{"dataset":{"id":"61223","dataset_id":"on007221","name":"Cross-Environment Multi-Paradigm Motor Imagery EEG Dataset","description":"This dataset comprises EEG recordings from 84 healthy participants performing motor imagery tasks across multiple paradigms (Graz motor imagery, SSMVEP-MI, and hybrid video/SSVideo paradigms) in two distinct recording environments: a controlled electromagnetically shielded laboratory and a simulated multi-sensory hospital setting. A supplementary dataset from 3 participants recorded in a space station environment is also included, extending the study to microgravity conditions. The dataset is intended to support research on cross-environment robustness, cross-subject decoding, and benchmarking of EEG-based brain-computer interface algorithms.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on007221","concept_doi":"10.82901/nemar.on007221","latest_version_doi":"10.82901/nemar.on007221.v1.0.0","created_at":"2026-06-30 03:31:10","updated_at":"2026-08-18 23:58:37","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Cross-Environment Multi-Paradigm Motor Imagery EEG Dataset\",\n  \"description\": \"This dataset comprises EEG recordings from 84 healthy participants performing motor imagery tasks across multiple paradigms (Graz motor imagery, SSMVEP-MI, and hybrid video/SSVideo paradigms) in two distinct recording environments: a controlled electromagnetically shielded laboratory and a simulated multi-sensory hospital setting. A supplementary dataset from 3 participants recorded in a space station environment is also included, extending the study to microgravity conditions. The dataset is intended to support research on cross-environment robustness, cross-subject decoding, and benchmarking of EEG-based brain-computer interface algorithms.\",\n  \"methods_description\": \"EEG was recorded using a 64-channel system following the 10-20 electrode arrangement (60 channels used) at a sampling rate of 1000 Hz (raw) and 250 Hz (processed) for the main laboratory and hospital datasets. Each trial included a cue period (-2 to 0 s), a task period (0 to 4 s), and a rest period (4 s). The supplementary space station dataset was recorded using a 32-channel dry-electrode EGGO system and stored in MATLAB .mat format.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Sun Xinwei\": {},\n    \"Wang Kun\": {},\n    \"Pan Lincong\": {},\n    \"Cao Yupei\": {},\n    \"Meng Lin\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"Electroencephalography\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D004569\"\n    },\n    {\n      \"term\": \"motor imagery\"\n    },\n    {\n      \"term\": \"Brain-Computer Interfaces\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D062207\"\n    },\n    {\n      \"term\": \"cross-environment analysis\"\n    },\n    {\n      \"term\": \"SSMVEP paradigm\"\n    },\n    {\n      \"term\": \"space station EEG\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on007221\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on007221\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds007221.v1.0.1\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds007221\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"Not externally funded\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"153.2 GB (4333 files)\"\n  ],\n  \"formats\": [\n    \".eeg\",\n    \".json\",\n    \".mat\",\n    \".md\",\n    \".tsv\",\n    \".txt\",\n    \".vhdr\",\n    \".vmrk\",\n    \".yml\"\n  ],\n  \"source_hash\": \"b1bcf7b4b38694d58eeddfe3aa35a132f9ded51bc7849003dac68cab115b7b53\"\n}","last_activity_at":"2026-06-30 03:31:10","source":"openneuro","source_id":"ds007221","subject_count":84,"modalities":"eeg","age_min":20,"age_max":32,"file_size":154154441728,"total_files":10623,"tasks":"graz,hybrid,hybridonline,ssmvepmi","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Sun Xinwei, Wang Kun, Pan Lincong, Cao Yupei, Meng Lin","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on007221-blue)](https://doi.org/10.82901/nemar.on007221)\n\n# Cross-Environment Multi-Paradigm Motor Imagery EEG Dataset\n# Description\nThis dataset contains EEG recordings collected during motor imagery (MI) tasks under different recording environments. The primary dataset includes recordings from a controlled laboratory setting and a simulated hospital environment, designed to investigate the impact of environmental variability on EEG-based brain–computer interface (BCI) performance.In addition, a small supplementary dataset recorded in a space station environment is provided, extending the dataset to a non-terrestrial recording condition.