Generation of stimulus features for analysis of FMRI during natural auditory experiences

Valeri Tsatsishvili, Fengyu Cong, Tapani Ristaniemi, Petri Toiviainen, Vinoo Alluri, Elvira Brattico, Asoke Nandi

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Abstract

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 its superiority over PCA in various applications, 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.

Original languageEnglish
Title of host publicationEuropean Signal Processing Conference
Number of pages5
PublisherEuropean Signal Processing Conference, EUSIPCO
Publication date10 Nov 2014
Pages2490-2494
Article number6952938
ISBN (Print)9780992862619
Publication statusPublished - 10 Nov 2014
Event22nd European Signal Processing Conference, EUSIPCO 2014 - Lisbon, Portugal
Duration: 1 Sept 20145 Sept 2014

Conference

Conference22nd European Signal Processing Conference, EUSIPCO 2014
Country/TerritoryPortugal
CityLisbon
Period01/09/201405/09/2014

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