{"dataset":{"id":"56212","dataset_id":"on004317","name":"Mood Manipulation and PST, Experiment 2","description":"This dataset comprises EEG data from a reinforcement learning probabilistic selection task (PST) administered to 50 healthy adult participants, half of whom underwent a sad mood manipulation and half a happy mood manipulation prior to task performance. The task, adapted from a published probabilistic selection paradigm, included training and testing phases with mood induction occurring before each training block. Data were collected between 2019 and 2021 at the Cognitive Rhythms and Computation Lab at the University of New Mexico to study the interaction between mood states and reinforcement learning processes.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on004317","concept_doi":"10.82901/nemar.on004317","latest_version_doi":"10.82901/nemar.on004317.v1.0.0","created_at":"2026-06-24 00:31:54","updated_at":"2026-08-19 16:10:09","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Mood Manipulation and PST, Experiment 2\",\n  \"description\": \"This dataset comprises EEG data from a reinforcement learning probabilistic selection task (PST) administered to 50 healthy adult participants, half of whom underwent a sad mood manipulation and half a happy mood manipulation prior to task performance. The task, adapted from a published probabilistic selection paradigm, included training and testing phases with mood induction occurring before each training block. Data were collected between 2019 and 2021 at the Cognitive Rhythms and Computation Lab at the University of New Mexico to study the interaction between mood states and reinforcement learning processes.\",\n  \"methods_description\": \"The reinforcement learning task, programmed in MATLAB, consisted of training and testing sections with a mood manipulation procedure administered before each training block, inducing either a sad or happy mood state in participants.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"James F Cavanagh\": {},\n    \"Trevor C J Jackson\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"Reinforcement Learning\"\n    },\n    {\n      \"term\": \"mood manipulation\"\n    },\n    {\n      \"term\": \"probabilistic selection task\"\n    },\n    {\n      \"term\": \"Affect\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D000339\"\n    },\n    {\n      \"term\": \"cognitive neuroscience\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on004317\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1126/science.1102941\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds004317\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsVersionOf\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds004317.v1.0.3\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on004317\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    }\n  ],\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"19.6 GB (121 files)\"\n  ],\n  \"formats\": [\n    \".fdt\",\n    \".json\",\n    \".m\",\n    \".md\",\n    \".mp4\",\n    \".set\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"e878799a470d7e5537f9cf06016a0288db810e70347041ab91f541ca6018b0ae\"\n}","last_activity_at":"2026-06-24 00:31:54","source":"openneuro","source_id":"ds004317","subject_count":50,"modalities":"eeg","age_min":18,"age_max":53,"file_size":19639202322,"total_files":429,"tasks":"PST","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"James F Cavanagh, Trevor C J Jackson","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004317-blue)](https://doi.org/10.82901/nemar.on004317)\n\nReinforcement learning task with 50 healthy controls (25 after a sad mood manipulation, 25 after a happy mood manipulation)  Task with a training section and testing section.   Task adapted from here: https://doi.org/10.1126/science.1102941.    Mood Manipulation occurs during task before each training block.  Task included in Matlab programming language.   Data collected from 2019-2021 in Cognitive Rhythms and Computation Lab at University of New Mexico.  Check the .xls sheet under code folder for more meta data.  - Trevor CJ Jackson 10/27/2022","bids_version":"1.1.1","sessions_count":null,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-05 12:45:06","zarr_store_count":50,"zarr_index_etag":"cb23f03f80c0af9a5c8a4cf1c03b3e39","zarr_source_commit":"2fc988be5d131161ecdfcb8cdf6359461e70effb","archive_status":"ready","archive_size":15971911700,"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":1,"num_datapaper_citations":0,"n_channels":66,"electrode_system":"10-10","has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":19636411717,"data_complete":1,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":null,"archive_absent_files":null,"archive_declared_files":null,"zarr_pool_breaks":null,"total_recording_duration":135960.436,"recording_duration_min":2274.1,"recording_duration_max":3553.8,"recording_count":50,"recordings_unavailable":0,"recordings_measured":50,"channel_count_min":66,"channel_count_max":66,"sampling_frequency":500,"power_line_frequency":60,"eeg_reference":"CPz","placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-19 16:10:09\",\"metadata_updated_at\":\"2026-08-19 16:10:09\",\"archive_checked_at\":\"2026-06-24 00:53:02\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-24 00:43:15\",\"citations_updated_at\":\"2026-09-08 03:00:52\",\"channel_montage_checked_at\":\"2026-06-28 23:22:43\",\"hed_checked_at\":\"2026-06-30 04:56:08\",\"data_checked_at\":\"2026-08-08 03:00:58\",\"availability_report_at\":\"2026-07-23 01:17:59\",\"recording_stats_at\":\"2026-09-02 11:32:41\",\"signal_defaults_at\":\"2026-09-02 12:10:11\"}","participants":50,"num_citations":1,"latest_version":"v1.0.0","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"nemarAdmin","owner_github":"nemarAdmin","file_size_formatted":"18.29 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/on004317/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}}