Naturalistic Music EEG Dataset - Hindi (NMED-H)
Abstract/Contents
- Abstract
- The NMED-H dataset contains scalp EEG responses recorded from 48 adults as they heard intact and scrambled versions of full-length vocal works (Hindi pop songs). Sixteen stimuli were included in the experiment: Four songs in four conditions per song. Twelve participants were assigned to each stimulus, and each participant heard their assigned stimuli twice (24 trials total per stimulus). Dense-array EEG was recorded using the Electrical Geodesics, Inc. (EGI) GES 300 platform. Data are published in Matlab format. The dataset contains (1) raw EEG (individual recordings, 97 files), (2) clean EEG (aggregated by stimulus and listen, 32 files), (3) spatially filtered EEG (aggregated by stimulus condition, four files), (4) behavioral responses (grouped by listen, two files), and (5) participant-stimulus assignment file. Items (1) - (3) are compressed in .zip archives (500 MB - 2 GB each); an example file from each archive can be downloaded separately. Items (4) and (5) are < 1 KB each. This dataset can be used in combination with the Naturalistic Music EEG Dataset - Tempo (NMED-T).
Description
| Type of resource | software, multimedia |
|---|---|
| Date created | 2014 - 2016 |
Creators/Contributors
| Author | Kaneshiro, Blair | |
|---|---|---|
| Author | Nguyen, Duc T. | |
| Author | Dmochowski, Jacek P. | |
| Author | Norcia, Anthony M. | |
| Principal investigator | Berger, Jonathan |
Subjects
| Subject | Electroencephalography |
|---|---|
| Subject | Ongoing EEG |
| Subject | Naturalistic music |
| Subject | Music cognition |
| Subject | Center for Computer Research in Music and Acoustics |
| Subject | CCRMA |
| Subject | Music Engagement Research Initiative |
| Genre | Dataset |
Bibliographic information
| Related Publication | Blair Kaneshiro, Duc T. Nguyen, Anthony M. Norcia, Jacek P. Dmochowski, and Jonathan Berger (2020). Natural Music Evokes Correlated EEG Responses Reflecting Temporal Structure and Beat. NeuroImage 214, 116559. doi:10.1016/j.neuroimage.2020.116559 |
|---|---|
| Related Publication | Blair Kaneshiro, Duc T. Nguyen, Jacek P. Dmochowski, Anthony M. Norcia, and Jonathan Berger (2019). Naturalistic Music EEG Dataset - Hindi (NMED-H) 2.0: New Release and Cross-Dataset Compatibility. In Extended Abstracts for the Late-Breaking Demo Session of the 20th International Society for Music Information Retrieval Conference, Delft, The Netherlands. |
| Related Publication | Nick Gang, Blair Kaneshiro, Jonathan Berger, and Jacek P. Dmochowski (2017). Decoding Neurally Relevant Musical Features Using Canonical Correlation Analysis. In Proceedings of the 18th International Society for Music Information Retrieval Conference, Suzhou, China. doi:10.5281/zenodo.1417137 |
| Related Publication | Steven Losorelli, Duc T. Nguyen, Jacek P. Dmochowski, and Blair Kaneshiro (2017). Naturalistic Music EEG Dataset - Tempo (NMED-T). Stanford Digital Repository. https://purl.stanford.edu/jn859kj8079 |
| 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. doi:10.5281/zenodo.1417917 |
| Related Publication | Blair Kaneshiro (2016). Toward an Objective Neurophysiological Measure of Musical Engagement. Doctoral Dissertation, Stanford University. |
| Related item | |
| Location | https://purl.stanford.edu/sd922db3535 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
Preferred citation
- Preferred Citation
- Blair Kaneshiro, Duc T. Nguyen, Jacek P. Dmochowski, Anthony M. Norcia, and Jonathan Berger (2016). Naturalistic Music EEG Dataset - Hindi (NMED-H). Stanford Digital Repository. Available at: http://purl.stanford.edu/sd922db3535
Collection
Stanford Research Data
View other items in this collection in SearchWorksContact information
- Contact
- blairbo@ccrma.stanford.edu
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