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 …

Brain graphs provide a relatively simple and increasingly popular way of modeling the
human brain connectome, using graph theory to abstractly define a nervous system as a set …

Brain connectivity datasets comprise networks of brain regions connected by anatomical
tracts or by functional associations. Complex network analysis—a new multidisciplinary …

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

The human brain is a complex network of interlinked regions. Recent studies have
demonstrated the existence of a number of highly connected and highly central neocortical …

Connectivity analyses and computational modeling of human brain function from fMRI data
frequently require the specification of regions of interests (ROIs). Several analyses have …

Human learning is a complex phenomenon requiring flexibility to adapt existing brain
function and precision in selecting new neurophysiological activities to drive desired …

The network architecture of functional connectivity within the human brain connectome is
poorly understood at the voxel level. Here, using resting state functional magnetic …

Graph theory is a valuable framework to study the organization of functional and anatomical
connections in the brain. Its use for comparing network topologies, however, is not without …

Neuronal networks, similar to many other complex systems, self-organize into fascinating
emergent states that are not only visually compelling, but also vital for the proper functioning …