\n\n# Participants\nMain dataset: 84 healthy participants\nSupplementary dataset: 3 participants (space station environment)\nAll participants completed motor imagery tasks following similar experimental protocols.\n\n# Experimental Design\n# Recording Environments\nLaboratory environment: electromagnetically shielded, low-noise condition\nSimulated hospital environment: multi-sensory setup including visual, auditory, and contextual elements\nSpace station environment (supplementary): microgravity condition with distinct acquisition setup\n\n# Motor Imagery Tasks\nTasks include:\nLeft-hand motor imagery\nRight-hand motor imagery\nResting state (space station dataset only)\n\n# Paradigms\nThe main dataset includes multiple paradigms:\nGraz motor imagery paradigm\nSSMVEP-MI paradigm\nHybrid paradigms (including video and SSVideo conditions)\n\n# Trial Structure\nEach trial consists of:\nCue period: −2 to 0 s\nTask period: 0 to 4 s\nRest period: 4 s\n\n# Data Format\nMain Dataset\nOrganized in BIDS format\nSpace Station Dataset (Supplementary)\nFormat: MATLAB .mat files\n\n# EEG Recording\nMain Dataset\n64-channel EEG system (10–20 system)\n60 channels used\nSampling rate:\nRaw: 1000 Hz\nProcessed: 250 Hz\nSpace Station Dataset\nEGGO system\n32 dry electrodes\nData stored directly in .mat format\n\n# This dataset can be used for:\nMotor imagery BCI algorithm development\nCross-subject decoding\nCross-environment analysis\nRobustness evaluation under different recording conditions\nBenchmarking EEG signal processing methods\n# Citation\nIf you use this dataset, please cite:\nCross-Environment Multi-Paradigm Motor Imagery EEG Dataset, Sun Xinwei, Wang Kun, Cao Yupei, OpenNeuro, Version 1.0.0  \nDOI: https://openneuro.org/datasets/ds007221\nA related manuscript describing this dataset is currently under review.\n\n# Notes\nThe main dataset (84 participants) is designed for systematic analysis across environments.The space station dataset is provided as a supplementary resource due to its different acquisition setup and limited sample size.\n\n# License\nThis dataset is released under an open-access license. Please refer to the repository for details.\n\n## Recording Summary\n| Subject | Session | Task | Acquisition | Run | Trials | Fs (Hz) | Ch | Duration (s) | Line Freq | Ref | Events | File |\n|----------|----------|------|--------------|------|----------|---------|------|--------------|-----------|------|---------|------|\n| sub-01 | ses-01 | graz | N/A | 1 | 40 | 1000.0 | 69 | 342.7 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-01_task-graz_run-01 |\n| sub-01 | ses-01 | graz | N/A | 2 | 40 | 1000.0 | 69 | 342.4 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-01_task-graz_run-02 |\n| sub-01 | ses-01 | graz | N/A | 3 | 40 | 1000.0 | 69 | 331.3 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-01_task-graz_run-03 |\n| sub-01 | ses-01 | graz | N/A | 4 | 40 | 1000.0 | 69 | 330.6 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-01_task-graz_run-04 |\n| sub-01 | ses-01 | graz | N/A | 5 | 40 | 1000.0 | 69 | 331.7 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-01_task-graz_run-05 |\n| sub-01 | ses-01 | graz | N/A | 6 | 40 | 1000.0 | 69 | 331.8 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-01_task-graz_run-06 |\n| sub-01 | ses-02 | graz | N/A | 1 | 40 | 1000.0 | 69 | 349.8 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-02_task-graz_run-01 |\n| sub-01 | ses-02 | graz | N/A | 2 | 40 | 1000.0 | 69 | 337.8 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-02_task-graz_run-02 |\n| sub-01 | ses-02 | graz | N/A | 3 | 40 | 1000.0 | 69 | 332.9 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-02_task-graz_run-03 |\n| sub-01 | ses-02 | graz | N/A | 4 | 40 | 1000.0 | 69 | 332.2 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-02_task-graz_run-04 |\n| sub-01 | ses-02 | graz | N/A | 5 | 40 | 1000.0 | 69 | 332.6 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-02_task-graz_run-05 |\n| sub-01 | ses-02 | graz | N/A | 6 | 40 | 1000.0 | 69 | 334.0 | 50 | nose | left_hand,right_hand,feet,rest | sub-01_ses-02_task-graz_run-06 |\n| sub-02 | ses-01 | graz | N/A | 1 | 40 | 1000.0 | 69 | 336.5 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-01_task-graz_run-01 |\n| sub-02 | ses-01 | graz | N/A | 2 | 40 | 1000.0 | 69 | 333.9 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-01_task-graz_run-02 |\n| sub-02 | ses-01 | graz | N/A | 3 | 40 | 1000.0 | 69 | 333.2 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-01_task-graz_run-03 |\n| sub-02 | ses-01 | graz | N/A | 4 | 40 | 1000.0 | 69 | 331.1 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-01_task-graz_run-04 |\n| sub-02 | ses-01 | graz | N/A | 5 | 40 | 1000.0 | 69 | 331.2 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-01_task-graz_run-05 |\n| sub-02 | ses-01 | graz | N/A | 6 | 40 | 1000.0 | 69 | 335.6 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-01_task-graz_run-06 |\n| sub-02 | ses-02 | graz | N/A | 1 | 40 | 1000.0 | 69 | 331.5 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-02_task-graz_run-01 |\n| sub-02 | ses-02 | graz | N/A | 2 | 40 | 1000.0 | 69 | 339.1 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-02_task-graz_run-02 |\n| sub-02 | ses-02 | graz | N/A | 3 | 40 | 1000.0 | 69 | 331.6 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-02_task-graz_run-03 |\n| sub-02 | ses-02 | graz | N/A | 4 | 40 | 1000.0 | 69 | 328.6 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-02_task-graz_run-04 |\n| sub-02 | ses-02 | graz | N/A | 5 | 40 | 1000.0 | 69 | 352.7 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-02_task-graz_run-05 |\n| sub-02 | ses-02 | graz | N/A | 6 | 40 | 1000.0 | 69 | 330.9 | 50 | nose | left_hand,right_hand,feet,rest | sub-02_ses-02_task-graz_run-06 |\n| sub-03 | ses-01 | graz | N/A | 1 | 40 | 1000.0 | 69 | 372.1 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-01_task-graz_run-01 |\n| sub-03 | ses-01 | graz | N/A | 2 | 40 | 1000.0 | 69 | 374.1 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-01_task-graz_run-02 |\n| sub-03 | ses-01 | graz | N/A | 3 | 40 | 1000.0 | 69 | 371.1 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-01_task-graz_run-03 |\n| sub-03 | ses-01 | graz | N/A | 4 | 40 | 1000.0 | 69 | 377.1 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-01_task-graz_run-04 |\n| sub-03 | ses-01 | graz | N/A | 5 | 40 | 1000.0 | 69 | 373.3 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-01_task-graz_run-05 |\n| sub-03 | ses-01 | graz | N/A | 6 | 40 | 1000.0 | 69 | 381.8 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-01_task-graz_run-06 |\n| sub-03 | ses-02 | graz | N/A | 1 | 40 | 1000.0 | 69 | 329.3 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-02_task-graz_run-01 |\n| sub-03 | ses-02 | graz | N/A | 2 | 40 | 1000.0 | 69 | 327.6 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-02_task-graz_run-02 |\n| sub-03 | ses-02 | graz | N/A | 3 | 40 | 1000.0 | 69 | 329.2 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-02_task-graz_run-03 |\n| sub-03 | ses-02 | graz | N/A | 4 | 40 | 1000.0 | 69 | 331.0 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-02_task-graz_run-04 |\n| sub-03 | ses-02 | graz | N/A | 5 | 40 | 1000.0 | 69 | 332.9 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-02_task-graz_run-05 |\n| sub-03 | ses-02 | graz | N/A | 6 | 40 | 1000.0 | 69 | 331.8 | 50 | nose | left_hand,right_hand,feet,rest | sub-03_ses-02_t","bids_version":"1.0.0","sessions_count":2,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-23 06:02:54","zarr_store_count":1265,"zarr_index_etag":"d0f39b1211717057f93261199d147ea0","zarr_source_commit":"2ad9194363df10fbb3d5360feb6081dae371523d","archive_status":null,"archive_size":null,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":"dataset 143.6 GB exceeds 100.0 GB archive limit; use direct 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