The organisation of the elderly connectome
Graphical abstract
We apply present the first systematic investigation of the topological structure of the healthy elderly connectome, applying graph theoretical measures to probabilistic tractography. These technique highlight the clustering of intra-and-inter-module connections (community structure indexed by circles and line colours) identified in the elderly connectome (left hand panel). The elderly connectome is organised around a small constellation of core hub nodes (upper right panel). Network communicability is most sensitive to simulated lesions of hub connections (red connections), suggesting that a pivotal role of hubs persists with healthy ageing.
Introduction
The human brain is a large-scale complex network known as the human “connectome” (Sporns et al., 2005). The application of graph theoretical analysis to human neuroimaging data has uncovered topological features of the connectome that mirror other complex systems (Fornito et al., 2013, Sporns, 2013). These network features include “small-worldness” (Achard et al., 2006, Sporns and Zwi, 2004, Stephan et al., 2000), highly-connected “hubs” (Hagmann et al., 2008, van den Heuvel and Sporns, 2011, van den Heuvel and Sporns, 2013b), and a modular structure (Hagmann et al., 2008, Meunier et al., 2009). Knowledge of the connectome has accelerated through recent advances in diffusion-weighted imaging, including optimal acquisition parameters (Sotiropoulos et al., 2013, Tournier et al., 2013), improved reconstruction algorithms (Behrens et al., 2003, Tournier et al., 2010), and diffusion models (Aganj et al., 2011, Behrens et al., 2007, Jbabdi et al., 2012, Tournier et al., 2008).
A crucial architectural feature of the adult human connectome is the presence of highly-connected regions (“hubs”), that are also densely connected with each other (van den Heuvel and Sporns, 2013b). These regions form what is known as a “rich-club”, and occur in cortical regions such as the precuneus, cingulum (anterior and posterior), insula, superior frontal and parietal areas, temporal regions, and also subcortical structures (van den Heuvel and Sporns, 2011, van den Heuvel and Sporns, 2013b). Rich-club connections in human (Collin et al., 2014, van den Heuvel et al., 2012), macaque (Harriger et al., 2012) and cat cortices (de Reus and van den Heuvel, 2013) have high topological efficiency, longer anatomical fibres, increased inter-modular connectivity and route a large proportion of network traffic. The structural rich-club may thus act as a central backbone that integrates communication between segregated brain regions (van den Heuvel and Sporns, 2013b). This is exemplified by the disproportionate reduction in network “communicability” and/or “efficiency” when hub-regions or their connections are artificially lesioned (Crossley et al., 2013, de Reus et al., 2014, van den Heuvel and Sporns, 2011).
These hub-regions overlap with transmodal areas known to be pivotal within-and-between core neurocognitive systems such as the cognitive control, default mode, and salience network (Crossley et al., 2013, Dwyer et al., 2014, Sepulcre et al., 2012, Spreng et al., 2013, Tomasi and Volkow, 2011, Uddin et al., 2011, van den Heuvel and Sporns, 2013a). Interestingly, alterations in functional connectivity of these large-scale systems in elderly populations have been associated with changes in working memory, processing speed and executive functions (Campbell et al., 2012, Damoiseaux et al., 2008, He et al., 2014, Lim et al., 2014, Wang et al., 2010). These disruptions are thus suggestive of topological changes occurring to hub connections with ageing. Hub-regions are also metabolically costly, evident through their increased metabolic expenditure and wiring cost (Collin et al., 2014, Liang et al., 2013, van den Heuvel et al., 2012). This increased energy expenditure of hub-regions further highlights their potential for age-related changes, as their high metabolic cost has been shown to potentially render such regions more vulnerable to pathological processes in neurodegenerative disorders (Crossley et al., 2014, Liang et al., 2013, Tomasi et al., 2013). Indeed, hub-regions have shown to be more likely susceptible to normal ageing processes such as amyloid deposition (Buckner et al., 2009, Toga and Thompson, 2014).
