Generalized Covariance Analysis (gCVA)
Generalized Covariance Analysis: a platform for any PCA-based analysis on functional neuroimaging data (PET and fMRI).
Includes:
- Ordinal Trend Canonical Variance Analysis for parametric designs
(C. Habeck et al. A New Approach to Spatial Covariance Modeling of Functional Brain Imaging Data: Ordinal Trend Analysis. Neural Computation 2005; 17: 1602-1645)
- Partial Least Squares for any design matrix
- Subprofile Scaling Model for cross-sectional designs
(JR. Moeller, Strother SC. A regional covariance approach to the analysis of functional patterns in positron emission tomographic data.J Cereb Blood Flow Metab. 1991 Mar;11(2):A121-35.)
Includes:
- Ordinal Trend Canonical Variance Analysis for parametric designs
(C. Habeck et al. A New Approach to Spatial Covariance Modeling of Functional Brain Imaging Data: Ordinal Trend Analysis. Neural Computation 2005; 17: 1602-1645)
- Partial Least Squares for any design matrix
- Subprofile Scaling Model for cross-sectional designs
(JR. Moeller, Strother SC. A regional covariance approach to the analysis of functional patterns in positron emission tomographic data.J Cereb Blood Flow Metab. 1991 Mar;11(2):A121-35.)
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Recent Activity - Files
GCVA_PCA.zip posted by Christian Habeck on Aug 22, 2011
PCASuiteDocumentationCONSOLIDATED.pdf posted by Christian Habeck on Apr 13, 2010
GCVA_Package.zip posted by Christian Habeck on Apr 13, 2010