Introduction: Cushing's disease (CD) is a rare and severe endocrine disease characterized by hypercortisolemia. Previous studies have found structural brain alterations in remitted CD patients... Show moreIntroduction: Cushing's disease (CD) is a rare and severe endocrine disease characterized by hypercortisolemia. Previous studies have found structural brain alterations in remitted CD patients compared to healthy controls, specifically in the anterior cingulate cortex (ACC). However, potential mechanisms through which these persistent alterations may have occurred are currently unknown. Methods: Structural 3T MRI's from 25 remitted CD patients were linked with gene expression data from neurotypical donors, derived from the Allen Human Brain Atlas. Differences in gene expression between the ACC and an unaffected control cortical region were examined, followed by a Gene Ontology (GO) enrichment analysis. A cell type enrichment analysis was conducted on the differentially expressed genes, and a disease association enrichment analysis was conducted to determine possible associations between differentially expressed genes and specific diseases. Subsequently, cortisol sensitivity of these genes in existing datasets was examined. Results: The gene expression analysis identified 300 differentially expressed genes in the ACC compared to the cortical control region. GO analyses found underexpressed genes to represent immune function. The cell type specificity analysis indicated that underexpressed genes were enriched for deactivated microglia and oligodendrocytes. Neither significant associations with diseases, nor evidence of cortisol sensitivity with the differentially expressed genes were found. Discussion: Underexpressed genes in the ACC, the area vulnerable to permanent changes in remitted CD patients, were often associated with immune functioning. The specific lack of deactivated microglia and oligodendrocytes implicates protective effects of these cell types against the long-term effects of cortisol overexposure. Show less
Although the outcomes of our daily-life risky decisions are often unknown (e.g., receiving or not receiving a fine after running a red light), the probabilities of these outcomes may also vary in... Show moreAlthough the outcomes of our daily-life risky decisions are often unknown (e.g., receiving or not receiving a fine after running a red light), the probabilities of these outcomes may also vary in uncertainty. That is, the probabilities may be known (risk) or unknown (ambiguity), which influences risk taking behavior to a great extent. A developmental phase associated with heightened risk taking is adolescence, yet how adolescents process risk and ambiguity, and the relation with real-life risk taking, remain elusive. Moreover, individual differences in observed risk taking behavior remain largely overlooked. In this PhD thesis risk and ambiguity processing in adolescents were decomposed using behavioral economics and fMRI, and related to real-life risk taking. The results indicated that risk and ambiguity differentially impact risk-taking behavior, and are processed by different neural mechanisms. In addition, individual variation in task-related and real-life risk taking highlighted that adolescence is not a phase of heightened risk taking for everyone. Moreover, it was found that real-life risk-taking and prosocial tendencies were both predicted by fun seeking, suggesting this trait may make individuals differentially susceptible to positive or negative outcomes. Together, this thesis points towards a more nuanced perspective on adolescent risk taking and its underlying components. Show less
Coppen, E.M.; Jacobs, M.; Berg-Huysmans, A.A. van den; Grond, J. van der; 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
Objective: A sensorimotor network structural phenotype predicted motor task performance in a previous study in Huntington's disease (HD) gene carriers. We investigated in the visual network whether... Show moreObjective: A sensorimotor network structural phenotype predicted motor task performance in a previous study in Huntington's disease (HD) gene carriers. We investigated in the visual network whether structure - function - behaviour relationship patterns, and the effects of the HD mutation, extended beyond the sensorimotor network.Methods: We used multimodal visual network MRI structural measures (cortical thickness and white matter connectivity), plus visual evoked potentials and task performance (Map Search; Symbol Digit Modalities Test) in healthy controls and HD gene carriers.Results: Using principal component (PC) analysis, we identified a structure - function relationship common to both groups. PC scores differed between groups indicating white matter disorganization (higher RD, lower FA) and slower, and more disperse, VEP signal transmission (higher VEP P100 latency and lower VEP P100 amplitude) in HD than controls while task performance was similar.Conclusions: HD may be associated with reduced white matter organization and efficient visual network function but normal task performance.Significance: These findings indicate that structure - function relationships in the visual network, and the effects of the HD mutation, share some commonalities with those in the sensorimotor network. However, implications for task performance differ between the two networks suggesting the influence of network specific factors. (C) 2019 Published by Elsevier B.V. on behalf of International Federation of Clinical Neurophysiology. Show less
Karch, J.D.; Fivelich, E.; Wenger, E.; Lisofski, N.; Becker, M.; Butler, O.; ... ; Kühn, S. 2019
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
Alzheimer’s disease (AD) is a neurodegenerative disease characterized by memory loss and declined cognitive functioning. Brain changes in AD involve grey matter atrophy and changes in brain... Show moreAlzheimer’s disease (AD) is a neurodegenerative disease characterized by memory loss and declined cognitive functioning. Brain changes in AD involve grey matter atrophy and changes in brain function. These different brain characteristics can respectively be visualized with structural and functional MRI scans. These MRI modalities have been used for AD classification, but studies typically only include a limited number of features. In this thesis we derived multiple types of features from each MRI modality, and combined those to discriminate AD patients and elderly controls. First, we showed that AD classification accuracy increases when combining multiple types of measures from a single MRI modality. This was shown for structural MRI scans in chapter 2, and for resting state fMRI scans in chapter 3. In chapter 4 we evaluated whether MRI based AD classification models can discriminate AD in a diverse clinical population as well. This worked to some extent, and it worked best using structural MRI scans. In chapter 5 we used baseline multimodal MRI scans from the same diverse clinical population to predict two-year follow-up cognitive decline. Decline was predicted above chance level for the MMSE, but not for six other neuropsychological tests. Show less
