Improving the spatial specificity of canonical correlation analysis in fMRI

Rajesh Nandy, Dietmar Cordes

Research output: Contribution to journalArticle

20 Scopus citations

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.

Original languageEnglish
Pages (from-to)947-952
Number of pages6
JournalMagnetic Resonance in Medicine
Volume52
Issue number4
DOIs
StatePublished - Oct 2004

Keywords

  • CCA
  • Canonical correlation analysis
  • Contrast-to-noise ratio
  • Multivariate statistical analysis
  • Spatial specificity
  • fMRI

Fingerprint Dive into the research topics of 'Improving the spatial specificity of canonical correlation analysis in fMRI'. Together they form a unique fingerprint.

  • Cite this