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 …

The exploration of brain networks with resting-state fMRI (rs-fMRI) combined with graph
theoretical approaches has become popular, with the perspective of finding network graph …

Networks have become a standard tool for analyzing functional magnetic resonance
imaging (fMRI) data. In this approach, brain areas and their functional connections are …

There is significant interest, both from basic and applied research perspectives, in
understanding how structural/functional connectivity changes can explain behavioral …

Graph theory has recently received a lot of attention from the neuroscience community as a
method to represent and characterize brain networks. Still, there is a lack of a gold standard …

Functional and structural neuronal networks, as recorded by resting-state functional MRI and
diffusion MRI-based tractography, gain increasing attention as data driven whole brain …

Objective. The use of non-invasive techniques for the estimation of structural brain networks
(ie connectomes) opened the door to large-scale investigations on the functioning and the …

Connectivity, and network-level features in general, have proven to be valuable tools in
several aspects of neuroscience research. Although network analysis is rooted in analysis of …

Graph theoretical analysis of the structural connectome has been employed successfully to
characterize brain network alterations in patients with traumatic brain injury (TBI). However …

Network science holds great promise for expanding our understanding of the human brain in
health, disease, development, and aging. Network analyses are quickly becoming the …