{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3439","dataset_id":"ds006126","associated_paper_doi":null,"authors":["Anthony Mensah","Gleb Perevoznyuk","Artyom Batov","Aleksandra S. Pleskovskaya"],"bids_version":"1.7.0","contact_info":["Anthony Mensah"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds006126.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":5,"ages":[22,19,30,19,30,18],"age_min":18,"age_max":30,"age_mean":23.0,"species":null,"sex_distribution":{"f":3,"m":3},"handedness_distribution":{"r":6}},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds006126","osf_url":null,"github_url":null,"paper_url":null},"funding":["Insitute for Cognitive Neuroscience - Higher School of Economics"],"ingestion_fingerprint":"56cb2565b27c951a157afaff4b49b5414229917cb1410c8410f13e71d57055bb","license":"CC0","n_contributing_labs":null,"name":"TDCS Modulation of Visual Cortex in Motor Imagery","readme":"# TDCS Neuromodulated Motor Imagery TMS Dataset\n## Research/Experiment Description\n[Your research description goes here]\n## BIDS Report\n The TDCS Modulation of Visual Cortex in Motor Imagery dataset was created by\nAnthony Mensah, Gleb Perevoznyuk, Artyom Batov, and Aleksandra S. Pleskovskaya\nand conforms to BIDS version 1.7.0. This report was generated with MNE-BIDS\n(https://doi.org/10.21105/joss.01896). The dataset consists of 5 participants\n(comprised of 3 male and 3 female participants; comprised of 6 right hand, 0\nleft hand and 0 ambidextrous; ages ranged from 18.0 to 30.0 (mean = 23.0, std =\n5.1)) and 3 recording sessions: An, Ca, and Sh. Data was recorded using an EEG\nsystem (Brain Products) sampled at 5000.0 Hz with line noise at 60.0 Hz. There\nwere 90 scans in total. Recording durations ranged from 363.7 to 2910.98 seconds\n(mean = 429.21, std = 270.19), for a total of 38629.34 seconds of data recorded\nover all scans. For each dataset, there were on average 3.0 (std = 0.0)\nrecording channels per scan, out of which 3.0 (std = 0.0) were used in analysis\n(0.0 +/- 0.0 were removed from analysis).\nReferences\n----------\nAppelhoff, 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\nPernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103.https://doi.org/10.1038/s41597-019-0104-8","recording_modality":["eeg"],"senior_author":"Aleksandra S. Pleskovskaya","sessions":["An","Ca","Sh"],"size_bytes":1159689297,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["B1","B2","BM","KI","V1","V3"],"timestamps":{"digested_at":"2026-04-22T12:29:09.508582+00:00","dataset_created_at":"2025-04-15T13:27:08.635Z","dataset_modified_at":"2025-04-15T13:41:43.000Z"},"total_files":90,"storage":{"backend":"s3","base":"s3://openneuro.org/ds006126","raw_key":"dataset_description.json","dep_keys":["CHANGES","README.md","participants.json","participants.tsv","sessions.json","sessions.tsv"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"2ec3a6bba45e217b","model":"openai/gpt-5.2","tagged_at":"2026-01-20T18:51:07.263151+00:00"},"tags":{"pathology":["Healthy"],"modality":["Motor"],"type":["Motor"],"confidence":{"pathology":0.6,"modality":0.55,"type":0.75},"reasoning":{"few_shot_analysis":"Closest few-shot match by paradigm is the \"EEG Motor Movement/Imagery Dataset\" example (Schalk et al.), which maps motor execution/imagery experiments to Type=\"Motor\" and Pathology=\"Healthy\". This convention guides labeling motor imagery datasets as Motor-type studies when the research focus is movement/imagery rather than (e.g.) perception or memory. However, that example uses explicit visual targets (therefore Modality=\"Visual\"), whereas the current dataset metadata does not clearly describe the cue/stimulus channel, so modality must be inferred more cautiously.","metadata_analysis":"Key facts available in the README:\n1) The dataset is explicitly about neuromodulation and motor imagery: \"# TDCS Neuromodulated Motor Imagery TMS Dataset\" and \"The TDCS Modulation of Visual Cortex in Motor Imagery dataset\".\n2) Participant demographics are provided but no diagnosis: \"The dataset consists of 5 participants ... ages ranged from 18.0 to 30.0\".\nNo metadata states any clinical recruitment criteria (no patient groups/diagnoses), and no task/stimulus description beyond the phrase \"Motor Imagery\" is included.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n- Metadata says: only \"5 participants\" with ages 18-30, with no diagnosis mentioned (e.g., \"The dataset consists of 5 participants...\").\n- Few-shot pattern suggests: motor imagery datasets in non-clinical volunteer samples are labeled Healthy (per the Schalk motor imagery example).\n- Alignment: ALIGN (both point to a non-clinical sample).\n\nModality:\n- Metadata says: \"TDCS Modulation of Visual Cortex in Motor Imagery\" but does not describe sensory stimuli/cues.\n- Few-shot pattern suggests: many motor imagery paradigms use visual cues (and are labeled Visual in the motor imagery example), but modality should follow explicit stimulus description.\n- Alignment: PARTIAL CONFLICT/UNCERTAINTY (few-shot suggests Visual-cue paradigms are common, but metadata does not explicitly confirm visual or auditory cues). Therefore we choose the most task-intrinsic channel (Motor) with reduced confidence.\n\nType:\n- Metadata says: \"TDCS Neuromodulated Motor Imagery\" indicating motor imagery as the core paradigm.\n- Few-shot pattern suggests: motor imagery research focus -> Type=\"Motor\" (per the Schalk example).\n- Alignment: ALIGN (clear match to Motor construct).","decision_summary":"Top-2 candidates and final choices:\n\nPathology:\n1) Healthy — Evidence: no disorder named; \"The dataset consists of 5 participants ... ages ranged from 18.0 to 30.0\"; matches few-shot convention that typical volunteer motor imagery datasets are Healthy.\n2) Unknown — Would apply if participant status were entirely unspecified; however demographics without clinical descriptors generally implies healthy volunteers.\nFinal: Healthy. (Alignment: yes)\n\nModality:\n1) Motor — Evidence: task focus is \"Motor Imagery\" (\"TDCS ... in Motor Imagery dataset\"); no explicit sensory stimulus channel described.\n2) Visual — Rationale: common motor imagery cueing is visual and the dataset mentions \"Visual Cortex\", but that phrase refers to stimulation target and does not explicitly describe presented stimuli.\nFinal: Motor. (Alignment: uncertain; chosen due to lack of explicit stimulus description)\n\nType:\n1) Motor — Evidence: repeated emphasis on \"Motor Imagery\" (\"TDCS Neuromodulated Motor Imagery\" / \"... in Motor Imagery dataset\"); few-shot motor imagery example maps to Type=Motor.\n2) Clinical/Intervention — Rationale: tDCS/TMS neuromodulation is an intervention, but the study is not described as clinical recruitment nor a treatment trial; the cognitive construct still centers on motor imagery.\nFinal: Motor. (Alignment: yes)\n\nConfidence justification is limited by sparse metadata (only a README snippet with minimal task/stimulus detail)."}},"computed_title":"TDCS Modulation of Visual Cortex in Motor Imagery","nchans_counts":[{"val":3,"count":90}],"sfreq_counts":[{"val":5000.0,"count":90}],"stats_computed_at":"2026-04-22T23:16:00.311350+00:00","total_duration_s":38629.3414,"author_year":"Mensah2025","canonical_name":null}}