy quotes (high). Modality is supported by the explicit \"visuomotor\" task wording plus contextual inference about Lumosity screen stimuli (moderate). Type is supported by explicit \"visuomotor task\" plus \"finger tapping\" timing (moderately high)."}},"computed_title":"Visuomotor_task","nchans_counts":[{"val":128,"count":12},{"val":110,"count":2},{"val":112,"count":2}],"sfreq_counts":[{"val":1000.0,"count":16}],"stats_computed_at":"2026-04-22T23:16:00.311109+00:00","total_duration_s":null,"author_year":"Ueda2025","canonical_name":null}}