{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3436","dataset_id":"ds006095","associated_paper_doi":null,"authors":["Chang Liu","Erika M. Pliner","Jacob S. Salminen","Ryan Downey","Jungyun Hwang","Akraprava Roy","Ryland Swearinger","Natalie Richer","Chris J. Hass","David J. Clark","Todd M. Manini","Yenisel Cruz-Almeida","Rachael D. Seidler","Daniel P. Ferris"],"bids_version":"v1.0.0","contact_info":["Chang Liu"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds006095.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":71,"ages":[81,78,84,74,72,73,74,77,76,71,77,82,79,75,81,73,72,73,73,75,74,71,65,76,68,67,66,69,64,83,88,82,80,66,72,70,79,67,81,78,73,79,79,70,80,79,70,69,70,74,67,80,72,66,65,84,82,78,90,77,72,69,77,77,68,71,72,75,81,81,68],"age_min":64,"age_max":90,"age_mean":74.66197183098592,"species":null,"sex_distribution":{"f":40,"m":31},"handedness_distribution":{"r":65,"l":5}},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds006095","osf_url":null,"github_url":null,"paper_url":null},"funding":["This study was supported by the National Institute of Health (U01AG061389)."],"ingestion_fingerprint":"283840047980552c910458505e4fa2dc75e380f7e6c1bdd69cd7ac74ff5691dc","license":"CC0","n_contributing_labs":null,"name":"Mind in Motion Older Adults Walking Over Uneven Terrain","readme":"Our dataset contains high-density, dual-layer electroencephalography (EEG), neck electromyography (EMG), inertial measurement unit (IMU) acceleration, ground reaction force from all participants walking over uneven terrain and at different speeds. Participants completed two trials for each condition for three minutes and a seated rest trial for three minutes. Please refer to our publication for more detail. Digitized electrode locations (txt) are included in each subject folder.","recording_modality":["eeg"],"senior_author":"Daniel P. Ferris","sessions":[],"size_bytes":139411715731,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["0p25","0p5","0p75","1p0","Rest","flat","high","low","med"],"timestamps":{"digested_at":"2026-04-22T12:29:05.231171+00:00","dataset_created_at":"2025-04-06T21:09:56.098Z","dataset_modified_at":"2025-04-07T01:15:10.000Z"},"total_files":1182,"storage":{"backend":"s3","base":"s3://openneuro.org/ds006095","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv","task-flat_events.json"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"d3555c0befec35c2","model":"openai/gpt-5.2","tagged_at":"2026-01-20T18:49:58.759805+00:00"},"tags":{"pathology":["Healthy"],"modality":["Motor"],"type":["Motor"],"confidence":{"pathology":0.7,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"Most similar few-shot by paradigm is the “EEG Motor Movement/Imagery Dataset” example, where the core experimental manipulation is movement execution/imagery and it is labeled Type=Motor. That convention supports labeling this dataset’s primary purpose as Motor because the metadata centers on walking over terrain/speed conditions. A secondary relevant convention is that when there is no dominant external sensory stimulation described (no tones/images), movement itself can be treated as the dominant modality (Motor) rather than Visual/Auditory.","metadata_analysis":"Key task/manipulation facts from the README: (1) “EEG... from all participants walking over uneven terrain and at different speeds.” This indicates locomotion/movement execution is the core condition. (2) “Participants completed two trials for each condition for three minutes and a seated rest trial for three minutes.” This indicates an added baseline rest trial but the main dataset revolves around walking conditions. No clinical diagnosis or patient group is mentioned anywhere in the provided metadata.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata says nothing about any diagnosis (e.g., only “all participants” with no clinical descriptors). Few-shot patterns suggest that absent any clinical recruitment language, label as Healthy rather than a disease category. ALIGN (no conflict).\nModality: Metadata says the main experimental condition is “walking over uneven terrain and at different speeds,” with no mention of visual/auditory/tactile stimuli. Few-shot convention for movement-focused paradigms supports Motor modality when movement is the primary manipulated input/behavior and no dominant sensory stimulus is described. ALIGN.\nType: Metadata emphasizes gait/walking across conditions and includes biomechanics sensors (EMG, IMU, ground reaction force), consistent with a locomotion/movement study. Few-shot motor-task example supports Type=Motor when movement execution/imagery is the study focus. ALIGN.","decision_summary":"Pathology top-2: (1) Healthy — supported by lack of any clinical recruitment language (quote: “from all participants walking...”), consistent with few-shot convention to label normative cohorts as Healthy. (2) Unknown — plausible because health status is not explicitly stated. Final=Healthy because datasets typically state a disorder if present; here none is stated. Confidence=0.7 (one clear absence-of-pathology inference, but no explicit “healthy” statement).\nModality top-2: (1) Motor — supported by “walking over uneven terrain and at different speeds” and the movement/locomotion instrumentation (EMG/IMU/forces), plus few-shot motor-paradigm convention. (2) Other — possible if one treats this as not stimulus-driven. Final=Motor. Confidence=0.8 (2 quoted task facts + strong few-shot analog).\nType top-2: (1) Motor — primary manipulation is walking speed/terrain; gait execution is central. (2) Resting-state — there is “a seated rest trial,” but it is described as one trial/baseline rather than the main purpose. Final=Motor. Confidence=0.8 (2 quoted task facts + strong few-shot analog)."}},"computed_title":"Mind in Motion Older Adults Walking Over Uneven Terrain","nchans_counts":[{"val":284,"count":1053},{"val":310,"count":115},{"val":336,"count":14}],"sfreq_counts":[{"val":500.0,"count":1182}],"stats_computed_at":"2026-04-22T23:16:00.311302+00:00","total_duration_s":219948.68,"author_year":"Liu2025_Mind_Motion_Older","canonical_name":null}}