{"dataset":{"id":"61193","dataset_id":"on006839","name":"EEG recordings during sham neurofeedback in virtual reality","description":"This dataset comprises 32-channel EEG recordings collected during a sham neurofeedback experiment conducted in a virtual reality environment. Participants underwent four conditions—positive feedback, negative feedback, control, and resting-state (eyes open/closed)—designed to examine how feedback valence influences alpha-band activity during an attentional task. The data were originally recorded in NeuroScan .cnt format and converted to BIDS using MNE-BIDS.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on006839","concept_doi":"10.82901/nemar.on006839","latest_version_doi":"10.82901/nemar.on006839.v1.0.0","created_at":"2026-06-29 12:31:44","updated_at":"2026-08-19 00:20:39","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"EEG recordings during sham neurofeedback in virtual reality\",\n  \"description\": \"This dataset comprises 32-channel EEG recordings collected during a sham neurofeedback experiment conducted in a virtual reality environment. Participants underwent four conditions—positive feedback, negative feedback, control, and resting-state (eyes open/closed)—designed to examine how feedback valence influences alpha-band activity during an attentional task. The data were originally recorded in NeuroScan .cnt format and converted to BIDS using MNE-BIDS.\",\n  \"methods_description\": \"EEG signals were recorded using a 32-channel SynAmps RT amplifier (Compumedics NeuroScan Inc.) with Ag/AgCl passive electrodes on an elastic cap (Wuhan Greentek Pty. Ltd.) following the extended 10-20 system. Participants completed positive, negative, and control feedback conditions in a VR environment, plus a resting-state condition alternating eyes open and eyes closed (1.5 min each). Stimuli were presented via a Unity3D-developed VR headset synchronized with event markers sent to the EEG system. Original .cnt recordings were converted to BIDS format using the MNE-BIDS toolbox.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"C. Brigitte Aguilar Gonzales\": {},\n    \"Collaborators from the Experimental and Computational Neuroscience Group\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"Neurofeedback\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D058765\"\n    },\n    {\n      \"term\": \"Virtual Reality\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D000076142\"\n    },\n    {\n      \"term\": \"alpha-band activity\"\n    },\n    {\n      \"term\": \"Attention\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D001288\"\n    },\n    {\n      \"term\": \"resting state\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.18112/openneuro.ds006839.v1.0.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on006839\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on006839\",\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  \"funding_references\": [\n    {\n      \"funder_name\": \"This work was supported by CONICET (Argentina) and Universidad Nacional de Entre Ríos.\"\n    },\n    {\n      \"funder_name\": \"CONICET\"\n    },\n    {\n      \"funder_name\": \"Universidad Nacional de Entre Ríos\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"11.1 GB (433 files)\"\n  ],\n  \"formats\": [\n    \".eeg\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".vhdr\",\n    \".vmrk\",\n    \".yml\"\n  ],\n  \"source_hash\": \"e72d683e979d86b51c8a9a733114eae7becb05153fada0709dc6715ad28f4606\"\n}","last_activity_at":"2026-06-29 12:31:44","source":"openneuro","source_id":"ds006839","subject_count":36,"modalities":"eeg","age_min":null,"age_max":null,"file_size":11119142971,"total_files":1128,"tasks":"control,negative,positive,resting","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"C. Brigitte Aguilar Gonzales, Collaborators from the Experimental and Computational Neuroscience Group","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006839-blue)](https://doi.org/10.82901/nemar.on006839)\n\nEEG recordings during sham neurofeedback in virtual reality\n\nDescription\n\nThis dataset contains EEG recordings acquired during a sham neurofeedback experiment conducted in a virtual reality (VR) environment. The study aimed to investigate how feedback valence (positive, negative, or control) modulates alpha-band activity and during an attentional task. EEG signals were recorded using a 32-channel SynAmps RT amplifier (Compumedics NeuroScan Inc., Charlotte, NC, USA) and Ag/AgCl passive electrodes mounted on an elastic cap (Wuhan Greentek Pty. Ltd., China) following the extended 10–20 international system.\n\nEach participant completed four conditions:\n\nPositive feedback (S##_p.cnt) - sham feedback with a reinforcement valence.\n\nNegative feedback (S##_n.cnt) - sham feedback with a punishment valence.\n\nControl (S##_c.cnt) — participants observed the VR environment without any feedback.\n\nResting-state (S##_resting.cnt) — participants alternated between eyes open and eyes closed conditions.\n\nExperimental design\n\nFeedback blocks: Each feedback condition consisted of four blocks of approximately 2 minutes each.\n\nEvents:\n\n238 — marks the beginning of each 2-minute feedback block.\n\n222 — indicates an increase in brightness or volume of VR objects.\n\n190 — indicates a decrease in brightness or volume.\n\n126 — marks the beginning and end of eyes open/closed periods during the resting condition.\n\nResting-state order: Eyes open first, followed by eyes closed.\n\nData format\n\nOriginal EEG recordings were collected in .cnt format (NeuroScan).\n\nData were converted to the Brain Imaging Data Structure (BIDS) format using the MNE-BIDS toolbox (Appelhoff et al., 2019).\n\nEach subject folder (e.g., sub-01/) contains EEG data files (.eeg), event markers, and corresponding JSON sidecar files with acquisition parameters.\n\nData availability\n\nThe BIDS-formatted dataset is publicly available on the OpenNeuro repository and linked through the OSF Wiki project.\n\nReferences\n\nAppelhoff, S., Sanderson, M., Brooks, T. L., van Vliet, M., Quentin, R., Holdgraf, C., … Gramfort, A. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software, 4(44), 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. Scientific Data, 6, 103.\n","bids_version":"1.9.0","sessions_count":null,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-23 23:58:29","zarr_store_count":135,"zarr_index_etag":"3fabcbbea642f4850ebf3559117334d2","zarr_source_commit":"ec645e474d8c58214b65d2c9a0ded2085c2903a0","archive_status":"ready","archive_size":3736959836,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":null,"zarr_errors":9,"zarr_failure_count":9,"zarr_deterministic":0,"zarr_failed_at":"2026-08-23 23:58:29","num_dataset_citations":0,"num_datapaper_citations":0,"n_channels":29,"electrode_system":"10-10","has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":11118158369,"data_complete":1,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":null,"archive_absent_files":null,"archive_declared_files":null,"zarr_pool_breaks":0,"total_recording_duration":87435.51999999996,"recording_duration_min":195.36,"recording_duration_max":950.24,"recording_count":144,"recordings_unavailable":9,"recordings_measured":135,"channel_count_min":29,"channel_count_max":29,"sampling_frequency":1000,"power_line_frequency":50,"eeg_reference":"FCz","placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-19 00:20:24\",\"metadata_updated_at\":\"2026-08-19 00:20:37\",\"archive_checked_at\":\"2026-06-29 12:45:31\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-29 12:49:49\",\"citations_updated_at\":null,\"channel_montage_checked_at\":null,\"hed_checked_at\":\"2026-06-30 05:38:04\",\"data_checked_at\":\"2026-08-30 03:00:26\",\"availability_report_at\":\"2026-07-23 01:30:14\",\"recording_stats_at\":\"2026-09-02 11:33:47\",\"signal_defaults_at\":\"2026-09-02 12:48:51\"}","participants":36,"num_citations":0,"latest_version":"v1.0.0","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"nemarAdmin","owner_github":"nemarAdmin","file_size_formatted":"10.36 GB","zarr_data_failures":{"count":9,"detail_ref":"zarr/index.json","compacted_by":"migration_0074"},"zarr_index_url":"https://zarr.nemar.org/on006839/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}}