The impact of aging on gray matter structural covariance networks

Bayesian exponential random graph modeling of whole-brain structural networks across lifespan

“…local clustering and global efficiency) over all age categories, in contrast with previous literature showing alterations in both structural (Dennis et al, 2013;Gong et al, 2009;Hagmann et al, 2010;Montembeault et al, 2012;Otte et al, 2015;Wu et al, 2012;Zhu et al, 2012) and functional brain networks across life-span (Achard and Bullmore, 2007;Betzel et al, 2014;Meier et al, 2012;Meunier et al, 2009;Nathan Spreng and Schacter, 2012;Simpson and Laurienti, 2015;Smit et al, 2016;Wang et al, 2012). Furthermore, our findings are also in contrast with significant differences found in a previous exponential random graph modeling study in functional networks , and a recently developed similar approach (also discussed below) which revealed differences in functional networks across the lifespan, such as older adults having stronger connections between highly clustered nodes, or less assortativity in visual and multisensory regions (Simpson and Laurienti, 2015).…”

“…the average shortest path length, maximum betweenness centrality or overall clustering coefficient) (Bullmore and Sporns, 2009) and/or network properties such as small-worldness, rich club connectedness (Bullmore and Sporns, 2012;Cao et al, 2014) and modularity (Rubinov and Sporns, 2010). In the past decade, multiple studies have shown that normal aging is associated with substantial alterations in NeuroImage 135 (2016) [79][80][81][82][83][84][85][86][87][88][89][90][91] structural Dennis et al, 2013;Gong et al, 2009;Hagmann et al, 2010;Lim et al, 2015;Montembeault et al, 2012;Otte et al, 2015;Wu et al, 2012;Zhu et al, 2012) and functional (Achard and Bullmore, 2007;Andrews-Hanna et al, 2007;Betzel et al, 2014;Meier et al, 2012;Meunier et al, 2009;Nathan Spreng and Schacter, 2012;Wang et al, 2012) brain networks. Some of these studies focused on specific age categories: childhood to adulthood (Dennis et al, 2013;Hagmann et al, 2010) or young and older adults (e.g.…”

Structure and function of the aging brain

“…Further, we observed that changes in default network structural covariance reliably predicted the transition from mild cognitive impairment to Alzheimer's disease in a longitudinal sample [62]. Similar patterns of declining structural covariance have been reported in other large-scale distributed brain networks, including executive control networks, which have been implicated in those cognitive functions most susceptible to aging [61]. Indeed, measures of structural covariance, when combined with estimates of cerebral blood flow, explained almost all age-related variance in cognitive performance in a recent report [67].…”

“…Across individuals, intrinsically connected functional brain networks, such as the default network, can be topographically represented in the structural patterns of cortical gray matter. Patterns of covariance in brain structure were first identified in post-mortem studies [55], and changes in structural covariance networks with age have now been reported in whole-brain in vivo studies [56][57][58][59][60][61][62][63].…”

“…As with global and regional measures of structural brain changes, structural covariance changes with age are more prominent between frontal brain and posterior cortices, reflecting a loss of long-range covariance in favor of increased local processing [61,63,64]. Another prominent feature of network-level changes is declining structural covariance within the default network, a collection of functionally-connected brain regions implicated in mnemonic and associative processing [65].…”