Graph theory allows assessing changes of neuronal connectivity and interactions of brain
regions in response to local lesions, eg, after stroke, and global perturbations, eg, due to …

Background: Analysis of the human connectome using functional magnetic resonance
imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to …

The human brain is a highly interconnected network. It is thus suitable for investigation with
graph theory, a branch of mathematics concerned with understanding systems of interacting …

The application of graph theory to brain networks has become increasingly popular in the
neuroimaging community. These investigations and analyses have led to a greater …

Recent developments in the quantitative analysis of complex networks, based largely on
graph theory, have been rapidly translated to studies of brain network organization. The …

Recent studies have suggested that the brain's structural and functional networks (ie,
connectomics) can be constructed by various imaging technologies (eg, EEG/MEG; …

Background Graph theory provides a powerful and comprehensive formalism of global and
local topological network properties of complex structural or functional brain connectivity …

Complex functional brain network analyses have exploded over the last decade, gaining
traction due to their profound clinical implications. The application of network science (an …

Graph theoretical analysis of neuroimaging data is growing rapidly and could potentially
provide a relatively simple but powerful quantitative framework to describe and compare …

Graph theoretical analysis of structural and functional connectivity MRI data (ie. diffusion
tractography or cortical volume correlation and resting-state or task-related (effective) fMRI …