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 …

Over the past 15 years, the emerging field of network science has revealed the key features
of brain networks, which include small‐world topology, the presence of highly connected …

Although graph theory has been around since the 18th century, the field of network science
is more recent and continues to gain popularity, particularly in the field of neuroimaging. The …

Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to
methods for unraveling the extraordinary complexity of neuronal connectivity. From the …

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

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 …

Considering the brain as a complex network of interacting dynamical systems offers new
insights into higher level brain processes such as memory, planning, and abstract reasoning …

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 …

Neurological and psychiatric disorders disturb higher cognitive functions and are
accompanied by aberrant cortico-cortical axonal pathways or synchronizations of neural …

It is nearly 20 years since the concept of a small-world network was first quantitatively
defined, by a combination of high clustering and short path length; and about 10 years since …