Resting-state functional magnetic resonance imaging (fMRI) has highlighted the rich
structure of brain activity in absence of a task or stimulus. A great effort has been dedicated …

Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …

Traditionally, studies of how pain and attention modulate one another involved explicit
cognitive-state manipulations. However, emerging evidence suggests that spontaneous …

Abstract Machine learning techniques have gained prominence for the analysis of resting-
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …

Functional connectivity (FC) as measured by correlation between fMRI BOLD time courses
of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in …

The human brain is a highly dynamic system with non-stationary neural activity and rapidly-
changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been …

A promising recent development in the study of brain function is the dynamic analysis of
resting-state functional MRI scans, which can enhance understanding of normal cognition …

Dynamic functional connectivity (DFC) aims to maximize resolvable information from
functional brain scans by considering temporal changes in network structure. Recent work …

The past few years have seen an emergence of approaches that leverage temporal changes
in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome …

Graph theory-based analysis has been widely employed in brain imaging studies, and
altered topological properties of brain connectivity have emerged as important features of …