High-resolution 7-Tesla fMRI data on the perception of musical genres – an extension to the studyforrest dataset

Hanke, Michael; Dinga, Richard; Christian, Häusler; Guntupalli, J. Swaroop; Casey, Michael A.; Kaule, Falko R. and Stadler, Jörg. 2015. High-resolution 7-Tesla fMRI data on the perception of musical genres – an extension to the studyforrest dataset. F1000Research, 4, p. 174. ISSN 2046-1402 [Article]

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Abstract or Description

Here we present an extension to the studyforrest dataset – a versatile resource for studying the behavior of the human brain in situations of real-life complexity (http://studyforrest.org). This release adds more high-resolution, ultra high-field (7 Tesla) functional magnetic resonance imaging (fMRI) data from the same individuals. The twenty participants were repeatedly stimulated with a total of 25 music clips, with and without speech content, from five different genres using a slow event-related paradigm. The data release includes raw fMRI data, as well as precomputed structural alignments for within-subject and group analysis. In addition to fMRI, simultaneously recorded cardiac and respiratory traces, as well the complete implementation of the stimulation paradigm, including stimuli, are provided. An initial quality control analysis reveals distinguishable patterns of response to individual genres throughout a large expanse of areas known to be involved in auditory and speech processing. The present data can be used to, for example, generate encoding models for music perception that can be validated against the previously released fMRI data from stimulation with the “Forrest Gump” audio-movie and its rich musical content. In order to facilitate replicative and derived works, only free and open-source software was utilized.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.12688/f1000research.6679.1

Keywords:

functional magnetic resonance imaging, music perception, natural sounds, 7 Tesla, auditory features

Departments, Centres and Research Units:

Computing > Intelligent Sound and Music Systems (ISMS)

Dates:

DateEvent
29 June 2015Published
22 June 2015Accepted

Item ID:

17627

Date Deposited:

01 Apr 2016 13:31

Last Modified:

28 Oct 2020 15:59

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

https://research.gold.ac.uk/id/eprint/17627

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