Small-World Propensity and Weighted Brain Networks

By S. Muldoon, Eric W. Bridgeford, D. Bassett. Scientific Reports, 2016

295 citations recorded by the source corpus.

Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this concept to the case of weighted brain networks by developing (i) a standardized procedure for generating weighted small-world networks, (ii) a weighted extension of the SWP, and (iii) a method for mapping observed brain network data onto the theoretical model. In applying these techniques to compare real-world brain networks, we uncover the surprising fact that the canonical biological small-world network, the C. elegans neuronal network, has strikingly low SWP. These metrics, models, and maps form a coherent toolbox for the assessment and comparison of architectural properties in brain networks.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/de5199e7d260e637e9095eaa41223e293635b572

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In Cognitive Neuroscience

In Experimental and Cognitive Psychology

Citations in the corpus

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review (2019, background): “Attention-Deﬁcit/Hyperactivity Disorder ADHD aﬀects about 3–5% of children globally (Nair et al., 2006).”
Cliques and cavities in the human connectome (2016, background): “…2010; Bullmore and Sporns 2012; Klimm et al. 2014; Lohse et al. 2014), though there are exceptions that give the brain its topological properties such as its small-world architecture (Bassett and Bullmore 2006; Pessoa 2014; Hilgetag and Goulas 2016; Muldoon et al. 2016a; Bassett and Bullmore 2016).”
Closures and Cavities in the Human Connectome (2016, background): “Often regions in the brain wire minimally to conserve wiring cost [4, 10, 38], though there are exceptions that give the brain its topological properties such as its small-world architecture [2, 45].”
Small-World Brain Networks Revisited (2016, background): “But what have we learnt more speciﬁ-cally about brain small-worldness since 2006, and what do we still have to learn?”
COVID-19 lockdown induces disease-mitigating structural changes in mobility networks (2020, unknown): “[42] S.”