{"dataset":{"id":"387","dataset_id":"nm000136","name":"Guttmann-Flury et al. 2025 (P300) — Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms","description":"A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing a P300-based speller task across three sessions. The dataset comprises 2,520 trials of visual event-related potential data acquired at 1000 Hz using a 64-channel Neuroscan system (64 EEG channels + 1 EOG + 1 stimulus channel), designed to enable analysis of ocular activity patterns and their relationship to brain-computer interface performance across multiple BCI paradigms.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000136","concept_doi":"10.82901/nemar.nm000136","latest_version_doi":"10.82901/nemar.nm000136.v1.0.3","created_at":"2026-03-30 09:31:26","updated_at":"2026-08-18 18:16:42","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"Guttmann-Flury et al. 2025 (P300) — Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms\",\n  \"description\": \"A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing a P300-based speller task across three sessions. The dataset comprises 2,520 trials of visual event-related potential data acquired at 1000 Hz using a 64-channel Neuroscan system (64 EEG channels + 1 EOG + 1 stimulus channel), designed to enable analysis of ocular activity patterns and their relationship to brain-computer interface performance across multiple BCI paradigms.\",\n  \"methods_description\": \"EEG data were acquired using a Neuroscan Quik-Cap 65-channel system with SynAmps2 amplifier at 1000 Hz sampling rate. The montage followed the standard 1005 electrode placement with 64 EEG channels, 1 EOG channel, and 1 stimulus channel. Reference electrode was placed at the right mastoid (M1) with ground at the forehead. Online high-pass filtering was applied with a 10-second time constant. Participants performed a row-column P300 speller task with 4L and 5L grid sizes in a synchronous, offline mode without feedback. Concurrent eye-tracking and high-speed video recordings captured ocular activity during the task.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"Eva Guttmann-Flury\": {\n      \"orcid\": \"0000-0002-8241-1713\"\n    },\n    \"Xinjun Sheng\": {},\n    \"Xiangyang Zhu\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"Event-Related Potentials, P300\",\n      \"subject_scheme\": \"MeSH\",\n      \"scheme_uri\": \"https://id.nlm.nih.gov/mesh/\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D018913\"\n    },\n    {\n      \"term\": \"brain-computer interfaces\"\n    },\n    {\n      \"term\": \"eye tracking\"\n    },\n    {\n      \"term\": \"speller paradigm\"\n    },\n    {\n      \"term\": \"multimodal neuroimaging\"\n    },\n    {\n      \"term\": \"high-speed video\"\n    },\n    {\n      \"term\": \"ocular activity\"\n    },\n    {\n      \"term\": \"communication\"\n    },\n    {\n      \"term\": \"research\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.1038/s41597-025-04861-9\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000136\",\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/nm000136\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"43.7 GB (378 files)\"\n  ],\n  \"formats\": [\n    \".avi\",\n    \".bdf\",\n    \".csv\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".txt\",\n    \".xlsx\",\n    \".xml\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"e5b5b4a35f0473ad9216f35b673e916fd2c7f7a3b924bc2959c0d39736d8db28\"\n}","last_activity_at":"2026-08-16 13:27:56","source":null,"source_id":null,"subject_count":31,"modalities":"eeg","age_min":28.3,"age_max":28.3,"file_size":43751957741,"total_files":1207,"tasks":"p300","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Eva Guttmann-Flury, Xinjun Sheng, Xiangyang Zhu","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000136-blue)](https://doi.org/10.82901/nemar.nm000136)\n\nGuttmannFlury2025-P300\n======================\n\nEye-BCI multimodal P300 speller dataset from Guttmann-Flury et al 2025.\n\nDataset Overview\n----------------\n  Code: GuttmannFlury2025-P300\n  Paradigm: p300\n  DOI: 10.1038/s41597-025-04861-9\n  Subjects: 31\n  Sessions per subject: 3\n  Events: Target=1, NonTarget=2\n  Trial interval: [0, 1] s\n  File format: BDF\n\nAcquisition\n-----------\n  Sampling rate: 1000.0 Hz\n  Number of channels: 66\n  Channel types: eeg=64, eog=1, stim=1\n  Channel names: FP1, FPZ, FP2, AF3, AF4, F7, F5, F3, F1, FZ, F2, F4, F6, F8, FT7, FC5, FC3, FC1, FCZ, FC2, FC4, FC6, FT8, T7, C5, C3, C1, CZ, C2, C4, C6, T8, TP7, CP5, CP3, CP1, CPZ, CP2, CP4, CP6, TP8, P7, P5, P3, P1, PZ, P2, P4, P6, P8, PO7, PO5, PO3, POZ, PO4, PO6, PO8, O1, OZ, O2, CB1, CB2\n  Montage: standard_1005\n  Hardware: Neuroscan Quik-Cap 65-ch, SynAmps2\n  Reference: right mastoid (M1)\n  Ground: forehead\n  Sensor type: Ag/AgCl\n  Line frequency: 50.0 Hz\n  Online filters: {'highpass_time_constant_s': 10}\n\nParticipants\n------------\n  Number of subjects: 31\n  Health status: healthy\n  Age: mean=28.3, min=20.0, max=57.0\n  Gender distribution: female=11, male=20\n  Species: human\n\nExperimental Protocol\n---------------------\n  Paradigm: p300\n  Number of classes: 2\n  Class labels: Target, NonTarget\n  Study design: Multi-paradigm BCI (MI/ME/SSVEP/P300). P300: row/column speller with 4L and 5L grid sizes.\n  Feedback type: none\n  Stimulus type: row-column flash\n  Stimulus modalities: visual\n  Primary modality: visual\n  Synchronicity: synchronous\n  Mode: offline\n\nHED Event Annotations\n---------------------\n  Schema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n\n  Target\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Target\n\n  NonTarget\n    ├─ Sensory-event\n    ├─ Experimental-stimulus\n    ├─ Visual-presentation\n    └─ Non-target\n\nParadigm-Specific Parameters\n----------------------------\n  Detected paradigm: p300\n\nData Structure\n--------------\n  Trials: 2520\n  Trials context: 63 sessions x 40 trials = 2520 (P300-4L default)\n\nBCI Application\n---------------\n  Applications: speller, communication\n  Environment: laboratory\n\nTags\n----\n  Pathology: Healthy\n  Modality: ERP\n  Type: Research\n\nDocumentation\n-------------\n  DOI: 10.1038/s41597-025-04861-9\n  License: CC0\n  Investigators: Eva Guttmann-Flury, Xinjun Sheng, Xiangyang Zhu\n  Institution: Shanghai Jiao Tong University\n  Country: CN\n  Publication year: 2025\n\nReferences\n----------\nGuttmann-Flury, E., Sheng, X., & Zhu, X. (2025). Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms. Scientific Data, 12, 587. https://doi.org/10.1038/s41597-025-04861-9\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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