Many complex networks have a small-world topology characterized by dense local
clustering or cliquishness of connections between neighboring nodes yet a short path length …

Brain function depends on adaptive self-organization of large-scale neural assemblies, but
little is known about quantitative network parameters governing these processes in humans. …

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

The brain is an inherently dynamic system, and executive cognition requires dynamically
reconfiguring, highly evolving networks of brain regions that interact in complex and transient …

Despite substantial recent progress, our understanding of the principles and mechanisms
underlying complex brain function and cognition remains incomplete. Network neuroscience …

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 of …

Many functional network properties of the human brain have been identified during rest and
task states, yet it remains unclear how the two relate. We identified a whole-brain network …

Schizophrenia has often been conceived as a disorder of connectivity between components
of large-scale brain networks. We tested this hypothesis by measuring aspects of both …

The complex organization of connectivity in the human brain is incompletely understood.
Recently, topological measures based on graph theory have provided a new approach to …

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