Networks of the Brain: Quantitative Analysis and Modeling

By Olaf Sporns. 2010

1,760 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b5f6ee9baa07301bba6e187bd9380686a72866c6

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In Cognitive Neuroscience

Citations in the corpus

Graph Signal Processing: Overview, Challenges, and Applications (2017, background): “The network links (edge weights) are considered to be known a priori and represent the structural connectivity or the functional coherence between brain regions [170], [171].”
Neural Granger Causality (2021, background): “For example, in neuroscience it is important to determine how brain activation spreads through brain regions [1], [2], [3], [4]; in finance it is important to determine groups of stocks with low covariance to design low risk portfolios [5]; and, in biology, it is of great interest to infer gene regu”
Investigating the structure of semantic networks in low and high creative persons (2014, background): “…biological and economical networks (Boccaletti et al., 2006; Cohen and Havlin, 2010; Kenett et al., 2010; Newman, 2010) and is also widely used in studying structural and functional brain networks (Sporns, 2011; Bullmore and Sporns, 2012; Stam and van Straaten, 2012; van Straaten and Stam, 2013).”
Functional and Effective Connectivity: A Review (2011, neutral): “These are well-studied and universal characteristics of complex systems and suggest that we may be able to understand the brain in terms of universal phenomena (Sporns, 2010).”
Colloquium: Criticality and dynamical scaling in living systems (2017, background): “(ii) the statistics of multiplicative processes (Reed and Hughes, 2002; Richmond and Solomon, 2001; Sornette, 1998; Sornette and Cont, 1997), (iii) preferential attachment processes (Barabási and Albert, 1999; Simon, 1955; Yule, 1925), (iv) optimization and constrained optimiza-”
Small-World Brain Networks Revisited (2016, background): “…of nervous systems since 2006, as evidenced by rapid growth in research articles, reviews and citations related to“brain graphs” and “connectomes” [20–22]; by the publication of several textbooks [23, 24]; and by the recent launch of new specialist journals for network neuroscience [25].”
Cognitive Network Neuroscience (2015, background): “For example, intersections between macroscale brain models such as the Virtual Brain (Ritter, Schirner, McIntosh, & Jirsa, 2013) and mesoscale models such as for cortical columns (Chemla & Chavane, 2010) and microscale models examining self-organized criticality (Plenz, Niebur, & Schuster, 2014) cou”
Multi-scale brain networks (2016, neutral): “…of Pennsylvania, Philadelphia, PA, 19104 and 2Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104 (Dated: November 7, 2016) The network architecture of the human brain has become a feature of increasing interest to the neuroscientific…”
Network attributes for segregation and integration in the human brain. (2013, background): “Importantly, network science not only provides intuitive and analytically powerful approaches for data analysis and modeling, it also offers a comprehensive theoretical framework for understanding the biological basis of brain function [8].”