Considering fractal dimensionality as a measure of age-related differences in brain morphology
10:00-11:00 Friday 3rd February 2017, IoPPN boardroom, Main Building
Different measures of cortical morphology have been shown to index distinct aspects of inter-individual differences (e.g., volume, thickness, surface area, gyrification). Here I consider the additional measure of structural complexity, as quantified by fractal dimensionality. Using several open-access MRI datasets, providing a combined sample of over 1000 adults across the adult lifespan, I examined the relationship between each measure and age-related differences in brain morphology. In a separate set of analyses I further examined the test-retest reliability of each measure. When examining the relationship between brain morphology and inter-individual differences, it is important to consider the most appropriate measure. For instance, it has been established that age-related differences are reflected most in cortical thickness, rather than surface area or volume. Here I demonstrate that fractal dimensionality, which incorporates shape-related properties, to be a more sensitive measure of age-related differences in cortical and subcortical structures. Limitations of this fractal dimensionality measure will also be discussed.