Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and... Show moreAdequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-person variance. To this end, we applied both classical statistical methods and machine-learning-inspired approaches to structural magnetic resonance imaging (sMRI) data of six participants aged 24–31 years gathered at 40–50 occasions distributed over 6–8 months from the Day2day study. We explored the within-person associations between 21 variables covering physiological, affective, social, and environmental factors and global measures of brain volume estimated by VBM8 and FreeSurfer. Time since the first scan was reliably associated with Freesurfer estimates of grey matter volume and total cortex volume, in line with a rate of annual brain volume shrinkage of about 1 percent. For the same two structural measures, time of day also emerged as a reliable predictor with an estimated diurnal volume decrease of, again, about 1 percent. Furthermore, we found weak predictive evidence for the number of steps taken on the previous day and testosterone levels. The results suggest a need to control for time-of-day effects in sMRI research. In particular, we recommend that researchers interested in assessing longitudinal change in the context of intervention studies or longitudinal panels make sure that, at each measurement occasion, (a) a given participant is measured at the same time of day; (b) all participants are measured at about the same time of day. Furthermore, the potential effects of physical activity, including moderate amounts of aerobic exercise, and testosterone levels on MRI-based measures of brain structure deserve further investigation. Show less
Coppen, E.M.; Grond, J. van der; Hafkemeijer, A.; Barkey Wolf, J.J.H.; Roos, R.A.C. 2018
Huntington's disease (HD) is an autosomal‐dominant inherited neurodegenerative disorder characterized by motor disturbances, psychiatric disturbances, and cognitive impairment. Visual cognitive... Show moreHuntington's disease (HD) is an autosomal‐dominant inherited neurodegenerative disorder characterized by motor disturbances, psychiatric disturbances, and cognitive impairment. Visual cognitive deficits and atrophy of the posterior cerebral cortex are additionally present in early disease stages. This study aimed to assess the extent of structural and functional brain alterations of the visual cortex in HD gene carriers using different neuroimaging modalities. Structural and functional magnetic resonance imaging data were acquired from 18 healthy controls, 21 premanifest, and 20 manifest HD gene carriers. Voxel‐based morphometry (VBM) analysis and cortical thickness measurements were performed to assess structural changes in the visual cortex. Brain function was measured by assessing neuronal connectivity changes in response to visual stimulation and at rest in visual resting‐state networks. Multiple linear regression analyses were performed to examine the relationship between visual cognitive function and structural imaging measures. Compared to controls, pronounced atrophy and decreased neuronal function at rest were present in associative visual cortices in manifest HD. The primary visual cortex did not show group differences in cortical thickness and in vascular activity after visual stimulation. Thinning of the associative visual cortex was related to worse visual perceptual function. Premanifest HD gene carriers did not show any differences in brain structure or function compared to controls. This study improves the knowledge on posterior brain changes in HD, as our findings suggest that the primary visual cortex remains preserved, both structurally and functionally, while atrophy of associative visual cortices is present in early HD and linked to clinical visual deficits. Show less
Bas, J.M.; Steenbergen, H. van; Pannekoek, J.N.; Fouche, J.P.; Lochner, C.; Hattingh, C.J.; ... ; Wee, N.J.A. van der 2017
