High-resolution 7-Tesla fMRI data on the perception of musical genres – an extension to the studyforrest dataset
- Submitting institution
-
Goldsmiths' College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2898
- Type
- D - Journal article
- DOI
-
10.12688/f1000research.6679.1
- Title of journal
- F1000Research
- Article number
- 174
- First page
- -
- Volume
- 4
- Issue
- -
- ISSN
- 2046-1402
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
http://research.gold.ac.uk/id/eprint/17627/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
6
- Research group(s)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- new rating_x000D_
_x000D_
The initial quality control analysis of this study reveals distinguishable patterns of response to individual genres throughout an expanse of areas known to be involved in auditory and speech processing. The present data can be used to generate encoding models for music perception that can be validated against the previously released fMRI data from stimulation with the_x000D_
“Forrest Gump” audio-movie. It is hoped that providing these example features, they will catalyze discoveries of auditory stimulus codes in neural populations. The data can also serve as a public resource for benchmarking algorithms for functional alignment
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
