Efficiency and Cost of Economical Brain Functional Networks

By Sophie Achard, E. Bullmore. PLoS Comput. Biol., 2007

2,510 citations recorded by the source corpus.

Brain anatomical networks are sparse, complex, and have economical small-world properties. We investigated the efficiency and cost of human brain functional networks measured using functional magnetic resonance imaging (fMRI) in a factorial design: two groups of healthy old (N = 11; mean age = 66.5 years) and healthy young (N = 15; mean age = 24.7 years) volunteers were each scanned twice in a no-task or “resting” state following placebo or a single dose of a dopamine receptor antagonist (sulpiride 400 mg). Functional connectivity between 90 cortical and subcortical regions was estimated by wavelet correlation analysis, in the frequency interval 0.06–0.11 Hz, and thresholded to construct undirected graphs. These brain functional networks were small-world and economical in the sense of providing high global and local efficiency of parallel information processing for low connection cost. Efficiency was reduced disproportionately to cost in older people, and the detrimental effects of age on efficiency were localised to frontal and temporal cortical and subcortical regions. Dopamine antagonism also impaired global and local efficiency of the network, but this effect was differentially localised and did not interact with the effect of age. Brain functional networks have economical small-world properties—supporting efficient parallel information transfer at relatively low cost—which are differently impaired by normal aging and pharmacological blockade of dopamine transmission.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/b55dfb180030e51e280c5660e7351bbaee7d2d19

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In Cognitive Neuroscience

Citations in the corpus

Graph-Based Network Analysis of Resting-State Functional MRI (2010, positive): “…number of studies to probe potential mechanisms involved in normal development (Fair et al., 2007, 2008, 2009; Supekar et al., 2009), aging (Achard and Bullmore, 2007; Gong et al., 2009b; Meunier et al., 2009a; Micheloyannis et al., 2009; Wang et al., 2010), and various brain disorders…”
Complex network measures of brain connectivity: Uses and interpretations (2010, background): “Some authors have argued that this may make the global ef ﬁ ciency a superior measure of integration (Achard and Bullmore, 2007).”
Graph theoretical analysis of structural and functional connectivity MRI in normal and pathological brain networks (2010, methodology): “Both partition methods led to networks with small-world properties and truncated power-law degree distribution as demonstrated in other studies using atlas-based parcellation [32,58,59].”
A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks (2011, background): “Moreover, small-world property seems to be relevant for brain function because it is affected by disease (17), normal aging, and by pharmacological blockade of dopamine neurotransmission (13).”
Reduced resting-state brain activity in the "default network" in normal aging. (2008, background): “Even though the concept of ‘‘network efficiency’’ used by Achard (Achard and Bullmore 2007) is quite complex, and translating it to the analysis of the present study is not trivial, these results suggest that it would be more likely to find reduced activity rather than increased activity in these ad”
Disrupted Modularity and Local Connectivity of Brain Functional Networks in Childhood-Onset Schizophrenia (2010, positive): “where L i,j is the minimum path length, or the minimum number of edges that must be traversed between regions i and j (Latora and Marchiori, 2001; Achard and Bullmore, 2007).”
Hemisphere- and gender-related differences in small-world brain networks: A resting-state functional MRI study (2011, background): “The nodal efficiency of a node i is defined as (Achard and Bullmore, 2007): Enod ið Þ = 1 N−1 ∑j≠i∈G 1 Lij : ð6Þ Fig.”
The resting brain: unconstrained yet reliable. (2009, background): “2008), and form key components of regulatory systems in human brain (Dosenbach et al. 2006; Achard and Bullmore 2007; Fair et al. 2007; Sridharan et al. 2008).”
Focal Brain Lesions to Critical Locations Cause Widespread Disruption of the Modular Organization of the Brain (2012, neutral): “1276 Journal of Cognitive Neuroscience Volume 24, Number 6 D ow nloaded from http://direct.m it.edu/jocn/article-pdf/24/6/1275/1777991/jocn_a_00222.pdf by guest on 07 June 2021”
Efficiency of Functional Brain Networks and Intellectual Performance (2009, result): “These results clearly suggest a small-world organization of the functional human brain, supporting the findings of recent studies showing a small-world organization of the brain network on both a regional (Sporns and Zwi, 2004; Stam, 2004; Achard et al., 2006; Achard and Bullmore, 2007; Sporns et al”
Cognitive Neuroscience of Aging (2008, background): “Recently, Achard and Bullmore (2007) examined the efficiency of human brain functional networks in young and older adults scanned in a resting state.”
Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory (2010, background): “Also, changes in small-worldness have been found at slow and fast time scales alike, e.g., as effect of aging [31–33], in different sleep stages [34,35], and during epileptic seizures [36–38].”
Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory (2008, neutral): “These results are in accordance with those obtained for brain functional networks corresponding to the same gray matter parcellation scheme (Achard and Bullmore, 2007).”
Cognitive Network Neuroscience (2015, background): “In the brain, this network efficiency is often interpreted to underlie efficiency of information processing (Sporns, 2010; Achard & Bullmore, 2007).”
Graph theoretical analysis of complex networks in the brain (2007, methodology): “A different approach was taken by the Cambridge group who studied fMRI BOLD time series during a 'resting state' with eyes-closed and no task [95,107-109].”