Generation of stimulus features for analysis of FMRI during natural auditory experiences
Tsatsishvili, V., Cong, F., Ristaniemi, T., Toiviainen, P., Alluri, V., Brattico, E., & Nandi, A. (2014). Generation of stimulus features for analysis of FMRI during natural auditory experiences. In 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO) (pp. 2490-2494). IEEE. European Signal Processing Conference.
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European Signal Processing ConferenceAuthors
Date
2014Copyright
© 2014 IEEE. This is an author's post-print version of an article whose final and definitive form has been published in the conference proceeding by IEEE.
In contrast to block and event-related designs for fMRI
experiments, it becomes much more difficult to extract
events of interest in the complex continuous stimulus for
finding corresponding blood-oxygen-level dependent
(BOLD) responses. Recently, in a free music listening fMRI
experiment, acoustic features of the naturalistic music
stimulus were first extracted, and then principal component
analysis (PCA) was applied to select the features of interest
acting as the stimulus sequences. For feature generation,
kernel PCA has shown superiority over PCA since it can
implicitly exploit nonlinear relationship among features and
such relationship seems to exist generally. Here, we applied
kernel PCA to select the musical features and obtained an
interesting new musical feature in contrast to PCA features.
With the new feature, we found similar fMRI results compared
with those by PCA features, indicating that kernel
PCA assists to capture more properties of the naturalistic
music stimulus.
...
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IEEEISBN
978-0-9928626-1-9Parent publication ISBN
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2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO)ISSN Search the Publication Forum
2219-5491Keywords
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https://converis.jyu.fi/converis/portal/detail/Publication/24056489
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