Age-related differences in functional brain network segregation are consistent with a cascade of cerebrovascular, structural, and cognitive effects

Abstract

Age-related declines in cognition are associated with widespread structural and functional brain changes, including changes in resting-state functional connectivity and gray and white matter status. Recently we have shown that the elasticity of cerebral arteries also explains some of the variance in cognitive and brain health in aging. Here, we investigated how network segregation, cerebral arterial elasticity (measured with pulse-DOT-the arterial pulse based on diffuse optical tomography) and gray and white matter status jointly account for age-related differences in cognitive performance. We hypothesized that at least some of the variance in brain and cognitive aging is linked to reduced cerebrovascular elasticity, leading to increased cortical atrophy and white matter abnormalities, which, in turn, are linked to reduced network segregation and decreases in cognitive performance. Pairwise comparisons between these variables are consistent with an exploratory hierarchical model linking them, especially when focusing on association network segregation (compared with segregation in sensorimotor networks). These findings suggest that preventing or slowing age-related changes in one or more of these factors may induce a neurophysiological cascade beneficial for preserving cognition in aging.

Keywords: Aging; Cerebrovascular health; Cortical thickness; Optical brain arterial pulse (pulse-DOT); Resting-state functional connectivity (rsFC); White matter signal abnormalities (WMSAs).

Figure 1.

Relationship between age and PReFx (A), cortical thickness (B), and WMSAs (C). Shading indicates the 95% bootstrap confidence interval for the linear regression function (solid line); **p < .01. PReFx = pulse relaxation function; WMSAs = White matter signal abnormalities.

Figure 2.

Mean functional connectivity matrices for younger (age range = 18–37 years, N = 16), middle-aged (age range = 39–57 years, N = 15), and older adults (age range = 58–75 years, N = 15). Color scale indicates the mean Fisher Z-transformed connectivity values. Aud = auditory network; CON = cingulo-opercular network; DAN = dorsal attention network; DMN = default mode network; FPN = fronto-parietal network; SN = salience network; VAN = ventral attention network; Vis = visual network; Memory = memory network; SMHand = sensorimotor hand network; SMMouth = sensorimotor mouth network.

Figure 3.

Relationship between age and association system segregation (A) and sensorimotor system segregation (B). Shading indicates the 95% bootstrap confidence interval for the linear regression function (solid line); **p < .01.

Figure 4.

Relationship between PReFx and association system segregation (A) and sensorimotor system segregation (B). Shading indicates the 95% bootstrap confidence interval for the linear regression function (solid line); **p < .01. PReFx, pulse relaxation function.

Figure 5.

Relationship between white matter signal abnormalities (WMSAs) and association system segregation (A) and sensorimotor system segregation (B). Shading indicates the 95% bootstrap confidence interval for the linear regression function (solid line); **p < .01. Note that these relationships remain significant (r = −0.477 and r = 0.414, respectively, p < .01 for both) when the two extreme values are excluded.

Figure 6.

Relationship between cortical thickness and association system segregation (A) and sensorimotor system segregation (B). Shading indicates the 95% bootstrap confidence interval for the linear regression function (solid line); *p < .05, **p < .01.

Figure 7.

Relationship between cortical thickness and WMSAs (A) and PReFx (B). Shading indicates the 95% bootstrap confidence interval for the linear regression function (solid line); *p < .05. PReFx = pulse relaxation function; WMSAs = white matter signal abnormalities.

Figure 8.

Schematic representation of an exploratory hierarchical cascade of effects. The sign next to each arrow indicates the direction of the relationship between pairwise variables (red minus sign = negative relationship; blue plus sign = positive relationship). The main hypothesized cascade of effects is indicated by the gray arrows. Pairwise relationships between the levels are indicated by the orange arrows. WMSAs = white matter signal abnormalities.

Figure 9.

Absolute values for the integrated pairwise correlations between levels in the exploratory hierarchical model presented in Figure 8. The green shading indicates the strength of the correlations, based on the scale presented on the right; **p < .01. PReFx = pulse relaxation function.