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A Canonical Correlation Analysis of Intelligence and Executive Functioning
Applied Neuropsychology, 2011Executive functioning is one of the most researched and debated topics in neuropsychology. Although neuropsychologists routinely consider executive functioning and intelligence in their assessment process, more information is needed regarding the relationship between these constructs.
Andrew S, Davis +2 more
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Detection of neural activity in functional MRI using canonical correlation analysis
Magnetic Resonance in Medicine, 2001A novel method for detecting neural activity in functional magnetic resonance imaging (fMRI) data is introduced. It is based on canonical correlation analysis (CCA), which is a multivariate extension of the univariate correlation analysis widely used in fMRI.
Ola Friman +2 more
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Nonlinear functional canonical correlation analysis via distance covariance
Journal of Multivariate Analysis, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hanbing Zhu +3 more
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Canonical correlation analysis applied to functional connectivity in MEG
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010We present a multivariate method based on canonical correlation analysis for the study of functional connectivity in the brain with MEG data. We obtain a time-frequency representation of the brain activity on the cortical surface, and use the signal power at specific frequency bands as inputs to our model. Our measure of interaction between two spatial
Sylvain Baillet
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Canonical correlation analysis of brain prefrontal activity measured by functional near infra-red spectroscopy (fNIRS) during a moral judgment task [PDF]
Behavioural Brain Research, 2019 Individuals differ in the extent to which they make decisions in different moral dilemmas. In this study, we investigated the relationship between functional brain activities during moral decision making and psychopathic personality traits in a healthy ...
Hadis Dashtestani +2 more
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Unconstrained Functional Criteria for Canonical Correlation Analysis
2005 IEEE International Symposium on Circuits and Systems, 2005Unconstrained and constrained optimization criteria for extracting multiple true canonical variates and canonical correlations are proposed. These include a weighted information criterion (WINC-CCA) and a shifted information criterion (SINC-CCA) for searching the optimal solutions.
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Inferring gene–gene interactions and functional modules using sparse canonical correlation analysis
Annals of Applied Statistics, 2015 Published at http://dx.doi.org/10.1214/14-AOAS792 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Y X Rachel Wang +2 more
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Psychometrika, 2017
Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space.
Choi, Ji Yeh +4 more
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Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space.
Choi, Ji Yeh +4 more
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A square root merit function for Canonical Correlation Analysis
2009 IEEE International Symposium on Circuits and Systems, 2009Canonical Correlation Analysis (CCA) is a well-known technique in multivariate statistical analysis, which has been widely used in economics, meteorology, and in many modern information processing fields. This paper proposes many dynamical systems for computing canonical correlations and canonical variates.
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A weighted logarithmic merit function for canonical correlation analysis
2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009A weighted logarithmic merit function that incorporates a diagonal matrix is utilized for deriving a gradient dynamical system that converges to the actual canonical correlation coordinates of arbitrary data matrices. The equilibrium points of the resulting gradient system are determined and their stability is thoroughly analyzed.
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