{"dataset":{"id":"250","dataset_id":"nm000217","name":"P300 dataset BI2015b from a \"Brain Invaders\" experiment","description":"This dataset (BI2015b) comprises EEG recordings from 44 subjects playing a visual P300-based Brain-Computer Interface videogame called Brain Invaders, collected at GIPSA-lab, Grenoble, France in 2015. Using an oddball paradigm on a 36-symbol grid, participants elicited P300 responses under three flash-duration conditions (50ms, 80ms, 110ms) across three game sessions. The dataset was reformatted into BIDS by MOABB and includes HED event annotations for Target and NonTarget stimuli, intended for benchmarking BCI decoding algorithms.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000217","concept_doi":"10.82901/nemar.nm000217","latest_version_doi":"10.82901/nemar.nm000217.v1.0.4","created_at":"2026-03-24 05:57:44","updated_at":"2026-08-21 10:47:26","zenodo_concept_id":"20518891","is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"P300 dataset BI2015b from a \\\"Brain Invaders\\\" experiment\",\n  \"description\": \"This dataset (BI2015b) comprises EEG recordings from 44 subjects playing a visual P300-based Brain-Computer Interface videogame called Brain Invaders, collected at GIPSA-lab, Grenoble, France in 2015. Using an oddball paradigm on a 36-symbol grid, participants elicited P300 responses under three flash-duration conditions (50ms, 80ms, 110ms) across three game sessions. The dataset was reformatted into BIDS by MOABB and includes HED event annotations for Target and NonTarget stimuli, intended for benchmarking BCI decoding algorithms.\",\n  \"methods_description\": \"EEG was recorded with a 32-channel g.USBamp system (g.tec) using wet Silver/Silver Chloride electrodes in a 10-10 montage, referenced to the right earlobe with ground at Fz, sampled at 512 Hz with no online digital filtering. Event tagging was synchronized via a USB digital-to-analog converter connected to the amplifier's trigger channel to reduce jitter. Each session consisted of three game blocks with different flash durations (110ms, 80ms, 50ms), with resting-state recordings before and after. A real-time adaptive Riemannian Minimum Distance to Mean (RMDM) classifier provided feedback during the oddball task.\",\n  \"license\": \"CC-BY-4.0\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"Louis Korczowski\": {},\n    \"Martine Cederhout\": {},\n    \"Anton Andreev\": {},\n    \"Grégoire Cattan\": {\n      \"orcid\": \"0000-0002-7515-0690\"\n    },\n    \"Pedro Luiz Coelho Rodrigues\": {},\n    \"Violette Gautheret\": {},\n    \"Marco Congedo\": {\n      \"orcid\": \"0000-0003-2196-0409\"\n    }\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\": \"P300\"\n    },\n    {\n      \"term\": \"Brain-Computer Interface\"\n    },\n    {\n      \"term\": \"Event-Related Potentials, P300\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D018913\"\n    },\n    {\n      \"term\": \"oddball paradigm\"\n    },\n    {\n      \"term\": \"Riemannian geometry\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.5281/zenodo.3266930\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsSupplementTo\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000217\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.5281/zenodo.3267307\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsVersionOf\"\n    },\n    {\n      \"identifier\": \"10.21105/joss.01896\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsReferencedBy\"\n    },\n    {\n      \"identifier\": \"10.1038/s41597-019-0104-8\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsReferencedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/nm000217\",\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    \"9.2 GB (265 files)\"\n  ],\n  \"formats\": [\n    \".bdf\",\n    \".json\",\n    \".mat\",\n    \".md\",\n    \".tsv\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"ab66fd7960768a85a39ca8ffe515ac7727fa3fbf215a73b5f9dc2467b2ce9954\"\n}","last_activity_at":"2026-08-16 13:33:57","source":null,"source_id":null,"subject_count":44,"modalities":"eeg","age_min":23.7,"age_max":23.7,"file_size":9218696811,"total_files":1375,"tasks":"p300","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Louis Korczowski, Martine Cederhout, Anton Andreev, Grégoire Cattan, Pedro Luiz Coelho Rodrigues, Violette Gautheret, Marco Congedo","license":"CC-BY-4.0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000217-blue)](https://doi.org/10.82901/nemar.nm000217)\n\n# P300 dataset BI2015b from a \"Brain Invaders\" experiment\n\nP300 dataset BI2015b from a \"Brain Invaders\" experiment.\n\n## Dataset Overview\n\n- **Code**: BrainInvaders2015b\n- **Paradigm**: p300\n- **DOI**: https://doi.org/10.5281/zenodo.3267307\n- **Subjects**: 44\n- **Sessions per subject**: 1\n- **Events**: Target=2, NonTarget=1\n- **Trial interval**: [0, 1] s\n- **Runs per session**: 4\n- **File format**: mat and csv\n- **Contributing labs**: GIPSA-lab\n\n## Acquisition\n\n- **Sampling rate**: 512.0 Hz\n- **Number of channels**: 32\n- **Channel types**: eeg=32\n- **Channel names**: AFz, C3, C4, CP1, CP2, CP5, CP6, Cz, F3, F4, F7, F8, FC1, FC2, FC5, FC6, Fp1, Fp2, O1, O2, Oz, P3, P4, P7, P8, PO10, PO7, PO8, PO9, Pz, T7, T8\n- **Montage**: 10-10\n- **Hardware**: g.USBamp (g.tec, Schiedlberg, Austria)\n- **Software**: OpenVibe\n- **Reference**: right earlobe\n- **Ground**: Fz\n- **Sensor type**: wet Silver/Silver Chloride electrodes\n- **Line frequency**: 50.0 Hz\n- **Online filters**: no digital filter applied\n- **Cap manufacturer**: g.tec\n- **Cap model**: g.GAMMAcap\n- **Electrode type**: wet\n- **Electrode material**: Silver/Silver Chloride\n\n## Participants\n\n- **Number of subjects**: 44\n- **Health status**: patients\n- **Clinical population**: Healthy\n- **Age**: mean=23.7, std=3.19\n- **Gender distribution**: male=36, female=14\n- **BCI experience**: mostly students and young researchers\n- **Species**: human\n\n## Experimental Protocol\n\n- **Paradigm**: p300\n- **Number of classes**: 2\n- **Class labels**: Target, NonTarget\n- **Study design**: Three game sessions with different flash durations (110ms, 80ms, 50ms), with resting state and eyes closed conditions recorded before and after. Subjects were instructed to limit eye blinks, head movements and face muscular contractions.\n- **Feedback type**: visual (game interface with reward screen)\n- **Stimulus type**: visual flash\n- **Stimulus modalities**: visual\n- **Primary modality**: visual\n- **Mode**: online\n- **Training/test split**: False\n- **Instructions**: Players had up to eight attempts to destroy the target symbol per level. Target symbol identification using oddball paradigm with 36 aliens flashing in pseudo-random groups of six symbols.\n\n## HED Event Annotations\n\nSchema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser\n\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\n```\n## Paradigm-Specific Parameters\n\n- **Detected paradigm**: p300\n- **Number of targets**: 1\n- **Number of repetitions**: 12\n\n## Data Structure\n\n- **Trials**: variable per subject (up to 8 attempts per level, 9 levels per session, 3 sessions)\n- **Blocks per session**: 9\n- **Trials context**: per session (9 levels per session, 3 sessions with different flash durations)\n\n## Preprocessing\n\n- **Data state**: raw EEG with synchronized hardware tagging via USB digital-to-analog converter (reduced jitter compared to software tagging)\n- **Preprocessing applied**: False\n- **Notes**: Data were stored with no digital filter applied. USB digital-to-analog converter connected to the g.USBamp trigger channel was used to synchronize experimental tags produced by Brain Invaders with EEG signals to reduce jitter.