The economy of brain network organization

By E. Bullmore, Olaf Sporns. Nature Reviews Neuroscience, 2012

3,178 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/4cb0081a80c556bf14d707416adfcb4841c173f6

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In Cognitive Neuroscience

In Experimental and Cognitive Psychology

Citations in the corpus

Networks of anatomical covariance (2013, background): “We need to better understand the impact of regional segmentation (Tohka et al., 2012; Zalesky et al., 2010) and connectivity weighting (Bullmore and Sporns, 2012) on the derived network metrics.”
Structural connectomics in brain diseases (2013, positive): “This structure is thought to reflect neurodevelopmental exigencies of wiring cost minimization, and network topological features optimization (Bullmore and Sporns, 2012).”
The minimum spanning tree: An unbiased method for brain network analysis (2015, positive): “Brain network studies are typically based on neuroimaging data (such as functional MRI (fMRI), similarity in cortical structure or Diffusion Tensor Imaging) or neurophysiological recordings (such as electroencephalography (EEG), magnetoencephalography (MEG), or corticography) (Bullmore and Sporns, 2”
Effects of temporal correlations in social multiplex networks (2016, neutral): “…and measure temporal correlations in other fields of complexity invested by the multiplex representation, ranging from the multilayer organization of brain networks 34 to multimodal mobility and efficient transportation 35, 36 , as well as to their extension to more general multilayer networks.”
The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance (2015, positive): “9; p = 10 (11); Sporns and Betzel, 2016), whereas those associated with the integrated states had greater global efficiency (ES = 0.18 ± 0.03 versus EI = 0.24 ± 0.05; d = 1.5; p = 10 (8); Bullmore and Sporns, 2012).”
Network attributes for segregation and integration in the human brain. (2013, background): “The analysis also suggests that these significant functional benefits come at a cost to the brain’s economy [64].”
Structural and Functional Brain Networks: From Connections to Cognition (2013, neutral): “and the computational imperatives above (15).”
Contributions and challenges for network models in cognitive neuroscience (2014, background): “…occurrence of smallworld architectures in complex systems 43 has led to important findings in brain networks regarding the tradeoff between an abundance of highly clustered (short distance) connections and specific (longdistance) ‘shortcuts’ that enable efficient communication 44,45 .”
Cognitive Network Neuroscience (2015, background): “For example, the intrinsic functional connectivity involves predominantly short and by extension potentially efficient (Bullmore & Sporns, 2012) functional wiring, which is lengthened to perform simple motor tasks such as finger tapping (Bassett et al., 2006).”
EEG Based Emotion Recognition: A Tutorial and Review (2022, background): “High-level cognition function depends on subtle cooperation between local and global brain activities and is inseparable from a network of brain neurons and brain regions [99].”
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).”
Cognitive relevance of the community structure of the human brain functional coactivation network (2013, background): “This is also compatible with an economical interpretation: integrative network features, such as long-range connections, incur a premium in terms of connection cost, emerging only under conditions where they can add value behaviorally in response to a cognitively challenging environment (10, 40).”
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].”
Reconfigurable task-dependent functional coupling modes cluster around a core functional architecture (2014, background): “These empirical observations underscore the point that intrinsic fluctuations and changes in connectivity are functionally relevant [43–52].”
Morphometric Similarity Networks Detect Microscale Cortical Organisation And Predict Inter-Individual Cognitive Variation (2017, neutral): “Some topological features, such as clusters and modules, will favour segregated processing of specific channels of information, whereas other features, such as hubs and a rich club, will favour integrated processing of all information (Bullmore and Sporns, 2012; Sporns et al., 2004).”