{"dataset":{"id":"179","dataset_id":"nm000146","name":"Motor Imagery dataset from Weibo et al 2014","description":"This dataset contains EEG recordings from 10 healthy, right-handed participants performing simple and compound limb motor imagery tasks, including imagined movements of the left hand, right hand, both hands, feet, and combined hand-foot movements, as well as rest periods. The data were collected using a 60-channel EEG system (plus EOG channels) at Tianjin University to study EEG oscillatory patterns and cognitive processes underlying motor imagery, and have been converted to BIDS format with HED event annotations by the MOABB project.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000146","concept_doi":"10.82901/nemar.nm000146","latest_version_doi":"10.82901/nemar.nm000146.v1.0.2","created_at":"2026-03-22 18:12:48","updated_at":"2026-08-18 22:07:20","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Motor Imagery dataset from Weibo et al 2014\",\n  \"description\": \"This dataset contains EEG recordings from 10 healthy, right-handed participants performing simple and compound limb motor imagery tasks, including imagined movements of the left hand, right hand, both hands, feet, and combined hand-foot movements, as well as rest periods. The data were collected using a 60-channel EEG system (plus EOG channels) at Tianjin University to study EEG oscillatory patterns and cognitive processes underlying motor imagery, and have been converted to BIDS format with HED event annotations by the MOABB project.\",\n  \"methods_description\": \"EEG data were recorded using a Neuroscan SynAmps2 system with 60 EEG channels plus 2 EOG channels, referenced to the nose with prefrontal grounding, sampled at 200 Hz with online bandpass filtering (0.5-100 Hz) and 50 Hz notch filtering. Participants performed kinesthetic motor imagery (left hand, right hand, hands, feet, left hand+right foot, right hand+left foot, and rest) cued visually with text, across 8 sections of 60 trials plus one 80-trial rest section. Preprocessing included bandpass filtering (0.5-50 Hz) and downsampling to 200 Hz.\",\n  \"license\": \"CC0-1.0\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"Weibo Yi\": {},\n    \"Shuang Qiu\": {},\n    \"Kun Wang\": {},\n    \"Hongzhi Qi\": {},\n    \"Lixin Zhang\": {},\n    \"Peng Zhou\": {},\n    \"Feng He\": {},\n    \"Dong Ming\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"motor imagery\"\n    },\n    {\n      \"term\": \"compound limb motor imagery\"\n    },\n    {\n      \"term\": \"EEG oscillatory patterns\"\n    },\n    {\n      \"term\": \"cognitive process\"\n    },\n    {\n      \"term\": \"effective connectivity\"\n    },\n    {\n      \"term\": \"Event-Related Desynchronization\"\n    },\n    {\n      \"term\": \"Event-Related Synchronization\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.1371/journal.pone.0114853\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"10.7910/DVN/27306\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000146\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/nm000146\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.21105/joss.01896\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.1038/s41597-019-0104-8\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"National Natural Science Foundation of China\",\n      \"award_number\": \"81222021, 61172008, 81171423, 51377120, 31271062\"\n    },\n    {\n      \"funder_name\": \"National Key Technology R&D Program of the Ministry of Science and Technology of China\",\n      \"award_number\": \"2012BAI34B02\"\n    },\n    {\n      \"funder_name\": \"Program for New Century Excellent Talents in University of the Ministry of Education of China\",\n      \"award_number\": \"NCET-10-0618\"\n    },\n    {\n      \"funder_name\": \"Natural Science Foundation of Tianjin\",\n      \"award_number\": \"13JCQNJC13900\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"6.1 GB (23 files)\"\n  ],\n  \"formats\": [\n    \".bdf\",\n    \".html\",\n    \".json\",\n    \".mat\",\n    \".md\",\n    \".tsv\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"a4ec0ceb3680f404c68b1f932f639b5f91d74c3b561d63b58299505b132e9009\"\n}","last_activity_at":"2026-08-18 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rate**: 200.0 Hz\n- **Number of channels**: 60\n- **Channel types**: eeg=60, eog=2, misc=2\n- **Channel names**: AF3, AF4, C1, C2, C3, C4, C5, C6, CB1, CB2, CP1, CP2, CP3, CP4, CP5, CP6, CPz, Cz, F1, F2, F3, F4, F5, F6, F7, F8, FC1, FC2, FC3, FC4, FC5, FC6, FCz, FT7, FT8, Fp1, Fp2, Fpz, Fz, HEO, O1, O2, Oz, P1, P2, P3, P4, P5, P6, P7, P8, PO3, PO4, PO5, PO6, PO7, PO8, POz, Pz, T7, T8, TP7, TP8, VEO\n- **Montage**: standard_1005\n- **Hardware**: Neuroscan SynAmps2\n- **Reference**: nose\n- **Ground**: prefrontal lobe\n- **Sensor type**: Ag/AgCl\n- **Line frequency**: 50.0 Hz\n- **Online