Human functional MRI (fMRI) research primarily focuses on analyzing data averaged across
groups, which limits the detail, specificity, and clinical utility of fMRI resting-state functional …

Functional neuroimaging studies have led to understanding the brain as a collection of
spatially segregated functional networks. It is thought that each of these networks is in turn …

In neuroscience, the functional magnetic resonance imaging (fMRI) is a vital tool to non-
invasively access brain activity. Using fMRI, the functional connectivity (FC) between brain …

Dynamic functional connectivity (dFC) analysis of resting-state fMRI data is commonly
performed by calculating sliding-window correlations (SWC), followed by k-means clustering …

Specialized processing in the brain is performed by multiple groups of brain regions
organized as functional modules. Although, in vivo studies of brain functional modules …

Functional MRI (fMRI) studies have traditionally relied on intersubject normalization based
on global brain morphology, which cannot establish proper functional correspondence …

An important aspect of network-based analysis is robust node definition. This issue is critical
for functional brain network analyses, as poor node choice can lead to spurious findings and …

Complex functional brain networks are large networks of brain regions and functional brain
connections. Statistical characterizations of these networks aim to quantify global and local …

The cerebral cortex is anatomically organized at many physical scales starting at the level of
single neurons and extending up to functional systems. Current functional magnetic …

Recently, resting-state functional magnetic resonance imaging (R-fMRI) has emerged as a
powerful tool for investigating functional brain organization changes in a variety of …