title: Improving the spatial specificity of canonical correlation analysis in fMRI.
abstract: 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.
authors.affiliation: Department of Radiology, University of Washington, Seattle, Washington 98195, USA. nandy@u.washington.edu
authors.forename: Rajesh
authors.initials: R
authors.lastname: Nandy
authors.forename: Dietmar
authors.initials: D
authors.lastname: Cordes
mesh_terms: D000328:Adult; D001931:Brain Mapping; D005583:Fourier Analysis; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D012372:ROC Curve; D012044:Regression Analysis; D012680:Sensitivity and Specificity