{"dataset":{"id":"305","dataset_id":"nm000272","name":"Romani et al. 2025 — BrainForm: a Serious Game for BCI Training and Data Collection (P300 ERP, University of Trento)","description":"This dataset comprises scalp EEG recordings from 22 participants who used BrainForm, a gamified brain-computer interface (BCI) designed for P300 event-related potential (ERP) training and scalable data collection with consumer hardware. Participants performed repeated runs of a P300 spelling/selection task, allowing analysis of BCI skill acquisition across sessions and the effects of different visual stimulation textures on performance. The dataset supports research on BCI training, human factors, and machine learning applications on ERP data.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000272","concept_doi":"10.82901/nemar.nm000272","latest_version_doi":"10.82901/nemar.nm000272.v1.0.6","created_at":"2026-03-26 22:03:15","updated_at":"2026-08-20 19:22:27","zenodo_concept_id":"20587491","is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"Romani et al. 2025 — BrainForm: a Serious Game for BCI Training and Data Collection (P300 ERP, University of Trento)\",\n  \"description\": \"This dataset comprises scalp EEG recordings from 22 participants who used BrainForm, a gamified brain-computer interface (BCI) designed for P300 event-related potential (ERP) training and scalable data collection with consumer hardware. Participants performed repeated runs of a P300 spelling/selection task, allowing analysis of BCI skill acquisition across sessions and the effects of different visual stimulation textures on performance. The dataset supports research on BCI training, human factors, and machine learning applications on ERP data.\",\n  \"methods_description\": \"EEG data were collected using consumer-grade hardware during a gamified P300 oddball/speller task (task-p300) implemented in the BrainForm serious game, with participants completing multiple runs across two task complexities in a within-subject design.\",\n  \"license\": \"CC-BY-4.0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Michele Romani\": {},\n    \"Devis Zanoni\": {},\n    \"Elisabetta Farella\": {},\n    \"Luca Turchet\": {}\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\": \"Brain-Computer Interfaces\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D062207\"\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\": \"Serious Games\"\n    },\n    {\n      \"term\": \"Machine Learning\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D000069550\"\n    },\n    {\n      \"term\": \"Human factors\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.48550/arXiv.2510.10169\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000272\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/nm000272\",\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    \"242.8 MB (182 files)\"\n  ],\n  \"formats\": [\n    \".bdf\",\n    \".edf\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".yaml\",\n    \".yml\"\n  ],\n  \"source_hash\": \"08ed4a7c44c34aaf4fc2f09d95f104636c8790fecccb016328bf68c8e703ec6b\"\n}","last_activity_at":"2026-08-16 13:39:18","source":null,"source_id":null,"subject_count":22,"modalities":"eeg","age_min":null,"age_max":null,"file_size":248663467,"total_files":1521,"tasks":"ERP,p300","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Michele Romani, Devis Zanoni, Elisabetta Farella, Luca Turchet","license":"CC-BY-4.0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000272-blue)](https://doi.org/10.82901/nemar.nm000272)\n\n# BrainForm: a P300 ERP EEG dataset from a serious game for BCI training and data collection\n\n## Summary\n\nThis dataset contains scalp electroencephalography (EEG) recordings collected with\n**BrainForm**, a gamified (serious-game) **P300 event-related potential (ERP)**\nbrain–computer interface (BCI) designed for scalable data collection using consumer\nhardware and a minimal setup. Participants completed repeated runs of a P300 spelling /\nselection task, enabling study of BCI skill acquisition across sessions and of the\nperceptual/performance effects of different visual stimulation textures.\n\nThe BIDS conversion in this NEMAR record contains EEG data for **22 participants**\n(`sub-*` folders), organised under the `eeg/` modality with a P300 task (`task-p300`).\n\n## Modality and paradigm\n\n- **Modality:** EEG (scalp electroencephalography)\n- **Task / paradigm:** P300 ERP oddball / speller within a serious game (`task-p300`)\n- **Focus:** BCI training, human factors, machine learning on ERP data\n\n## Participants\n\nThis BIDS dataset includes **22 subjects**. The original study used a within-subject\ndesign with multiple runs and two task complexities. Refer to `participants.tsv` and the\npaper for details.\n\n## Original dataset / data paper\n\nPlease cite the original paper when using this dataset:\n\n> Romani, M., Zanoni, D., Farella, E., & Turchet, L. (2025). *BrainForm: a Serious Game\n> for BCI Training and Data Collection.* arXiv:2510.10169.\n> https://doi.org/10.48550/arXiv.2510.10169\n\n- **DOI / preprint:** [arXiv:2510.10169](https://doi.org/10.48550/arXiv.2510.10169)\n- **Source / project:** University of Trento and Fondazione Bruno Kessler (FBK)\n- **Related record:** https://zenodo.org/records/17225966\n\n## Attribution\n\nAll data were collected by the original authors (Michele Romani and colleagues,\nUniversity of Trento / FBK). Please credit the original creators and cite the paper\nabove. This NEMAR record redistributes the dataset in BIDS format; EEG-BIDS and related\nBIDS tools were used only for standardisation, not as the source of the data.\n\n## License\n\nCC-BY-4.0 (see `dataset_description.json`).\n","bids_version":"1.9.0","sessions_count":6,"publish_date":"2026-03-26 22:03:15","embedding_dirty":0,"license_tier":"attribution","zarr_status":"ready","zarr_converted_at":"2026-09-05 12:00:22","zarr_store_count":120,"zarr_index_etag":"3417bc7b1085b49b96dc3cb9848c439c","zarr_source_commit":"b9f79182bf5f17aaa753621afdf49fedda70f5f1","archive_status":"ready","archive_size":155967628,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":null,"zarr_errors":0,"zarr_failure_count":0,"zarr_deterministic":0,"zarr_failed_at":null,"num_dataset_citations":0,"num_datapaper_citations":1,"n_channels":8,"electrode_system":"10-10","has_hed":1,"hed_version":"8.4.0","is_exemplar":0,"bytes_present":242847739,"data_complete":1,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":1,"archive_absent_files":0,"archive_declared_files":1521,"zarr_pool_breaks":0,"total_recording_duration":22602,"recording_duration_min":62,"recording_duration_max":531,"recording_count":120,"recordings_unavailable":0,"recordings_measured":120,"channel_count_min":8,"channel_count_max":8,"sampling_frequency":250,"power_line_frequency":50,"eeg_reference":"right mastoid","placement_scheme":"10-20 system","sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-20 19:21:40\",\"metadata_updated_at\":\"2026-08-20 19:22:26\",\"archive_checked_at\":\"2026-08-20 19:23:29\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-08-20 19:23:08\",\"citations_updated_at\":\"2026-08-01 03:00:59\",\"channel_montage_checked_at\":\"2026-06-28 23:02:45\",\"hed_checked_at\":\"2026-06-30 07:33:25\",\"data_checked_at\":null,\"availability_report_at\":\"2026-08-22 03:01:32\",\"signal_defaults_at\":\"2026-09-02 11:50:48\",\"recording_stats_at\":\"2026-09-06 03:00:47\"}","participants":22,"num_citations":1,"latest_version":"v1.0.6","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"bruaristimunha","owner_github":"bruAristimunha","file_size_formatted":"237 MB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/nm000272/zarr/index.json","attestation_deposit_type":null,"attestation_key_status":null,"attestation_deidentified":null,"attestation_no_duplicate":null,"attestation_upstream_source":null,"attestation_accepted_at":null}}