During cognitively demanding tasks, older adults increase their recruitment of contralateral brain regions, suggesting compensatory mechanisms (Cabeza et al., 2002, Davis et al., 2012, Park and Reuter-Lorenz, 2009). Left-hemisphere networks are well known to be dominant in language tasks, whilst the right-hemisphere is associated with visuospatial abilities (Geschwind and Galaburda, 1985, Herve et al., 2013, Toga and Thompson, 2003). Although connectomic investigations (Caeyenberghs and Leemans, 2014, Nielsen et al., 2013, Tomasi and Volkow, 2012b) have examined lateralized organisation at the nodal-level, no study has specifically investigated lateralization of the elderly connectome.
Sexual dimorphism has also been an active area of research for the last few decades, with increasing interest from connectomic investigations (Dennis et al., 2013, Duarte-Carvajalino et al., 2012, Gong et al., 2009, Ryman et al., 2014). Across the lifespan, males have been shown to demonstrate greater performance in visuospatial tasks, whilst females excel on verbal tasks (Gur et al., 2012, Hoogendam et al., 2014, Kimura, 2004). Preferential wiring for inter-hemispheric structural connections was recently observed in female adolescents, whilst localised intra-hemispheric connectivity characterises cortical networks in young men (Ingalhalikar et al., 2014). Whether such topological differences persist into late adulthood is not known.
Hitherto, the structural connectomes of healthy elderly populations have been investigated through lifespan longitudinal studies (Betzel et al., 2014, Caeyenberghs and Leemans, 2014, Gong et al., 2009). Whilst these incorporate sufficiently large numbers of subjects across the life span, the number of elderly subjects is invariably modest. The organisation of healthy older connectomes hence remains relatively unknown and has not benefitted from recent advances in the acquisition and analysis of structural connectomes. The present study addresses this gap by characterising network topology in elderly structural connectomes generated from high-angular resolution fibre bundles. For comparative purposes, structural networks of a young adult population (17–30 years old) are also investigated.
Section snippets
Participants
143 cognitively healthy elderly individuals were drawn from the Sydney Memory and Ageing Study (Tsang et al., 2013). The longitudinal study involves community-dwelling older adults aged 76–94 years, randomly recruited from the electoral roll. Participants in the present study were cognitively healthy, defined as performance on all neuropsychological test measures were not below 1.5 standard deviations of normative published mean values (Tsang et al., 2013). Individuals not meeting these
Identification of hub-regions and rich-club architecture
Brain regions identified as hubs, by virtue of having consistently high composite scores across subjects are illustrated in Fig. 2. These hubs (for index of surface colours see Fig. 2c) are distributed bilaterally in subcortical structures (Fig. 2b), and cortical (Fig. 2a) regions including the insula, anterior cingulate (AC), precentral gyrus, precuneus, superior frontal, supplementary motor area (SMA), temporal poles, occipital areas, and also the left inferior frontal gyrus (IFG).
Discussion
We sought to elucidate key features of the healthy elderly connectome, leveraging recent advances in the acquisition and analysis of brain network connectivity. We found the topology and architectural features of hub-regions to be consistent with connectomic data from a young healthy adult cohort, and also with prior research in young adults (van den Heuvel and Sporns, 2011, van den Heuvel and Sporns, 2013b). We also report the presence of strongly lateralized subnetworks, and focal sexual
Conclusion
In sum, our study is the first systematic investigation of network organisation in the elderly connectome. Notwithstanding the methodological caveats highlighted above, we provide preliminary evidence that the topology and architectural features of hub-regions are preserved into the healthy elderly. Moreover, our findings provide a benchmark for future longitudinal and clinical investigations, arguing that elucidating the topology and cost of hub regions may be key to connectomic changes. In
Acknowledgments
This work was supported by the National Health and Medical Research Council Program (350833), and MB acknowledges support of the Australian Research Council (CIBF).
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