{"dataset":{"id":"54503","dataset_id":"on003774","name":"Music Listening- Genre EEG dataset (MUSIN-G)","description":"This dataset comprises electroencephalography (EEG) recordings from 20 Indian participants listening to 12 songs spanning diverse genres, from Indian Classical to Goth Rock. Participants rated their familiarity and enjoyment of each song on a 5-point scale following passive listening. The dataset provides neurophysiological measures of music perception and aesthetic response across genre diversity.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on003774","concept_doi":"10.82901/nemar.on003774","latest_version_doi":"10.82901/nemar.on003774.v1.0.0","created_at":"2026-06-22 16:01:29","updated_at":"2026-07-10 22:20:25","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Music Listening- Genre EEG dataset (MUSIN-G)\",\n  \"description\": \"This dataset comprises electroencephalography (EEG) recordings from 20 Indian participants listening to 12 songs spanning diverse genres, from Indian Classical to Goth Rock. Participants rated their familiarity and enjoyment of each song on a 5-point scale following passive listening. The dataset provides neurophysiological measures of music perception and aesthetic response across genre diversity.\",\n  \"methods_description\": \"EEG recordings were obtained while participants listened to 12 songs of different genres presented via speakers. Each session began with a single beep cueing participants to close their eyes, followed by song presentation. After each song, a double beep signaled participants to open their eyes and rate familiarity and enjoyment on a 5-point scale (1=most familiar/enjoyable, 5=least familiar/enjoyable).\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Krishna Prasad Miyapuram\": {},\n    \"Pankaj Pandey\": {},\n    \"Nashra Ahmad\": {},\n    \"Bharatesh R Shiraguppi\": {},\n    \"Esha Sharma\": {},\n    \"Prashant Lawhatre\": {},\n    \"Dhananjay Sonawane\": {},\n    \"Derek Lomas\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"music perception\"\n    },\n    {\n      \"term\": \"genre classification\"\n    },\n    {\n      \"term\": \"aesthetic response\"\n    },\n    {\n      \"term\": \"electroencephalography\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on003774\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataexplorer/detail?dataset_id=on003774\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds003774.v1.0.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"10.9 GB (243 files)\"\n  ],\n  \"formats\": [\n    \".gitattributes\",\n    \".json\",\n    \".md\",\n    \".set\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"b85441fb1a5a7d5a133b5932adb5340679cfd68041d73fa97b8ef2eb5d1e2fa5\"\n}","last_activity_at":"2026-06-22 16:01:29","source":"openneuro","source_id":"ds003774","subject_count":20,"modalities":"eeg","age_min":null,"age_max":null,"file_size":10863713824,"total_files":1690,"tasks":"MusicListening","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Krishna Prasad Miyapuram, Pankaj Pandey, Nashra Ahmad, Bharatesh R Shiraguppi, Esha Sharma, Prashant Lawhatre, Dhananjay Sonawane, Derek Lomas","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003774-blue)](https://doi.org/10.82901/nemar.on003774)\n\nThe dataset contains Electroencephalography (EEG) responses from 20 Indian participants, on 12 songs of different genres (from Indian Classical to Goth Rock). Each session indicates a song by its number. \n\nFor the experiment,  the participants were indicated to close their eyes indicated by a single beep, and the song was presented to them on speakers. After listening to each song, a double beep was presented, asking them to open their eyes and rate their familiarity and enjoyment to the song.  The responses were taken on a scale of 1 to 5, where 1 meant most familiar or most enjoyable, and 5 meant least familiar or least enjoyable. 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