Dynamic graph metrics: Tutorial, toolbox, and tale.

ABSTRACT: The central nervous system is composed of many individual units - from cells to areas - that are connected with one another in a complex pattern of functional interactions that supports perception, action, and cognition. One natural and parsimonious representation of such a system is a graph in which nodes (units) are connected by edges (interactions). While applicable across spatiotemporal scales, species, and cohorts, the traditional graph approach is unable to address the complexity of time-varying connectivity patterns that may be critically important for an understanding of emotional and cognitive state, task-switching, adaptation and development, or aging and disease progression. Here we survey a set of tools from applied mathematics that offer measures to characterize dynamic graphs

SUBMITTER: Sizemore AE 

PROVIDER: S-EPMC5758445 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature