@article {DuPre090233, author = {Elizabeth DuPre and R. Nathan Spreng}, title = {Structural covariance networks across the lifespan, from 6-94 years of age}, elocation-id = {090233}, year = {2016}, doi = {10.1101/090233}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Structural covariance examines interindividual differences in the covariation of grey matter morphology between brain regions. Although structural covariance has been used to examine the development of brain networks in either adolescence or aging, no study to date has provided a lifespan perspective on the development of structural covariance networks, bridging childhood with early and late adulthood. Here, we investigate the lifespan trajectories of structural covariance in six canonical neurocognitive networks default, dorsal attention, frontoparietal control, somatomotor, ventral attention, and visual networks. By combining data from five open access data sources, we examine the structural covariance trajectories of these networks from 6-94 years of age in a sample of 1580 participants. Using partial least squares, we show that structural covariance patterns across the lifespan exhibit two significant, age-dependent trends. The first trend is a rapid decline that levels off in later life, suggestive of reduced within-network covariance. The second trend is an inverted-U that peaks in young adulthood, suggestive of the patterns of integration followed by de-differentiation as observed in functional brain networks. Hub regions, including posterior cingulate cortex and anterior insula, appear particularly influential in the expression of this second age-dependent trend. Overall, we suggest that these results provide evidence for the importance of a persistent pattern of functional coupling in the developmental trajectories of structural covariance networks.Research HighlightsWe examine structural covariance of six neurocognitive networks over the lifespan.The structural covariance of these networks exhibits reliable age-dependent trends.Hub regions significantly influence trajectories of structural covariance.Structural covariance appears to partially reflect a shared functional history.}, URL = {https://www.biorxiv.org/content/early/2016/11/29/090233}, eprint = {https://www.biorxiv.org/content/early/2016/11/29/090233.full.pdf}, journal = {bioRxiv} }