\n\n## Signal Processing\n\n- **Classifiers**: Riemannian Minimum Distance to Mean (RMDM), xDAWN, Riemannian MDM\n- **Feature extraction**: Covariance/Riemannian, xDAWN\n\n## Cross-Validation\n\n- **Evaluation type**: cross_session\n\n## Performance (Original Study)\n\n- **Note**: Real-time adaptive classifier used during experiment, performance variable per subject\n\n## BCI Application\n\n- **Applications**: gaming\n- **Environment**: small room with a surface of four meters square, containing a 24' screen\n- **Online feedback**: True\n\n## Tags\n\n- **Pathology**: Healthy\n- **Modality**: Visual\n- **Type**: Perception\n\n## Documentation\n\n- **Description**: EEG recordings of 50 subjects playing to a visual P300 Brain-Computer Interface (BCI) videogame named Brain Invaders. The interface uses the oddball paradigm on a grid of 36 symbols (1 Target, 35 Non-Target) that are flashed pseudo-randomly to elicit the P300 response. Three conditions: flash duration 50ms, 80ms or 110ms.\n- **DOI**: 10.5281/zenodo.3266930\n- **Associated paper DOI**: hal-02172347\n- **License**: CC-BY-4.0\n- **Investigators**: Louis Korczowski, Martine Cederhout, Anton Andreev, Grégoire Cattan, Pedro Luiz Coelho Rodrigues, Violette Gautheret, Marco Congedo\n- **Senior author**: Marco Congedo\n- **Institution**: GIPSA-lab, CNRS, University Grenoble-Alpes, Grenoble INP\n- **Address**: GIPSA-lab, 11 rue des Mathématiques, Grenoble Campus BP46, F-38402, France\n- **Country**: France\n- **Repository**: Zenodo\n- **Data URL**: https://doi.org/10.5281/zenodo.3266930\n- **Publication year**: 2019\n- **Ethics approval**: Ethical Committee of the University of Grenoble Alpes (Comité d'Ethique pour la Recherche Non-Interventionnelle)\n- **Keywords**: Electroencephalography (EEG), P300, Brain-Computer Interface, Experiment\n\n## Abstract\n\nWe describe the experimental procedures for an experiment dataset that we have made publicly available at https://doi.org/10.5281/zenodo.3266930 in mat and csv formats. This dataset contains electroencephalographic (EEG) recordings of 50 subjects playing to a visual P300 Brain-Computer Interface (BCI) videogame named Brain Invaders. The interface uses the oddball paradigm on a grid of 36 symbols (1 Target, 35 Non-Target) that are flashed pseudo-randomly to elicit the P300 response. EEG data were recorded using 32 active wet electrodes with three conditions: flash duration 50ms, 80ms or 110ms. The experiment took place at GIPSA-lab, Grenoble, France, in 2015.\n\n## Methodology\n\nThe experiment consisted of three game sessions of Brain Invaders of 9 levels each with different flash duration (110ms, 80ms, 50ms). Before and after the three game sessions, around one minute of resting state and eyes closed conditions were recorded. The interface is composed of 36 aliens. A repetition is composed of 12 flashes of pseudo-random groups of six symbols chosen in such a way that after each repetition each symbol has flashed exactly two times. The ratio of Target versus non-Target is one-to-five. During the experiment, the output of a real-time adaptive Riemannian Minimum Distance to Mean (RMDM) classifier was used for assessing the participants' command. This scheme allows a calibration-free classifier.\n\n## References\n\nKorczowski, L., Cederhout, M., Andreev, A., Cattan, G., Rodrigues, P. L. C., Gautheret, V., & Congedo, M. (2019). Brain Invaders Cooperative versus Competitive: Multi-User P300-based Brain-Computer Interface Dataset (BI2015b) https://hal.archives-ouvertes.fr/hal-02172347\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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