A task-invariant cognitive reserve network

Abstract

The concept of cognitive reserve (CR) can explain individual differences in susceptibility to cognitive or functional impairment in the presence of age or disease-related brain changes. Epidemiologic evidence indicates that CR helps maintain performance in the face of pathology across multiple cognitive domains. We therefore tried to identify a single, "task-invariant" CR network that is active during the performance of many disparate tasks. In imaging data acquired from 255 individuals age 20-80 while performing 12 different cognitive tasks, we used an iterative approach to derive a multivariate network that was expressed during the performance of all tasks, and whose degree of expression correlated with IQ, a proxy for CR. When applied to held out data or forward applied to fMRI data from an entirely different activation task, network expression correlated with IQ. Expression of the CR pattern accounted for additional variance in fluid reasoning performance over and above the influence of cortical thickness, and also moderated between cortical thickness and reasoning performance, consistent with the behavior of a CR network. The identification of a task-invariant CR network supports the idea that life experiences may result in brain processing differences that might provide reserve against age- or disease-related changes across multiple tasks.

Keywords: Cognitive aging; Cortical thickness; IQ; Multivariate imaging analysis; fMRI.

Fig. 1.

Topographic composition of the task-invariant CR pattern. Bootstrap loadings indicating statistically robust participant voxels in the covariance pattern ∣Z∣>2 with cluster size >49 voxels). Red voxels indicate positive correlation between task-activation and NART IQ, while blue voxels indicate covarying negative correlation. Numbers correspond to cluster numbers in Table 2.

Fig. 2.

Replication success in the dual ECF task, which is separate from the RANN data set. NART IQ was predicted from the pattern score and age. Both also contributed independently: for age we obtained T = −2.79, p = 0.0059, and for the pattern score we obtained T = 3.7921, p = 0.0002.

Fig. 3.

Moderation of the relationship between a cortical thickness covariance pattern and fluid reasoning performance by expression of the task invariant CR pattern. The ROIs contributing significantly to the cortical thickness covariance pattern are illustrated on the right, and the moderation is illustrated on the left. After dichotomizing expression of the CR pattern score around its median into high and low pattern expression, one can discern a negative difference in slope: participants with low pattern scores (black circles) show a steeper slope in the relationship of thickness and fluid reasoning (black line), while participants with high pattern scores (red circles) show a flatter slope (red line). The scatter plot in the figure shows raw data, not partial model predictions. The colors in the thickness pattern are arbitrary, to illustrate the different regions.