{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a33ab","dataset_id":"ds004998","associated_paper_doi":null,"authors":["Fayed Rassoulou","Alexandra Steina","Christian J. Hartmann","Jan Vesper","Markus Butz","Alfons Schnitzler","Jan Hirschmann"],"bids_version":"1.6.0","contact_info":["Fayed Rassoulou"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004998.v1.2.2","datatypes":["meg"],"demographics":{"subjects_count":20,"ages":[48,60,69,53,53,64,61,54,62,70,66,71,72,70,68,62,76,69,53,62,54,70],"age_min":48,"age_max":76,"age_mean":63.04545454545455,"species":null,"sex_distribution":{"m":16,"f":6},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds004998","osf_url":null,"github_url":null,"paper_url":null},"funding":["The project was funded by ERA-NET Neuron for 3 years."],"ingestion_fingerprint":"08c9a2d46904c3308adcd1b93e0501c67ead335a092d1cab3b963ddbb81c55b1","license":"CC0","n_contributing_labs":null,"name":"Exploring the electrophysiology of Parkinson's disease - magnetoencephalography combined with deep brain recordings from the subthalamic nucleus. ","readme":"This dataset contains data from externalized DBS patients undergoing simultaneous MEG - STN LFP recordings with (MedOn) and without (MedOn) dopaminergic medication. It has two movement conditions: 1) 5 min of rest followed by static forearm extension (hold) and 2) 5 min of rest followed by self-paced fist-clenching (move). The movement parts contain pauses. Some patients were recorded in resting-state only (rest). The project aimed to understand the neurophysiology of basal ganglia-cortex loops and its modulation by movement and medication.\nCode for quickly start is available here:\nhttps://github.com/Fayed-Rsl/RHM_preprocessing\nReferences\n----------\nRassoulou, F., Steina, A., Hartmann, C. J., Vesper, J., Butz, M., Schnitzler, A., & Hirschmann, J. (2024). Exploring the electrophysiology of Parkinson's disease with magnetoencephalography and deep brain recordings. Scientific data, 11(1), 889. https://doi.org/10.1038/s41597-024-03768-1\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\nNiso, G., Gorgolewski, K. J., Bock, E., Brooks, T. L., Flandin, G., Gramfort, A., Henson, R. N., Jas, M., Litvak, V., Moreau, J., Oostenveld, R., Schoffelen, J., Tadel, F., Wexler, J., Baillet, S. (2018). MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Scientific Data, 5, 180110. https://doi.org/10.1038/sdata.2018.110","recording_modality":["meg"],"senior_author":"Jan Hirschmann","sessions":["PeriOp"],"size_bytes":173691728283,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["HoldL","HoldR","MoveL","MoveR","Rest","noise"],"timestamps":{"digested_at":"2026-04-22T12:27:12.090867+00:00","dataset_created_at":"2024-03-04T17:45:27.695Z","dataset_modified_at":"2024-09-09T08:26:28.000Z"},"total_files":145,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004998","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv","participants_updrs_off.tsv","participants_updrs_on.tsv"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"226d33f4d21e9293","model":"openai/gpt-5.2","tagged_at":"2026-01-20T17:39:08.988570+00:00"},"tags":{"pathology":["Parkinson's"],"modality":["Motor"],"type":["Motor"],"confidence":{"pathology":0.8,"modality":0.85,"type":0.8},"reasoning":{"few_shot_analysis":"Most similar few-shot examples are the Parkinson’s datasets: (1) “Cross-modal Oddball Task.” labeled Pathology=Parkinson's, showing that when metadata explicitly mentions Parkinson’s disease patients, the pathology label should be Parkinson's; and (2) “EEG: Reinforcement Learning in Parkinson's” also labeled Pathology=Parkinson's, demonstrating the same convention even when there are medication ON/OFF sessions. These guide mapping of a dopaminergic medication manipulation in a DBS cohort to Parkinson's. For Modality/Type, the motor-movement convention is illustrated by the “EEG Motor Movement/Imagery Dataset” (Healthy; Modality=Visual; Type=Motor): despite visual cues, the research focus is movement/imagery → Type=Motor. In the current dataset, the task is explicitly movement (fist clenching/forearm extension), so Motor is the closest match for Type, and Motor is also the dominant “input/condition” channel (movement condition rather than sensory stimulus).","metadata_analysis":"Key facts from the provided README include: (1) clinical/DBS + PD context: \"This dataset contains data from externalized DBS patients\" and the citation \"Exploring the electrophysiology of Parkinson's disease with magnetoencephalography and deep brain recordings.