Network models describe the brain as sets of nodes and edges that represent its distributed
organization. So far, most discoveries in network neuroscience have prioritized insights that …

Network neuroscience has emphasized the connectional properties of neural elements–
cells, populations, and regions. This has come at the expense of the anatomical and …

Resting-state functional magnetic resonance imaging (MRI) has yielded seemingly
disparate insights into large-scale organization of the human brain. The brain's large-scale …

The standard approach to modeling the human brain as a complex system is with a network,
where the basic unit of interaction is a pairwise link between two brain regions. While …

One of the most well-established tools for modeling the brain is the functional connectivity
network, which is constructed from pairs of interacting brain regions. While powerful, the …

The topology of structural brain networks shapes brain dynamics, including the correlation
structure of brain activity (functional connectivity) as estimated from functional neuroimaging …

Recent work identified single time points (“events”) of high regional cofluctuation in
functional Magnetic Resonance Imaging (fMRI) which contain more large-scale brain …

Progress in scientific disciplines is accompanied by standardization of terminology. Network
neuroscience, at the level of macroscale organization of the brain, is beginning to confront …

In the absence of external stimuli, neural activity continuously evolves from one
configuration to another. Whether these transitions or explorations follow some underlying …

Edge time series are increasingly used in brain imaging to study the node functional
connectivity (nFC) dynamics at the finest temporal resolution while avoiding sliding …