Simple models of human brain functional networks

By Petra E. Vértes, Aaron F. Alexander-Bloch, Nitin Gogtay, Jay N. Giedd, Judith L. Rapoport, E. Bullmore. Proceedings of the National Academy of Sciences of the United States of America, 2012

361 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/68e5cee9e78e366b3ad52d7186d59d9cf9b22773

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review (2019, background): “Theoretical examinations have pointed out that the brain regions are more likely to interact with their neighboring areas to reduce the whole metabolic costs, while at the same time they need to have a small number of long-distance connections among themselves to accelerate data transmission (Sik et”
The trees and the forest: Characterization of complex brain networks with minimum spanning trees. (2014, neutral): “Many studies have attempted to explain properties of structural and functional brain networks, as well as their relation, in terms of a few underlying principles such as optimization in the face of connection cost and speed of information processing (Bullmore and Sporns, 2012; Goñi et al., 2014; Vér”
The hubs of the human connectome are generally implicated in the anatomy of brain disorders (2014, background): “, 2013), suggesting that an economical trade-off between topological value and biological cost may be a general and scale-invariant selection pressure on the formation of nervous systems (Bullmore and Sporns, 2012; Vertes et al., 2012).”
Small-World Brain Networks Revisited (2016, methodology): “Several variants of this approach have been published, exploring a range of diﬀerent topological relationships k i,j between nodes, for example, clustering and homophily [10–12].”
Multi-scale brain networks (2016, neutral): “, 2016)—the same energetic and spatial constraints that shape network structure at the scale of brain regions and areas are at play at the cellular-level (Betzel et al., 2016a; Henriksen et al., 2016; Vértes et al., 2012).”
The minimum spanning tree: An unbiased method for brain network analysis (2015, neutral): “…also shape brain networks, such as hierarchical modularity, rich club organization, economical clustering, and, in the case of functional brain networks, the degree product of the underlying structural network (Tewarie et al., 2014; van den Heuvel and Sporns, 2011; Vertes et al., 2012).”
Growing Homophilic Networks Are Natural Navigable Small Worlds (2015, neutral): “Functional brain networks are studied in vivo using MRI techniques[33] and are usually modeled by generalizations of random models[34 – 36] requiring global network knowledge.”
Graph analysis of the human connectome: Promise, progress, and pitfalls (2013, positive): “Recently, it has been demonstrated that growing networks according to relatively simple rules, such as penalizing long-distance connections and favoring connections between nodes with common neighbors, can reproduce empirically observed variations across a range of topological properties of brain fu”
Generative models of the human connectome (2015, neutral): “, 2007a) and human functional brain networks (Vértes et al., 2012).”
Networks of anatomical covariance (2013, background): “…GM density analysis to map structural covariance in four pediatric age groups from early childhood to late adolescence in a large normative cohort (Brain Development Cooperative Group, 2012; Evans and Brain Development Cooperative Group, www.brain-child.org, 2006; Waber et al., 2007, 2012).”
Contributions and challenges for network models in cognitive neuroscience (2014, methodology): “On slow time scales, developmental growth models 96 and genera tive models 80 are beginning to identify some of the key ingredients that shape the spatial arrangement and topology of networks.”