Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing,
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …

Although covarying for potential confounds or nuisance variables is common in
psychological research, relatively little is known about how the inclusion of covariates may …

Conventional group analysis is usually performed with Student-type t-test, regression, or
standard AN (C) OVA in which the variance–covariance matrix is presumed to have a simple …

Aiming at abundant scientific and engineering data with not only high dimensionality but
also complex structure, we study the regression problem with a multidimensional array …

Despite the growing importance of longitudinal data in neuroimaging, the standard analysis
methods make restrictive or unrealistic assumptions (eg, assumption of Compound …

We present an extension of the Linear Mixed Effects (LME) modeling approach to be applied
to the mass-univariate analysis of longitudinal neuroimaging (LNI) data. The proposed …

This book explores various state-of-the-art aspects behind the statistical analysis of
neuroimaging data. It examines the development of novel statistical approaches to model …

Repeated measurements and multimodal data are common in neuroimaging research.
Despite this, conventional approaches to group level analysis ignore these repeated …

Multiway data-related learning tasks pose a huge challenge to the traditional regression
analysis techniques due to the existence of multidirectional relatedness. Simply vectorizing …

More and more large-scale imaging genetic studies are being widely conducted to collect a
rich set of imaging, genetic, and clinical data to detect putative genes for complexly inherited …