{"dataset":{"id":"125","dataset_id":"nm000122","name":"Chen2017 – Single-flicker online SSVEP BCI dataset","description":"A 32-channel EEG dataset from 12 healthy subjects performing a spatial navigation task using a single-flicker steady-state visual evoked potential (SSVEP) brain-computer interface. The dataset comprises two sessions per subject: a structured training session with 200 trials per subject recorded at 2048 Hz, and an online adaptive BCI game session recorded at 512 Hz. This paradigm employs a spatially-coded approach where a single 15 Hz flickering stimulus in the center of the screen produces distinct spatial topographies corresponding to four cardinal directions (north, east, west, south), enabling direction-specific decoding without frequency-based analysis methods.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000122","concept_doi":"10.82901/nemar.nm000122","latest_version_doi":"10.82901/nemar.nm000122.v1.0.2","created_at":"2026-03-06 21:18:10","updated_at":"2026-08-18 18:11:33","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Chen2017 – Single-flicker online SSVEP BCI dataset\",\n  \"description\": \"A 32-channel EEG dataset from 12 healthy subjects performing a spatial navigation task using a single-flicker steady-state visual evoked potential (SSVEP) brain-computer interface. The dataset comprises two sessions per subject: a structured training session with 200 trials per subject recorded at 2048 Hz, and an online adaptive BCI game session recorded at 512 Hz. This paradigm employs a spatially-coded approach where a single 15 Hz flickering stimulus in the center of the screen produces distinct spatial topographies corresponding to four cardinal directions (north, east, west, south), enabling direction-specific decoding without frequency-based analysis methods.\",\n  \"methods_description\": \"EEG data were acquired using a BioSemi ActiveTwo system with 32 active electrodes arranged in the biosemi32 montage and CMS/DRL reference. Training sessions were recorded at 2048 Hz with 100 trials per run (50 trials per direction, 200 total) lasting approximately 3.5 seconds each. Online sessions were recorded at 512 Hz with variable-length trials from approximately 16 game rounds per subject. All recordings used sintered Ag/AgCl electrodes with a 50 Hz line frequency.\",\n  \"license\": \"CC BY 4.0\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"Jingjing Chen\": {},\n    \"Dan Zhang\": {},\n    \"Andreas K. Engel\": {},\n    \"Qin Gong\": {},\n    \"Alexander Maye\": {\n      \"orcid\": \"0000-0002-3660-4186\"\n    }\n  },\n  \"keywords\": [\n    {\n      \"term\": \"SSVEP\"\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\": \"EEG\"\n    },\n    {\n      \"term\": \"spatial navigation\"\n    },\n    {\n      \"term\": \"single-flicker paradigm\"\n    },\n    {\n      \"term\": \"online BCI\"\n    },\n    {\n      \"term\": \"visual evoked potentials\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.1371/journal.pone.0178385\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000122\",\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      \"identifier\": \"https://nemar.org/dataset/nm000122\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"DFG\",\n      \"award_number\": \"TRR169/B1/Z2\",\n      \"award_title\": \"Crossmodal Learning\"\n    },\n    {\n      \"funder_name\": \"Landesforschungsfoerderung Hamburg\",\n      \"award_number\": \"CROSS FV25\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"11.7 GB (230 files)\"\n  ],\n  \"formats\": [\n    \".html\",\n    \".json\",\n    \".mat\",\n    \".md\",\n    \".set\",\n    \".tsv\",\n    \".xdf\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"c0cd78cfa4fc21ba3769227b9eb3091498a27fe403dedcebe0ca4d02548641f0\"\n}","last_activity_at":"2026-08-16 13:24:47","source":null,"source_id":null,"subject_count":12,"modalities":"eeg","age_min":23.5,"age_max":23.5,"file_size":11698064261,"total_files":361,"tasks":"ssvep","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Jingjing Chen, Dan Zhang, Andreas K. Engel, Qin Gong, Alexander Maye","license":"CC BY 4.0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000122-blue)](https://doi.org/10.82901/nemar.nm000122)\n\n# Single-flicker online SSVEP BCI dataset\n\nSingle-flicker online SSVEP BCI dataset.\n\n## Dataset Overview\n\n- **Code**: Chen2017SingleFlicker\n- **Paradigm**: ssvep\n- **DOI**: 10.1371/journal.pone.0178385\n- **Subjects**: 12\n- **Sessions per subject**: 2\n- **Events**: north=1, east=2, west=3, south=4\n- **Trial interval**: [0.0, 3.5] s\n- **File format**: XDF/MAT\n\n## Acquisition\n\n- **Sampling rate**: 512.0 Hz\n- **Number of channels**: 32\n- **Channel types**: eeg=32\n- **Montage**: biosemi32\n- **Hardware**: BioSemi ActiveTwo\n- **Reference**: CMS/DRL\n- **Sensor type**: active\n- **Line frequency**: 50.0 Hz\n- **Cap manufacturer**: BioSemi\n- **Electrode material**: sintered Ag/AgCl\n\n## Participants\n\n- **Number of subjects**: 12\n- **Health status**: healthy\n- **Age**: mean=23.5, min=19, max=32\n- **Gender distribution**: male=5, female=7\n\n## Experimental Protocol\n\n- **Paradigm**: ssvep\n- **Task type**: spatial navigation\n- **Number of classes**: 4\n- **Class labels**: north, east, west, south\n- **Study design**: Spatial navigation with single 15 Hz flicker\n- **Feedback type**: visual\n- **Stimulus type**: single-flicker spatially coded\n- **Stimulus modalities**: visual\n- **Primary modality**: visual\n- **Synchronicity**: synchronous\n- **Mode**: online\n- **Training/test split**: True\n\n## HED Event Annotations\n\nSchema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n\n```\n  north\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Label/north\n\n  east\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Label/east\n\n  west\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Label/west\n\n  south\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Label/south\n\n```\n## Paradigm-Specific Parameters\n\n- **Detected paradigm**: ssvep\n- **Stimulus frequencies**: [15.0] Hz\n\n## Signal Processing\n\n- **Classifiers**: LDA\n- **Feature extraction**: CCA\n- **Frequency bands**: bandpass=[1.0, 80.0] Hz\n- **Spatial filters**: CCA\n\n## Cross-Validation\n\n- **Evaluation type**: within_subject\n\n## BCI Application\n\n- **Applications**: spatial_navigation\n- **Environment**: lab\n- **Online feedback**: True\n\n## Tags\n\n- **Pathology**: healthy\n- **Modality**: visual\n- **Type**: perception\n\n## Documentation\n\n- **DOI**: 10.1371/journal.pone.0178385\n- **License**: CC BY 4.0\n- **Investigators**: Jingjing Chen, Dan Zhang, Andreas K. Engel, Qin Gong, Alexander Maye\n- **Senior author**: Alexander Maye\n- **Institution**: University Medical Center Hamburg-Eppendorf\n- **Department**: Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf\n- **Country**: DE\n- **Repository**: Zenodo\n- **Data URL**: https://zenodo.org/records/580485\n- **Publication year**: 2017\n- **Funding**: DFG TRR169/B1/Z2 Crossmodal Learning; Landesforschungsfoerderung Hamburg CROSS FV25\n- **Ethics approval**: Ethics committee of the medical association, Hamburg\n- **Keywords**: SSVEP, BCI, spatial navigation, single-flicker, online BCI\n\n## References\n\nJ. Chen, D. Zhang, A. K. Engel, Q. Gong, and A. Maye, \"Application of a single-flicker online SSVEP BCI for spatial navigation,\" PLoS ONE, vol. 12, no. 5, e0178385, 2017. DOI: 10.1371/journal.pone.0178385\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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