Abstract
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.
Highlights
Small-World Brain Networks Complex networks, from ecosystems to metabolic pathways, occur in diverse fields of biological science [1,2]
It is increasingly evident that many complex networks, in diverse fields and over a wide range of spatial and time scales, may have topological properties in common
These unifying organizational principles have been described in terms of ‘‘small-world’’ parameters—meaning that many networks have both local clustering of connections and a short path length between any pair of nodes
Summary
Small-World Brain Networks Complex networks, from ecosystems to metabolic pathways, occur in diverse fields of biological science [1,2]. Brain networks have characteristically small-world properties of dense or clustered local connectivity with relatively few long-range connections mediating a short path length between any pair of neurons or regions in the network [5,6,7]. Small-world topology is an attractive model for brain network organization because it could support both segregated and distributed information processing [8], confer resilience against pathological attack [9], and minimise wiring costs [10]. It can be argued that small-world brain networks have been competitively selected to solve the economic problem of maximising information processing efficiency while minimising costs [6,7,11]
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