Naturalistic Music EEG Dataset - Tempo (NMED-T)

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Abstract/Contents

Abstract: This dataset contains cortical (EEG) and behavioral data collected during natural music listening. Dense-array EEG was recorded from 20 adult participants who each heard a set of 10 full-length songs with electronically produced beats at various tempos. In a separate subsequent listen, each participant tapped to the beat of a 35-second excerpt from each song. Participants also delivered ratings of familiarity and enjoyment for each full-length song during the EEG recording. Finally, the dataset includes basic demographic information about the participants, as well as Matlab scripts to perform the illustrated analyses presented in the paper introducing the dataset (Losorelli et al., 2017). Cleaned and aggregated data are published in Matlab format; raw EEG is published in Matlab format, while raw tapping data are published in .txt format. Stimulus audio is not published, but metadata links are provided. Cleaned EEG files have been aggregated across participants on a per-song basis and range in size from 656-721MB. Raw EEG recordings (two recordings per participant) range in size from 753-861MB. All other files are less than 1MB in size. In total the dataset comprises 55 downloadable files, with a total size of 39GB.

Type of resource	software, multimedia
Date created	2017

Subject	Electroencephalography
Subject	ongoing EEG
Subject	naturalistic music
Subject	music cognition
Subject	beat processing
Subject	music information retrieval
Subject	sensorimotor synchronization
Subject	Center for the Study of Language and Information
Subject	Center for Computer Research in Music and Acoustics
Genre	Dataset

Related Publication	Steven Losorelli, Duc T. Nguyen, Jacek P. Dmochowski, and Blair Kaneshiro. 2017. NMED-T: A Tempo-Focused Dataset of Cortical and Behavioral Responses to Naturalistic Music. In Proceedings of the 18th International Society for Music Information Retrieval Conference, Suzhou, China. https://ismir2017.smcnus.org/wp-content/uploads/2017/10/198_Paper.pdf
Related item	Title Losorelli et al. (to appear) ISMIR preprint.
Location	https://purl.stanford.edu/jn859kj8079

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License: This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).

Preferred Citation: Steven Losorelli, Duc T. Nguyen, Jacek P. Dmochowski, and Blair Kaneshiro (2017). Naturalistic Music EEG Dataset - Tempo (NMED-T). Stanford Digital Repository. Available at: http://purl.stanford.edu/jn859kj8079

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