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Improving the spatial specificity of canonical correlation analysis in fMRI
Author(s) -
Nandy Rajesh,
Cordes Dietmar
Publication year - 2004
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.20234
Subject(s) - univariate , canonical correlation , correlation , context (archaeology) , multivariate statistics , sensitivity (control systems) , pattern recognition (psychology) , computer science , contrast (vision) , artificial intelligence , noise (video) , multivariate analysis , spatial correlation , statistics , mathematics , image (mathematics) , biology , paleontology , geometry , electronic engineering , engineering
The contrast‐to‐noise ratio (CNR) is often very low in fMRI data, and standard univariate methods suffer from a loss of sensitivity in the context of noise. The increased power of a multivariate statistical analysis method known as canonical correlation analysis (CCA) in fMRI studies with low CNR was established previously. However, CCA in its conventional form has weak spatial specificity. In this work we propose a new assignment scheme to rectify this problem. It is shown that the new method has improved spatial specificity as well as sensitivity compared to conventional CCA for detecting activation patterns in fMRI. Magn Reson Med 52:947–952, 2004. © 2004 Wiley‐Liss, Inc.