{"dataset":{"id":"51214","dataset_id":"on002721","name":"An EEG dataset recorded during affective music listening","description":"This dataset comprises unprocessed EEG recordings from 31 healthy adult participants (age 18-66, 18 female) listening to 40 music clips of 12 s duration each of varying emotional content. The study investigates neural correlates of music-induced emotion through six runs of EEG recordings, including resting-state baseline and four music listening runs. Data were collected at 1 kHz sampling rate and are accompanied by participants' self-reported emotional responses, providing a resource for studying the relationship between brain activity and affective music perception. The musical stimuli were excerpts from film scores selected from Eerola & Vuoskoski (2010).","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on002721","concept_doi":"10.82901/nemar.on002721","latest_version_doi":"10.82901/nemar.on002721.v1.0.0","created_at":"2026-06-21 07:30:54","updated_at":"2026-07-10 22:11:10","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 EEG dataset recorded during affective music listening\",\n  \"description\": \"This dataset comprises unprocessed EEG recordings from 31 healthy adult participants (age 18-66, 18 female) listening to 40 music clips of 12 s duration each of varying emotional content. The study investigates neural correlates of music-induced emotion through six runs of EEG recordings, including resting-state baseline and four music listening runs. Data were collected at 1 kHz sampling rate and are accompanied by participants' self-reported emotional responses, providing a resource for studying the relationship between brain activity and affective music perception. The musical stimuli were excerpts from film scores selected from Eerola & Vuoskoski (2010).\",\n  \"methods_description\": \"EEG data were recorded at 1 kHz sampling rate while 31 participants listened to 40 music clips (12 s duration each) from film scores spanning multiple styles and emotional ratings. The experimental paradigm consisted of 6 runs: two resting-state runs (300 s each) at the beginning and end, and four music listening runs containing 10 trials each. EEG segments corresponding to music clips were 12 s in duration. Participants reported induced emotional responses following stimulus presentation.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Ian Daly\": {},\n    \"Nicoletta Nicolaou\": {},\n    \"Duncan Williams\": {},\n    \"Faustina Hwang\": {},\n    \"Alexis Kirke\": {},\n    \"Eduardo Miranda\": {},\n    \"Slawomir J. Nasuto\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"emotion recognition\"\n    },\n    {\n      \"term\": \"music perception\"\n    },\n    {\n      \"term\": \"affective neuroscience\"\n    },\n    {\n      \"term\": \"brain-computer interfaces\"\n    },\n    {\n      \"term\": \"neural correlates\"\n    },\n    {\n      \"term\": \"music\"\n    },\n    {\n      \"term\": \"resting state\"\n    },\n    {\n      \"term\": \"emotion\"\n    },\n    {\n      \"term\": \"film scores\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.18112/openneuro.ds002721.v1.0.2\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsIdenticalTo\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on002721\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataexplorer/detail?dataset_id=on002721\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1177/0305735610362821\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.1016/j.neulet.2014.05.003\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1109/EMBC.2014.6944647\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1016/j.bandc.2015.08.003\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1038/sdata.2018.203\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.38119/openneuro.ds002721\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsIdenticalTo\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"Engineering and Physical Sciences Research Council\",\n      \"award_number\": \"EP/J003077/1\"\n    },\n    {\n      \"funder_name\": \"Engineering and Physical Sciences Research Council\",\n      \"award_number\": \"EP/J002135/1\"\n    }\n  ],\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"3.6 GB (187 files)\"\n  ],\n  \"formats\": [\n    \".edf\",\n    \".gitattributes\",\n    \".json\",\n    \".m\",\n    \".md\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"d60464efe07d35150acfc55dc2a63f6c15e5995293c2ba5331562b8a36de39c2\"\n}","last_activity_at":"2026-06-21 07:30:54","source":"openneuro","source_id":"ds002721","subject_count":31,"modalities":"eeg","age_min":18,"age_max":66,"file_size":3598855791,"total_files":935,"tasks":"run1,run2,run3,run4,run5,run6","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Ian Daly, Nicoletta Nicolaou, Duncan Williams, Faustina Hwang, Alexis Kirke, Eduardo Miranda, Slawomir J. Nasuto","license":"CC0","readme":"0. Sections\n------------\n1. Project\n2. Dataset\n3. Terms of Use\n4. Contents\n5. Method and Processing\n1. PROJECT\n------------\n\nTitle: Brain-Computer Music Interface for Monitoring and Inducing Affective States (BCMI-MIdAS)\n\nDates: 2012-2017\n\nFunding organisation: Engineering and Physical Sciences Research Council (EPSRC)\n\nGrant no.: EP/J003077/1 and EP/J002135/1.