Measuring cognitive reserve based on the decomposition of episodic memory variance

Abstract

In later adulthood brain pathology becomes common and trajectories of cognitive change are heterogeneous. Among the multiple determinants of late-life cognitive course, cognitive reserve has been proposed as an important factor that modifies or buffers the impact of brain pathology on cognitive function. This article presents and investigates a novel method for measuring and investigating such factors. The core concept is that in a population where pathology is common and variably present, 'reserve' may be defined as the difference between the cognitive performance predicted by an individual's level of pathology and that individual's actual performance. By this definition, people whose measured cognitive performance is better than predicted by pathology have high reserve, whereas those who perform worse than predicted have low reserve. To test this hypothesis, we applied a latent variable model to data from a diverse ageing cohort and decomposed the variance in a measure of episodic memory into three components, one predicted by demographics, one predicted by pathology as measured by structural MRI and a 'residual' or 'reserve' term that included all remaining variance. To investigate the plausibility of this approach, we then tested the residual component as an operational measure of reserve. Specific predictions about the effects of this putative reserve measure were generated from a general conceptual model of reserve. Each was borne from the results. The results show that the current level of reserve, as measured by this decomposition approach, modifies rates of conversion from mild cognitive impairment to dementia, modifies rates of longitudinal decline in executive function and, most importantly, attenuates the effect of brain atrophy on cognitive decline such that atrophy is more strongly associated with cognitive decline in subjects with low reserve than in those with high reserve. Decomposing the variance in cognitive function scores offers a promising new approach to the measure and study of cognitive reserve.

Figure 1

Analytic model for decomposing episodic memory into independent components and relating these components to external variables. Rectangles represent observed variables and ovals represent latent variables. Observed demographic and MRI variables were allowed to correlate freely (paths not shown). Freely estimated parameters are indicated by ‘asterisk’. S² refers to sample variance. c1 and c2 are scaling constants selected to set variances at 1.0 for the MemB and MemD latent variables.

Figure 2

Relationship of baseline Mem-B to longitudinal change in executive function as a function of different levels of Mem-R. Mem-B scores reflect brain status as measured by structural MRI measures of brain matter, hippocampal volume and white matter hyperintensity. Positive Mem-R scores indicate that episodic memory performance was better than expected on the basis of demographic and MRI variables (high reserve), negative scores indicate worse than expected performance (low reserve). Mem-B was a stronger determinant of executive function change in individuals with lower Mem-R.

Figure 3

Relationship of baseline Sem-B to longitudinal change in executive function as a function of different levels of Sem-R. Sem-B scores reflect brain status as measured by structural MRI measures of brain matter, hippocampal volume and white matter hyperintensity. Positive Sem-R scores indicate that semantic memory performance was better than expected on the basis of demographic and MRI variables (high reserve), negative scores indicate worse than expected performance (low reserve). Sem-B was a stronger determinant of executive function change in individuals with lower Sem-R.