filters**: {'bandpass': [0.5, 100], 'notch_hz': 50}\n- **Auxiliary channels**: EOG (2 ch, HEO, VEO)\n\n## Participants\n\n- **Number of subjects**: 10\n- **Health status**: healthy\n- **Age**: mean=24.0, min=23.0, max=25.0\n- **Gender distribution**: female=7, male=3\n- **Handedness**: right-handed\n- **BCI experience**: naive\n- **Species**: human\n\n## Experimental Protocol\n\n- **Paradigm**: imagery\n- **Number of classes**: 7\n- **Class labels**: left_hand, right_hand, hands, feet, left_hand_right_foot, right_hand_left_foot, rest\n- **Trial duration**: 8.0 s\n- **Study design**: Simple limb motor imagery (left hand, right hand, feet) and compound limb motor imagery (both hands, left hand combined with right foot, right hand combined with left foot)\n- **Feedback type**: none\n- **Stimulus type**: text cues\n- **Stimulus modalities**: visual\n- **Primary modality**: visual\n- **Synchronicity**: synchronous\n- **Mode**: offline\n- **Instructions**: Participants were asked to perform kinesthetic motor imagery rather than a visual type of imagery while avoiding any muscle movement\n\n## HED Event Annotations\n\nSchema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n\n```\n  left_hand\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       └─ Imagine\n          ├─ Move\n          └─ Left, Hand\n\n  right_hand\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       └─ Imagine\n          ├─ Move\n          └─ Right, Hand\n\n  hands\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       └─ Imagine, Move, Hand\n\n  feet\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       └─ Imagine, Move, Foot\n\n  left_hand_right_foot\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       ├─ Imagine\n       │  ├─ Move\n       │  └─ Left, Hand\n       └─ Imagine\n          ├─ Move\n          └─ Right, Foot\n\n  right_hand_left_foot\n    ├─ Sensory-event, Experimental-stimulus, Visual-presentation\n    └─ Agent-action\n       ├─ Imagine\n       │  ├─ Move\n       │  └─ Right, Hand\n       └─ Imagine\n          ├─ Move\n          └─ Left, Foot\n\n  rest\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Rest\n\n```\n## Paradigm-Specific Parameters\n\n- **Detected paradigm**: motor_imagery\n- **Imagery tasks**: left_hand, right_hand, feet, both_hands, left_hand_right_foot, right_hand_left_foot\n- **Cue duration**: 1.0 s\n- **Imagery duration**: 4.0 s\n\n## Data Structure\n\n- **Trials**: 560\n- **Trials context**: 8 sections with 60 trials each (10 trials per MI task per section) for 6 MI tasks, plus 1 section with 80 trials for rest state\n\n## Preprocessing\n\n- **Data state**: preprocessed\n- **Preprocessing applied**: True\n- **Steps**: bandpass filtering, downsampling\n- **Highpass filter**: 0.5 Hz\n- **Lowpass filter**: 50.0 Hz\n- **Bandpass filter**: {'low_cutoff_hz': 0.5, 'high_cutoff_hz': 50.0}\n- **Re-reference**: nose\n- **Downsampled to**: 200.0 Hz\n\n## Signal Processing\n\n- **Feature extraction**: Bandpower, ERD, ERS, ERSP, Time-Frequency, AR, DTF, PLV\n- **Frequency bands**: theta=[4.0, 5.0] Hz; alpha=[8.0, 13.0] Hz; beta=[13.0, 30.0] Hz; analyzed=[1.0, 40.0] Hz\n\n## BCI Application\n\n- **Applications**: motor_control\n- **Environment**: laboratory\n\n## Tags\n\n- **Pathology**: Healthy\n- **Modality**: Motor\n- **Type**: Research\n\n## Documentation\n\n- **DOI**: 10.1371/journal.pone.0114853\n- **License**: CC0-1.0\n- **Investigators**: Weibo Yi, Shuang Qiu, Kun Wang, Hongzhi Qi, Lixin Zhang, Peng Zhou, Feng He, Dong Ming\n- **Senior author**: Dong Ming\n- **Contact**: qhz@tju.edu.cn; richardming@tju.edu.cn\n- **Institution**: Tianjin University\n- **Department**: Department of Biomedical Engineering\n- **Country**: CN\n- **Repository**: Harvard Dataverse Database\n- **Data URL**: http://dx.doi.org/10.7910/DVN/27306\n- **Publication year**: 2014\n- **Funding**: National Natural Science Foundation of China (No. 81222021, 61172008, 81171423, 51377120, 31271062); National Key Technology R&D Program of the Ministry of Science and Technology of China (No. 2012BAI34B02); Program for New Century Excellent Talents in University of the Ministry of Education of China (No. NCET-10-0618); Natural Science Foundation of Tianjin (No. 13JCQNJC13900)\n- **Ethics approval**: Ethical committee of Tianjin University\n- **Keywords**: motor imagery, compound limb motor imagery, EEG oscillatory patterns, cognitive process, effective connectivity, ERD, ERS\n\n## References\n\nYi, Weibo, et al. \"Evaluation of EEG oscillatory patterns and cognitive process during simple and compound limb motor imagery.\" PloS one 9.12 (2014). https://doi.org/10.1371/journal.pone.0114853\nAppelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Hochenberger, 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\n\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. 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