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Neuroscience needs Network Science
We explore the challenges and opportunities in integrating multiple data streams for understanding the neural transitions from development to healthy function to disease, and discuss the potential for collaboration between network science and neuroscience communities.
Partial entropy decomposition reveals higher-order structures in human brain activity
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.
Edges in Brain Networks: Contributions to Models of Structure and Function
Here, we underscore the important contributions made by brain network edges for understanding distributed brain organization.
Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays
Recently, linear formulations and convex optimization methods have been proposed to predict diffusion-weighted Magnetic Resonance Imaging (dMRI) data given estimates of brain connections generated using tractography algorithms.
Weight-conserving characterization of complex functional brain networks
Important functional network measures include measures of modularity (measures of the goodness with which a network is optimally partitioned into functional subgroups) and measures of centrality (measures of the functional influence of individual brain regions).
