Cognitive reserve

Abstract

The concept of reserve has been proposed to account for the disjunction between the degree of brain damage and its clinical outcome. This paper attempts to produce a coherent theoretical account the reserve in general and of cognitive reserve in particular. It reviews epidemiologic data supporting the concept of cognitive reserve, with a particular focus of its implications for aging and dementia. It then focuses on methodologic issues that are important when attempting to elucidate the neural underpinnings of cognitive reserve using imaging studies, and reviews some of our group's work in order to demonstrate these issues.

Figures

Figure 1

Theoretical illustration of how cognitive reserve may mediate between AD pathology and its clinical expression. We assume that AD pathology slowly increases over time, and this is graphed on the x-axis. The y-axis represents cognitive function, in this case memory performance. Assuming that AD pathology increases over time at the same rate in two individuals with high and low reserve, the following predictions can be made about the individual with high CR: 1) the point of inflection, where memory begins to be affected AD pathology will be later; 2) clinical diagnostic criteria for AD be reached later, when pathology is more severe; 3) at any level of memory performance, AD pathology will be more severe; 4) after the point of inflection, clinical progression will be more rapid.

Figure 2

A scheme for exploring and comparing task related activation and young and old with the goal of understanding cognitive reserve. The same approach would apply to any condition that could potentially disrupt brain function. Each step in this scheme is discussed in the text.

Figure 3

Hypothetical relationship between task demand and activation in old and young. On the X axis is increasing task demand, referring to a within-subject manipulation where the difficulty of the task is increased in a parametric manner. The Y axis represents task-related activation either at one particular brain location or throughout some brain network. The figure demonstrates hypothesized curves relating task demand to task-related activation in young and old individuals. The rate of rise in the curve is an index of the efficiency of the system. The asymptote of the curves could indicate the capacity of the system. Note in the illustration that at relatively low task demand, greater activation might be seen in old people than in young people. Conversely, at greater task demand, greater activation might be seen in the young subjects than in the old.

Figure 4

Example of two groups expressing the same pattern of activation across three voxels (or brain areas) but to different degrees. When comparing thresholded maps between groups, as in standard voxel-wise GLM analyses, one would not appreciate the fact that both groups express the same pattern of activation. Further, one might incorrectly conclude activation of voxel 3 is unique to group A. Specific covariance analyses such as MLM and OrT CVA are designed to identify patterns such as these and compare their expression across groups.