Cognitive reserve and compensation

Proposal details

Title: Cognitive reserve and compensation in aging and dementia
Research Area(s): Development and Aging
Background: The underlying biology of late onset dementia is complex. It appears to be due to a broad range of pathologies in the brain, neurodegenerative and vascular. However, pathological burden and clinical dementia severity correspond poorly. Population-based samples have shown that some individuals can cope with a large burden of pathology before expressing clinical dementia, while others express the syndrome with relatively little pathology. Cognitive Reserve has been conceptualised to explain this finding. Those with high cognitive reserve are able to cope with damage to the brain better than those with low reserve. Factors that compose Cognitive Reserve have emerged from the epidemiological field, where early life intelligence and education, along with midlife occupation and late-life social interaction appear to modify the age of dementia onset. For example, those with high education (i.e. primary and secondary school, along with any tertiary education) develop dementia later than those with low education. Until recently, there was little evidence in relation to why Cognitive Reserve factors such as education are related to a delayed or hastened age of dementia onset. There were two completing theories: (1) ‘neuroprotection’ whereby those with high education (for example) had less pathologies in the brain and (2), ‘compensation’ whereby those with high education could compensate for pathological burden which was equivalent to those with low education. Last year, I (Keage) along with colleagues, investigated these two possibilities using the largest epidemiological autopsy sample (n=872) of dementia. Findings supported of the former hypothesis, that of compensation (EClipSE, 2010, Brain): there were no differences in the quantity of neurodegenerative and vascular pathology between those with high and low education, but those with high education were better able to cognitively cope with the presence of pathology. This article represented a major step in the understanding of Cognitive Reserve and the variability in pathological burden in those with dementia. It highlighted our lack of understanding about the psychophysiological correlates of compensatory ability. There are two major functional brain hypotheses to explain compensation: Hemispheric Asymmetry Reduction in Older Adults (HAROLD) and the Compensation-Related Utilisation of Neural Circuits Hypothesis (CRUNCH). They overlap considerably. The HAROLD model, proposes that under similar circumstances, brain activity during cognitive performances tends to be less lateralised in older adults than in younger adults, compensating for age-related neurocognitive decline. During a source memory task (memory of context in which an item is learned), younger adults and low-performing older adults showed right pre-frontal cortex (PFC) activity, whereas high-performing older adults showed bilateral PFC activity. These results suggest that low-performing older adults recruited a similar network as young adults but used it inefficiently, whereas high-performing older adults counteracted age-related neural decline through a reorganisation of networks underlying cognition. The CRUNCH model is very similar but instead of emphasising the bilateral nature of over-activation, stresses that compensation relies on general over-activation analogous to the brain “working harder”. Both the HAROLD and CRUNCH models have fed into theories of aging and cognitive decline such as the Scaffolding Theory of Aging and Cognition by Park and Reuter-Lorenz.
Aims: 1. Characterise cogntive compensation using ERP measures. 2. Investigate the amplitude and laterality of ERP components relative to performance and participant group (AD, MCI, control). 3. Investigate how relationships between performance and ERP measures change with the addition of education (index of Cognitive Reserve) and APOE genotype (major genetic determinant of dementia) into statistical models.
Method: Individuals 65 years and over with Alzheimer’s disorder, Mild Cognitive Impairment and age- and sex-matched controls. Would like advice on which ERP tasks are scored where components are lateralised.