Cerebral white matter integrity mediates adult age differences in cognitive performance

Abstract

Previous research has established that age-related decline occurs in measures of cerebral white matter integrity, but the role of this decline in age-related cognitive changes is not clear. To conclude that white matter integrity has a mediating (causal) contribution, it is necessary to demonstrate that statistical control of the white matter-cognition relation reduces the magnitude of age-cognition relation. In this research, we tested the mediating role of white matter integrity, in the context of a task-switching paradigm involving word categorization. Participants were 20 healthy, community-dwelling older adults (60-85 years), and 20 younger adults (18-27 years). From diffusion tensor imaging tractography, we obtained fractional anisotropy (FA) as an index of white matter integrity in the genu and splenium of the corpus callosum and the superior longitudinal fasciculus (SLF). Mean FA values exhibited age-related decline consistent with a decrease in white matter integrity. From a model of reaction time distributions, we obtained independent estimates of the decisional and nondecisional (perceptual-motor) components of task performance. Age-related decline was evident in both components. Critically, age differences in task performance were mediated by FA in two regions: the central portion of the genu, and splenium-parietal fibers in the right hemisphere. This relation held only for the decisional component and was not evident in the nondecisional component. This result is the first demonstration that the integrity of specific white matter tracts is a mediator of age-related changes in cognitive performance.

Figure 1

Sequence of events on each trial. The cue display indicated the type of category decision (manmade/natural or larger/smaller than the computer monitor) to be made regarding the target word. Participants responded at the onset of target. Trials are defined as repeat or switch in relation to the cue on the immediately preceding trial. ITI = inter-trial interval.

Figure 2

Examples of fiber tracts (in red) generated by target and source region placement, for a single participant. The orange areas are target regions, the green areas are source regions, and the blue areas are exclusion regions. All of these regions are operator defined, for each participant, using anatomical boundaries. The fiber tracking algorithm estimates tracts that pass through the target regions from the source regions, eliminating any fibers terminating in the exclusion regions. The approximate locations of output fiber tracts are illustrated by overlaying on a single-slice T₁-weighted image. Panel A = genu; Panel B = splenium-occipital; Panel C = splenium-parietal; Panel D = superior longitudinal fasciculus.

Figure 3

Mean parameter estimates (Wagenmakers, van der Maas, & Grasman, 2007) of task switching performance, as a function of age group and repeat versus switch trials. Panel A = the drift rate parameter (v), representing the quality of decision processing; Panel B = the nondecision time parameter (T-er), representing perceptual encoding and response time.

Figure 4

Mean fractional anisotropy (FA) as a function of age group and interval along the tract. Error bars represent 1 SE. Panel A = genu and superior longitudinal fasciculus; Panel B = splenium-occipital and splenium-parietal. For genu and splenium, the tracts are oriented left-right, with 0 = axial midline. For the superior longitudinal fasciculus, the tracts are oriented anterior-posterior and 0 = central sulcus. Below the mean FA data, t-values are plotted for the age group comparison at each point along the tract. The dotted line represents the significant t(38) value for p < .05, two-tailed.

Figure 5

Diffusivity as a function of age group and region. Panel A = axial diffusivity (the first eigenvalue, λ₁); Panel B = radial diffusivity (the mean of the second and third eigenvalues, λ₂, and λ₃); Sp-Par = splenium-parietal; Sp-Occ = splenium-occipital; SLF = superior longitudinal fasciculus.

Figure 6

Attenuation of age-related variance in drift rate (decisional processing) by regional FA. The first three bars (from left to right) in the graph illustrate the variance in drift rate associated with age group, FA in the right-hemisphere splenium-parietal tract (Sp-Par R), and FA in the central genu (Genu-C), when each of these variables is used as the sole predictor of drift rate. The last two bars in the graph illustrate the attenuation of age-related variance when either the splenium or genu FA variables are entered before age group in the regression model. The substantial attenuation indicates that these variables are mediators of age differences in this aspect of task performance.