Cerebral blood flow and gray matter volume covariance patterns of cognition in aging

Abstract

Advancing age results in altered cognitive and neuroimaging-derived markers of neural integrity. Whether cognitive changes are the result of variations in brain measures remains unclear and relating the two across the lifespan poses a unique set of problems. It must be determined whether statistical associations between cognitive and brain measures truly exist and are not epiphenomenal due solely to their shared relationships with age. The purpose of this study was to determine whether cerebral blood flow (CBF) and gray matter volume (GMV) measures make unique and better predictions of cognition than age alone. Multivariate analyses identified brain-wide covariance patterns from 35 healthy young and 23 healthy older adults using MRI-derived measures of CBF and GMV related to three cognitive composite scores (i.e., memory, fluid ability, and speed/attention). These brain-cognitive relationships were consistent across the age range, and not the result of epiphenomenal associations with age and each imaging modality provided its own unique information. The CBF and GMV patterns each accounted for unique aspects of cognition and accounted for nearly all the age-related variance in the cognitive composite scores. The findings suggest that measures derived from multiple imaging modalities explain larger amounts of variance in cognition providing a more complete understanding of the aging brain.

Structure and function of the aging brain

“…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]. This last observation speaks to the importance of measuring not simply independent trajectories of regional changes, but covariance patterns describing how volume changes in distributed brain regions cohere across the across the lifespan.…”

Imaging structural co-variance between human brain regions

“…Initial analyses revealed particular patterns of correlated atrophy (‘components’) that were subsequently also found in other samples 123,126 — an example of successful experimental replication of brain imaging findings. The functional significance of age-related changes in structural co-variance networks is supported by their links with neuropsychological performance, as the strength of these brain-wide co-variance patterns is correlated with individuals’ scores on memory, attention and cognitive tests 123,127 (even in healthy young subjects 127 ).…”

Individual differences in regional cortical volumes across the life span are associated with regional optical measures of arterial elasticity

“…Previous research has also shown a link between local cortical atrophy and specific changes in cognitive outcomes (Aguilar et al, 2014; Draganski et al, 2013; Hedden & Gabrieli, 2004; Hedden et al, 2014; Kaup et al, 2011; Raz et al, 1998; Raz & Rodrigue, 2006; Rodrigue & Raz, 2004; Salthouse, 2011). This indicates the need for future studies investigating whether the regional associations between cortical atrophy and arterial stiffness may, in turn, lead to declines in the specific cognitive domains supported by the affected regions (see also Steffener et al, 2013; Zimmerman et al, 2014, for similar approaches).…”