{"dataset":{"id":"42944","dataset_id":"on004973","name":"An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios ","description":"This fNIRS neuroimaging dataset captures prefrontal cortex activity from 20 participants during 14 types of highly automated driving scenarios in a simulator environment. The study examines risk cognition in passengers across different age groups, sexes, and driving experience levels using an 8-channel fNIRS device. The dataset aims to identify differences in prefrontal cortex activation between low-risk and high-risk driving episodes to support safety-of-the-intended-functionality (SOTIF) improvements and brain-computer interface applications.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on004973","concept_doi":"10.82901/nemar.on004973","latest_version_doi":"10.82901/nemar.on004973.v1.0.0","created_at":"2026-06-18 06:31:06","updated_at":"2026-07-10 22:42:36","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios \",\n  \"description\": \"This fNIRS neuroimaging dataset captures prefrontal cortex activity from 20 participants during 14 types of highly automated driving scenarios in a simulator environment. The study examines risk cognition in passengers across different age groups, sexes, and driving experience levels using an 8-channel fNIRS device. The dataset aims to identify differences in prefrontal cortex activation between low-risk and high-risk driving episodes to support safety-of-the-intended-functionality (SOTIF) improvements and brain-computer interface applications.\",\n  \"methods_description\": \"Data were collected from 20 participants (ages 21-46; 5 females, 15 males) using an 8-channel fNIRS device during a driving simulator experiment. Each participant completed 12 tasks across 14 highly automated driving scenario types, for a total of 240 tasks. Twenty tasks were excluded from analysis due to recording errors, resulting in 220 valid tasks for analysis.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Xiaofei Zhang \": {},\n    \"Qiaoya Wang \": {},\n    \"Jun Li\": {},\n    \"Xiaorong Gao \": {},\n    \"Bowen Li \": {},\n    \"Bingbing Nie \": {},\n    \"Jianqiang Wang \": {},\n    \"Ziyuan Zhou \": {},\n    \"Yingkai Yang \": {},\n    \"Hong Wang\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"fNIRS\"\n    },\n    {\n      \"term\": \"prefrontal cortex\"\n    },\n    {\n      \"term\": \"automated driving\"\n    },\n    {\n      \"term\": \"risk cognition\"\n    },\n    {\n      \"term\": \"neuroimaging\"\n    },\n    {\n      \"term\": \"driving simulator\"\n    },\n    {\n      \"term\": \"brain activity\"\n    },\n    {\n      \"term\": \"SOTIF\"\n    },\n    {\n      \"term\": \"passenger\"\n    },\n    {\n      \"term\": \"autonomous driving\"\n    },\n    {\n      \"term\": \"age differences\"\n    },\n    {\n      \"term\": \"sex differences\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on004973\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataexplorer/detail?dataset_id=on004973\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds004973\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsVersionOf\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds004973.v1.0.1\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"fNIRS Dataset\",\n  \"modalities\": [\n    \"nirs\"\n  ],\n  \"sizes\": [\n    \"2.5 GB (223 files)\"\n  ],\n  \"formats\": [\n    \".json\",\n    \".md\",\n    \".snirf\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"d137aefe1e34f3e4eb5862f5599a8d89317b11797b883bdc95b272e1a725ae54\"\n}","last_activity_at":"2026-06-18 06:31:06","source":"openneuro","source_id":"ds004973","subject_count":20,"modalities":"nirs","age_min":21,"age_max":46,"file_size":2485504834,"total_files":223,"tasks":"1,10,11,12,2,3,4,5,6,7,8,9","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Xiaofei Zhang , Qiaoya Wang , Jun Li, Xiaorong Gao , Bowen Li , Bingbing Nie , Jianqiang Wang , Ziyuan Zhou , Yingkai Yang , Hong Wang","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004973-blue)](https://doi.org/10.82901/nemar.on004973)\n\nThe  fNIRS dataset focus on the prefrontal cortex activity in fourteen types of highly automated driving scenarios, which considers age, sex and driving experience factors, and contains the data of an 8-channel fNIRS device and driving scenarios. A total of 20 participants completed this driving simulator experiment，and each participant need to finish 12 tasks. Their ages range from 21 to 46 years old, with 5 females and 15 males. \n\n Our objective is to provides the data support for finding the difference of prefrontal cortex activity between low-risk and high-risk episodes by quantifying the risk of driving scenarios. This research may provide a solution to prevent potential hazard and improve SOTIF based on brain-computer interface technology and fNIRS, in the future. \n\n## Notes\n\n- Here a total of 240 tasks which are need to be completed by  20 participants，and the data about 20 tasks is removed because the data are not recorded correctly.\n- We update the results of subjective evaluations about dangerous degree of VTD segment, and they are shown in the file \"participants.tsv\".\n\n## How to cite?\ndoi:10.18112/openneuro.ds004973.v1.0.0","bids_version":"1.7.0","sessions_count":null,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-09-06 06:28:14","zarr_store_count":0,"zarr_index_etag":"d42b999a22f4f4ca7a5f296881312f1c","zarr_source_commit":"545d241ca5b151e0ba4473ee79771774d91ae1f0","archive_status":"ready","archive_size":606822512,"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":0,"n_channels":null,"electrode_system":null,"has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":null,"data_complete":null,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":null,"archive_absent_files":null,"archive_declared_files":null,"zarr_pool_breaks":0,"total_recording_duration":null,"recording_duration_min":null,"recording_duration_max":null,"recording_count":0,"recordings_unavailable":0,"recordings_measured":0,"channel_count_min":null,"channel_count_max":null,"sampling_frequency":null,"power_line_frequency":null,"eeg_reference":null,"placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-06-18 06:39:39\",\"metadata_updated_at\":\"2026-06-18 06:39:43\",\"archive_checked_at\":\"2026-06-18 06:42:18\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-18 06:41:12\",\"citations_updated_at\":null,\"channel_montage_checked_at\":null,\"hed_checked_at\":\"2026-06-30 05:09:26\",\"data_checked_at\":null,\"availability_report_at\":\"2026-07-23 01:22:03\",\"signal_defaults_at\":\"2026-09-02 12:23:05\",\"recording_stats_at\":\"2026-09-07 03:01:07\"}","participants":20,"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":"2.31 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/on004973/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}}