Music genre neuroimaging dataset
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Updated: Oct 9, 2025

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals
Published on: May 23, 2017
Tomoya Nakai1,2,3, Naoko Koide-Majima1,4, Shinji Nishimoto1,4,5
1Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan.
Abstract:
This dataset includes functional magnetic resonance imaging (fMRI) data collected while five subjects extensively listened to 540 music pieces from 10 music genres over the course of 3 days. Behavioral data are also available. Data are separated into training and test samples to facilitate the application of machine learning algorithms. Test stimuli were repeated four times and can be used to evaluate the signal to noise ratio of brain activity. Using this dataset, both neuroimaging and machine learning researchers can test multiple algorithms regarding the prediction performance of brain activity induced by various music stimuli. Although two previous studies have used this dataset, there remains much room to apply different acoustic models. This dataset can contribute to integration of the fields of auditory neuroscience and machine learning.
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