Cortisol, cognition and the ageing prefrontal cortex

The structural and functional decline of the ageing human brain varies by brain region, cognitive function and individual. The underlying biological mechanisms are poorly understood. One potentially important mechanism is exposure to glucocorticoids (GCs; cortisol in humans); GC production is increasingly varied with age in humans, and chronic exposure to high levels is hypothesised to result in cognitive decline via cerebral remodelling. However, studies of GC exposure in humans are scarce and methodological differences confound cross-study comparison. Furthermore, there has been little focus on the effects of GCs on the frontal lobes and key white matter tracts in the ageing brain. This thesis therefore examines relationships among cortisol levels, structural brain measures and cognitive performance in 90 healthy, elderly community-dwelling males from the Lothian Birth Cohort 1936. Salivary cortisol samples characterised diurnal (morning and evening) and reactive profiles (before and after a cognitive test battery). Structural variables comprised Diffusion Tensor Imaging measures of major brain tracts and a novel manual parcellation method for the frontal lobes. The latter was based on a systematic review of current manual methods in the context of putative function and cytoarchitecture. Manual frontal lobe brain parcellation conferred greater spatial and volumetric accuracy when compared to both single- and multi-atlas parcellation at the lobar level. Cognitive ability was assessed via tests of general cognitive ability, and neuropsychological tests thought to show differential sensitivity to the integrity of frontal lobe sub-regions. The majority of, but not all frontal lobe test scores shared considerable overlap with general cognitive ability, and cognitive scores correlated most consistently with the volumes of the anterior cingulate. This is discussed in light of the diverse connective profile of the cingulate and a need to integrate information over more diffuse cognitive networks according to proposed de-differentiation or compensation in ageing. Individuals with higher morning, evening or pre-test cortisol levels showed consistently negative relationships with specific regional volumes and tract integrity. Participants whose cortisol levels increased between the start and end of cognitive testing showed selectively larger regional volumes and lower tract diffusivity (correlation magnitudes <.44). The significant relationships between cortisol levels and cognition indicated that flatter diurnal slopes or higher pre-test levels related to poorer test performance. In contrast, higher levels in the morning generally correlated with better scores (correlation magnitudes <.25). Interpretation of all findings was moderated by sensitivity to type I error, given the large number of comparisons conducted. Though there were limited candidates for mediation analysis, cortisol-function relationships were partially mediated by tract integrity (but not sub-regional frontal volumes) for memory and post-error slowing. This thesis offers a novel perspective on the complex interplay among glucocorticoids, cognition and the structure of the ageing brain. The findings suggest some role for cortisol exposure in determining age-related decline in complex cognition, mediated via brain structure

Automated template-based hippocampal segmentations from MRI: the effects of 1.5T or 3T field strength on accuracy.

Hippocampal volumetric measures may be useful for Alzheimer's disease (AD) diagnosis and disease tracking; however, manual segmentation of the hippocampus is labour-intensive. Therefore, automated techniques are necessary for large studies and to make hippocampal measures feasible for clinical use. As large studies and clinical centres are moving from using 1.5 Tesla (T) scanners to higher field strengths it is important to assess whether specific image processing techniques can be used at these field strengths. This study investigated whether an automated hippocampal segmentation technique (HMAPS: hippocampal multi-atlas propagation and segmentation) and volume change measures (BSI: boundary shift integral) were as accurate at 3T as at 1.5T. Eighteen Alzheimer's disease patients and 18 controls with 1.5T and 3T scans at baseline and 12-month follow-up were used from the Alzheimer's Disease Neuroimaging Initiative cohort. Baseline scans were segmented manually and using HMAPS and their similarity was measured by the Jaccard index. BSIs were calculated for serial image pairs. We calculated pair-wise differences between manual and HMAPS rates at 1.5T and 3T and compared the SD of these differences at each field strength. The difference in mean Jaccards (manual and HMAPS) between 1.5T and 3T was small with narrow confidence intervals (CIs) and did not appear to be segmentor dependent. The SDs of the difference between volumes from manual and automated segmentations were similar at 1.5T and 3T, with a relatively narrow CI for their ratios. The SDs of the difference between BSIs from manual and automated segmentations were also similar at 1.5T and 3T but with a wider CI for their ratios. This study supports the use of our automated hippocampal voluming methods, developed using 1.5T images, with 3T images