\" (2) medication manipulation: \"with (MedOn) and without (MedOn) dopaminergic medication\" (interpreting as with/without dopaminergic medication). (3) task/conditions are movement-focused: \"It has two movement conditions\" and specifically \"static forearm extension (hold)\" and \"self-paced fist-clenching (move).\" (4) resting included but embedded in movement blocks: \"1) 5 min of rest followed by...\" and \"2) 5 min of rest followed by...\" and \"Some patients were recorded in resting-state only (rest).\"","paper_abstract_analysis":"No useful paper information (abstract text not provided in the input).","evidence_alignment_check":"Pathology: Metadata says PD explicitly via the referenced paper title: \"Parkinson's disease\" and describes a DBS patient cohort (\"externalized DBS patients\") with dopaminergic medication manipulation. Few-shot pattern suggests Parkinson's for PD cohorts (e.g., Cross-modal Oddball Task; Reinforcement Learning in Parkinson's). ALIGN.\nModality: Metadata says participants perform movement conditions: \"static forearm extension\" and \"self-paced fist-clenching.\" Few-shot pattern suggests that when the paradigm is movement execution/imagery, Motor is appropriate as the dominant modality/condition channel. ALIGN (Resting State is present but secondary/embedded).\nType: Metadata says the study aims to understand physiology \"modulation by movement and medication\" and includes explicit movement tasks. Few-shot pattern suggests movement-focused paradigms map to Type=Motor (cf. Motor Movement/Imagery dataset). ALIGN (runner-up would be Clinical/Intervention due to PD+medication, but the task focus is movement modulation).","decision_summary":"Top-2 candidates:\n- Pathology: (A) Parkinson's vs (B) Other/Unknown. Evidence for Parkinson's: \"externalized DBS patients... dopaminergic medication\" plus explicit PD citation \"Parkinson's disease\". Few-shot PD examples map such cohorts to Parkinson's. Final: Parkinson's. Confidence supported by 2 explicit PD/clinical quotes.\n- Modality: (A) Motor vs (B) Resting State. Evidence for Motor: \"two movement conditions\"; \"static forearm extension\"; \"self-paced fist-clenching\". Evidence for Resting State: \"5 min of rest\" and \"Some patients were recorded in resting-state only\". Head-to-head: Motor is dominant because the primary experimental manipulations are movement (hold/move) and rest is a baseline segment. Final: Motor.\n- Type: (A) Motor vs (B) Clinical/Intervention. Evidence for Motor: explicit movement tasks and aim of modulation by movement. Evidence for Clinical/Intervention: PD cohort with dopaminergic medication ON/OFF. Head-to-head: Motor is stronger because the cognitive/behavioral construct studied is movement-related neurophysiology (basal ganglia-cortex loops during movement), with medication as an additional factor rather than the sole clinical endpoint. Final: Motor.\nConfidence justification quotes/features: Pathology uses \"Parkinson's disease\" (citation) + \"externalized DBS patients\" + \"dopaminergic medication\"; Modality/Type use \"two movement conditions\", \"static forearm extension\", \"self-paced fist-clenching\" with rest as secondary."}},"nemar_citation_count":1,"computed_title":"Exploring the electrophysiology of Parkinson's disease - magnetoencephalography combined with deep brain recordings from the subthalamic nucleus.","nchans_counts":[{"val":323,"count":122},{"val":333,"count":6},{"val":326,"count":6},{"val":324,"count":6},{"val":347,"count":4},{"val":319,"count":1}],"sfreq_counts":[{"val":2000.0,"count":85}],"stats_computed_at":"2026-04-22T23:16:00.308808+00:00","total_duration_s":38759.957,"author_year":"Rassoulou2024","canonical_name":null}}