Scaled subprofile modeling of resting state imaging data in Parkinson's disease: methodological issues.
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ABSTRACT:
SUBMITTER: Spetsieris PG
PROVIDER: S-EPMC3020239 | biostudies-literature | 2011 Feb
REPOSITORIES: biostudies-literature
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Scaled subprofile modeling of resting state imaging data in Parkinson's disease: methodological issues.
Spetsieris Phoebe G PG Eidelberg David D
NeuroImage 20101020 4
Consistent functional brain abnormalities in Parkinson's disease (PD) are difficult to pinpoint because differences from the normal state are often subtle. In this regard, the application of multivariate methods of analysis has been successful but not devoid of misinterpretation and controversy. The Scaled Subprofile Model (SSM), a principal components analysis (PCA)-based spatial covariance method, has yielded critical information regarding the characteristic abnormalities of functional brain o ...[more]
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