NDLI: Principal Component Analysis of fMRI Data in Local Frequency Domain

Content Provider	IEEE Xplore Digital Library
Author	Zonglei Zhen Jie Tian Hui Zhang
Copyright Year	2007
Description	Author affiliation: Chinese Acad. of Sci., Beijing (Zonglei Zhen; Jie Tian; Hui Zhang)
Abstract	Most established activation detection techniques for functional magnetic resonance imaging(fMRI) data are always based on oversimplified assumptions that no spatial or temporal correlations exist in the data. In this article, we strive for analysis of fMRI data in local frequency domain with multitaper frequency-domain singular value decomposition(MTM-SVD) technique which explicitly takes into account the intrinsic spatiotemporal correlations in the data and allows modeling patterns of spatiotemporal dynamics of brain activity. A local frequency-based representation well captures the features of BOLD signal evoked by experimental designs with periodic stimuli and the dominant physiology noise, therefore we can utilize principal component analysis to decompose fMRI data in local frequency domain and extract the spatiotemporal patterns of the brain activity. We have made experiment on real fMRI data, and the results demonstrated that our approach could detect the brain activity patterns effectively and reliably.
Starting Page	656
Ending Page	660
File Size	4294852
Page Count	5
File Format	PDF
ISBN	9781424410774
DOI	10.1109/ICCME.2007.4381819
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data analysis Magnetic resonance Brain modeling Design for experiments Physiology Spatiotemporal phenomena Magnetic analysis Pattern analysis Frequency domain analysis Principal component analysis
Content Type	Text
Resource Type	Article

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