{"dataset":{"id":"52510","dataset_id":"on003458","name":"EEG: Three armed bandit gambling task","description":"This dataset comprises electroencephalography (EEG) recordings from 23 healthy college students performing a three-armed bandit gambling task with dynamically oscillating reward probabilities. The task was designed to investigate neural correlates of reward processing and reward prediction error during adaptive decision-making and task set generation. Each stimulus condition (blue, red, and green) had oscillating reinforcement probabilities (ranging from 20% to 90%) that moved in different phases across trials. Supplementary physiological recordings including corrugator EMG and skin conductance were acquired on most participants; however, data quality for these supplementary recordings was limited and they were not extensively analyzed. Data were collected in 2014 at the University of New Mexico's Cognitive Rhythms and Computation Lab.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on003458","concept_doi":"10.82901/nemar.on003458","latest_version_doi":"10.82901/nemar.on003458.v1.0.0","created_at":"2026-06-21 20:31:07","updated_at":"2026-07-10 22:15:12","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"EEG: Three armed bandit gambling task\",\n  \"description\": \"This dataset comprises electroencephalography (EEG) recordings from 23 healthy college students performing a three-armed bandit gambling task with dynamically oscillating reward probabilities. The task was designed to investigate neural correlates of reward processing and reward prediction error during adaptive decision-making and task set generation. Each stimulus condition (blue, red, and green) had oscillating reinforcement probabilities (ranging from 20% to 90%) that moved in different phases across trials. Supplementary physiological recordings including corrugator EMG and skin conductance were acquired on most participants; however, data quality for these supplementary recordings was limited and they were not extensively analyzed. Data were collected in 2014 at the University of New Mexico's Cognitive Rhythms and Computation Lab.\",\n  \"methods_description\": \"EEG data were collected from 23 healthy control subjects performing a three-armed bandit task with oscillating reinforcement probabilities (ranging from 20% to 90%) across three stimulus conditions (blue, red, and green). Supplementary physiological recordings including corrugator EMG and skin conductance were acquired on most participants. The task was implemented in MATLAB programming language.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"James F Cavanagh  jcavanagh@unm.edu\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"reward processing\"\n    },\n    {\n      \"term\": \"decision making\"\n    },\n    {\n      \"term\": \"adaptive decision-making\"\n    },\n    {\n      \"term\": \"bandit task\"\n    },\n    {\n      \"term\": \"gambling\"\n    },\n    {\n      \"term\": \"prediction error\"\n    },\n    {\n      \"term\": \"reinforcement learning\"\n    },\n    {\n      \"term\": \"task set generation\"\n    },\n    {\n      \"term\": \"oscillating probabilities\"\n    },\n    {\n      \"term\": \"dynamic probabilities\"\n    },\n    {\n      \"term\": \"EMG\"\n    },\n    {\n      \"term\": \"skin conductance\"\n    },\n    {\n      \"term\": \"corrugator EMG\"\n    },\n    {\n      \"term\": \"physiological recordings\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on003458\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds003458.v1.1.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on003458\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    }\n  ],\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"5.1 GB (67 files)\"\n  ],\n  \"formats\": [\n    \".bmp\",\n    \".fdt\",\n    \".gitattributes\",\n    \".json\",\n    \".m\",\n    \".md\",\n    \".set\",\n    \".tsv\",\n    \".txt\",\n    \".xlsx\",\n    \".yml\"\n  ],\n  \"source_hash\": \"e01fbafb77f14d4420b34722bceb3450577a12d7a22777b277886c09a82d7d82\"\n}","last_activity_at":"2026-06-21 20:31:07","source":"openneuro","source_id":"ds003458","subject_count":23,"modalities":"eeg","age_min":18,"age_max":24,"file_size":5062719741,"total_files":67,"tasks":"ThreeArmedBandit","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"James F Cavanagh  jcavanagh@unm.edu","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003458-blue)](https://doi.org/10.82901/nemar.on003458)\n\nHealthy control college students.  23 subjects completed the 3-armed bandit task with oscillating probabilities.    For example, the 'blue' stim would slowly move from 20% reinforcing to 90% then back to 20 over many trials.  The other 'red' and 'green' stims would move similarly, but in different phase.  See Fig 1 of the paper.  This makes the task great for investigating reward processing & reward prediction error in the service of novel task set generation.\n\nTask included in Matlab programming language.  \n\nData collected in 2014 in the Cognitive Rhythms and Computation Lab, University of New Mexico.   \n\nI also collected Corrugator EMG (may be labeled EKG) and Skin Conductance on most people.  But quality was dubious so I never did much with it.  Check .xls sheet under code folder.\n\nSome pre-processing scripts are included in code folder as well.   \n\n- James F Cavanagh 01/04/2021","bids_version":"1.1.1","sessions_count":null,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-27 10:02:22","zarr_store_count":23,"zarr_index_etag":"363da05a9684d0f12e2646993fa56f75","zarr_source_commit":"b58f3f6286b2ea13bf4faebddce0c5cc492babff","archive_status":"ready","archive_size":4016817661,"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":64,"electrode_system":"10-10","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":37610.608,"recording_duration_min":1380.552,"recording_duration_max":2045.552,"recording_count":23,"recordings_unavailable":0,"recordings_measured":23,"channel_count_min":64,"channel_count_max":66,"sampling_frequency":500,"power_line_frequency":60,"eeg_reference":"CPz","placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-07-02 04:28:45\",\"metadata_updated_at\":\"2026-07-02 04:29:09\",\"archive_checked_at\":\"2026-07-02 04:32:44\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-07-02 04:30:17\",\"citations_updated_at\":null,\"channel_montage_checked_at\":\"2026-06-28 23:10:40\",\"hed_checked_at\":\"2026-06-30 04:42:14\",\"data_checked_at\":null,\"availability_report_at\":\"2026-07-23 01:13:40\",\"recording_stats_at\":\"2026-09-02 11:32:25\",\"signal_defaults_at\":\"2026-09-02 11:58:49\"}","participants":23,"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":"4.72 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/on003458/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}}