\n\n2. DATASET\n------------\nTitle: EEG data investigating neural correlates of music-induced emotion.\n\nDescription: This dataset accompanies the publication by Daly et al. (2018) and has been analysed in Daly et al. (2014; 2015a; 2015b) (please see Section 5 for full references). The purpose of the research activity in which the data were collected was to investigate the EEG neural correlates of music-induced emotion. For this purpose 31 healthy adult participants listened to 40 music clips of 12 s duration each, targeting a range of emotional states. The music clips comprised excerpts from film scores spanning a range of styles and rated on induced emotion. \nThe dataset contains unprocessed EEG data from all 31 participants (age range 18-66, 18 female) while listening to the music clips, together with the reported induced emotional responses . The paradigm involved 6 runs of EEG recordings. The first and last runs were resting state runs, during which participants were instructed to sit still and rest for 300 s. The other 4 runs each contained 10 music listening trials.\n\nPublication Year: 2018\n\nCreator: Nicoletta Nicolaou, Ian Daly.\n\nContributors: Isil Poyraz Bilgin, James Weaver, Asad Malik. \n\nPrincipal Investigator: Slawomir Nasuto (EP/J003077/1).\n\nCo-Investigator: Eduardo Miranda (EP/J002135/1).\n\nOrganisation: University of Reading\n\nRights-holders: University of Reading\n\nSource: The musical stimuli were taken from Eerola & Vuoskoski, “A comparison of the discrete and dimensional models of emotion in music”, Psychol. Music, 39:18-49, 2010 (doi: 10.1177/0305735610362821). Stimuli set 1 was used (https://www.jyu.fi/hytk/fi/laitokset/mutku/en/research/projects2/past-projects/coe/materials/emotion/soundtracks/set1/view)\n\nSystem: The data is prepared for use on Windows systems and no garanantee is made that the datasets can be opened correctly on other systems.\n\n3. TERMS OF USE\n-----------------\n\nCopyright University of Reading, 2018. This dataset is licensed by the rights-holder(s) under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/.\n\n4. CONTENTS\n------------\n\nBIDS File listing:\nThe dataset comprises data from 31 participants, named using the convention:\nsub_s_number\nwhere: s_number is a random participant number from 1 to 31. For example: ‘sub-08’ contains data obtained from participant 8. \n\nThe data is BIDS format and contains EEG and associated meta data. The sampling rate is 1 kHz and the EEG corresponding to a music clip is 20 s long (the duration of the clips).\n\nEach data folder contains the following data (please note that the number of runs varies between participants):\n\n5. METHOD and PROCESSING\n--------------------------\n\nThis information is available in the following publications:\n\n[1] Daly, I., Nicolaou, N., Williams, D., Hwang, F., Kirke, A., Miranda, E., Nasuto, S.J., Ԏeural and physiological data from participants listening to affective musicԬ Scientific Data, 2018.\n[2] Daly, I., Malik, A., Hwang, F., Roesch, E., Weaver, J., Kirke, A., Williams, D., Miranda, E. R., Nasuto, S. J., Ԏeural correlates of emotional responses to music: an EEG studyԬ Neuroscience Letters, 573: 52-7, 2014; doi: 10.1016/j.neulet.2014.05.003.\n[3] Daly, I., Hallowell, J., Hwang, F., Kirke, A., Malik, A., Roesch, E., Weaver, J., Williams, D., Miranda, E., Nasuto, S.J., ԃhanges in music tempo entrain movement related brain activityԬ Proc. IEEE EMBC 2014, pp.4595-8; doi: 10.1109/EMBC.2014.6944647\n[4] Daly, I., Williams, D., Hallowell, J., Hwang, F., Kirke, A., Malik, A., Weaver, J., Miranda, E., Nasuto, S.J., ԍusic-induced emotions can be predicted from a combination of brain activity and acoustic featuresԬ Brain and Cognition, 101:1-11, 2015b; doi: 10.1016/j.bandc.2015.08.003\n\nPlease cite these references if you use this dataset in your study.\n\nThank you for your interest in our work.\n","bids_version":"1.0.2","sessions_count":null,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-09-06 13:30:14","zarr_store_count":0,"zarr_index_etag":"1b2e9a8a95fd1e47412b2d637067dc43","zarr_source_commit":"82da2665513c096287c8d5461175d3a7f08b9b55","archive_status":"ready","archive_size":3419731525,"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":19,"electrode_system":"10-20","has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":3596432439,"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":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":1000,"power_line_frequency":50,"eeg_reference":"placed on FCz","placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-06-21 07:35:52\",\"metadata_updated_at\":\"2026-06-21 07:35:53\",\"archive_checked_at\":\"2026-06-21 07:39:26\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-21 07:44:01\",\"citations_updated_at\":\"2026-09-08 03:00:53\",\"channel_montage_checked_at\":\"2026-06-28 23:07:55\",\"hed_checked_at\":\"2026-06-30 04:38:55\",\"data_checked_at\":\"2026-07-29 03:00:11\",\"availability_report_at\":\"2026-07-23 01:12:20\",\"signal_defaults_at\":\"2026-09-02 11:56:15\",\"recording_stats_at\":\"2026-09-07 03:00:57\"}","participants":31,"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":"3.35 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/on002721/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}}