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Baker, Ryan Cabeen, Erbil Akbudak, Xi Luo, Peisi Yan and Robert H. Malerei der Gegenwart I , Kunsthalle der Hypo-Kulturstiftung, Munich Germany Körper, Gesicht und Seele: Frauenbilder vom 16. Here, 120 participants 20-85 years were tested at two time points, separated by 3.
Nederlandse kunst na 1945, Stedelijk Museum Schiedam, Schiedam The Netherlands Sluizen Floodgates. Curated by Artur Elmer 24 April 2003-24 August 2003. Our sample size, despite being the largest of its kind studied to date, did not allow us to examine sex differences in trajectories of cortical changes with age.
Paulina Due-Tønnesen - The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism.
Abstract It is well established that human brain white matter structure changes with aging, but the timescale and spatial distribution of this change remain uncertain. However, inferring trajectories of change from cross-sectional data can be challenging; and, as yet, there have been no longitudinal reports of the timescale and spatial distribution of age-related white matter change in healthy adults across the adult lifespan. We found extensive and overlapping significant annual decreases in fractional anisotropy, and increases in axial diffusivity, radial diffusivity, and mean diffusivity. Spatially, results were consistent with inferior-to-superior gradients of lesser-to-greater vulnerability. Annual change increased with age, particularly within superior regions, with age-related decline estimated to begin in the fifth decade. Spatially, results have been discussed within the context of several anatomical frameworks, and there is continued debate regarding the extent to which age-related changes are localized to the frontal lobe, follow posterior-to-anterior or inferior-to-superior gradients of lesser-to-greater vulnerability, or represent a selective deterioration of specific white matter tracts ;. The conclusions that can be drawn from cross-sectional studies are, unfortunately, limited because of between-subject variance and possible cohort effects. Although accelerated rates of annual change with age have not been demonstrated in older populations , examining annual change in a larger sample and across a broader age range may provide greater sensitivity to detect an effect. First, we aim to describe the pattern of annual change over a 3 to 5 year period, independent of the effect of age. Second, we aim to examine the effect of age on annual change. Anatomically, our main aim is to explore the extent to which changes follow posterior-to-anterior or inferior-to-superior gradients. The sample was drawn from the ongoing project Cognition and Plasticity through the Lifespan at the Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo ,. All procedures were approved by the Regional Ethical Committee for Medical and Health Research Ethics, and written consent was obtained from all participants before commencement. For the first wave of data collection, participants were recruited through newspaper advertisements. Recruitment for the follow-up assessment was by written invitation to the original participants. At both time points, participants were screened with health interviews to ascertain eligibility. Participants were required to be right handed, fluent Norwegian speakers, and have normal or corrected to normal vision and hearing. Furthermore, at both time points, all scans were evaluated by a neuroradiologist and were required to be deemed free of significant injuries or pathological conditions. Exclusion criteria did not extend to vascular risk factors, such as hypertension or diabetes. A total of 281 participants satisfied the inclusion criteria at baseline. Full participant characteristics are provided in. Briefly, the mean age at baseline was 50. Mean interval between scans was 3. One participant was prescribed blood pressure medication at baseline, and 19 participants at follow-up. One participant had a diagnosis of diabetes and was prescribed insulin both at baseline and follow-up. Two participants were receiving treatment for depression at follow-up, with one prescribed antidepressant medication. Higher levels of cognitive ability in returning participants has often been noted and discussed in longitudinal studies ;. Imaging data were collected using a 12-channel head coil on a 1. The same scanner and sequences were used at both time points, although with minor software upgrades. Acquisition time was 11 min 21 s. Averaging was performed before tensor fitting. However, because the skeleton was based on the mean of all scans from both time points, there is no danger that the registration procedure could cause a bias in the change estimates in any direction. For T 1-weighted images, the two runs were averaged during preprocessing, to increase the signal-to-noise ratio. The resulting images were first automatically processed cross-sectionally independently for each time point with FreeSurfer version 5. To investigate the pattern of annual change, a nonparametric one-sample t test was run with mean age of the two time points and sex as confound regressors. To investigate acceleration of annual change with age, a correlation between annual change and mean age of the two time points was run with sex as a confound regressor. Because diffusivity values can approach 0 and lead to misleading percentage change values, voxelwise statistics were performed on annual difference maps rather than maps of annual percentage change. In interpreting global and lobe profiles, it is important to consider the interaction between gradients; for example, anterior portions of the frontal lobe are more inferior compared with posterior portions, and we have therefore illustrated the center of gravity for each coronal and axial slice in. Curve fitting was performed using functions freely available through the statistical environment R, version 3. To examine the influence of sex, we examined whether annual change or age correlations were significantly different between males and females. Annual change was greatest within the frontal and parietal lobes. Coronal profiles showed that annual change increased gradually along the posterior-to-anterior gradient within the parietal lobe for all measures and peaked after fibers entered the frontal lobe. Results were similar after excluding age or sex as covariates or including interval as an additional covariate. Significant regions primarily fell within the frontal and parietal lobes, with the occipital and temporal lobes affected to a lesser extent ;. Significant regions spanned all of the major white matter tracts and included vast portions of the anterior thalamic radiation, body and genu of the corpus callosum, and superior longitudinal fasciculus. Coronal and axial profiles of the mean t statistic within a slice displayed similar profiles to mean annual change. Overlap of voxels showing significant change. Mean annual difference and equivalent percentage change within significant regions are illustrated in. Including interval as an additional covariate did not reduce the percentage of significant voxels. Similar to analyses of annual change, significant regions spanned widespread portions of the frontal and parietal lobes, with the occipital and temporal lobes affected to a lesser degree ;. Again, vast portions of the anterior thalamic radiation, body and genu of the corpus callosum, and superior longitudinal fasciculus displayed significant voxels. Acceleration of annual change with age. Voxelwise analysis, covarying for age, did not reveal any areas in which annual change was significantly different between sexes. Anatomy of age-related changes There were striking similarities in the anatomy of annual change and acceleration of annual change with age, and we now consider the most appropriate framework for age-related changes with reference to the results of both analyses. Overall, as illustrated by slice-by-slice profiles, age-related changes appear to be principally governed by inferior-to-superior gradients. Our conclusion, however, may well reflect the combination of methods used, rather than the anatomy itself, representing a major departure from published cross-sectional results. Indeed, our results can be considered with reference to several alternative anatomical frameworks. For example, first, it has been proposed that the frontal lobe is particularly vulnerable to age-related deterioration. Whereas our results support age-related degeneration within the frontal lobe, significant findings also included wide portions of the parietal lobe, with occipital and temporal lobes affected to a lesser extent. Crucially, slice-by-slice profiles illustrated that, at a given axial slice, lobe did not appear to exert a major influence. Therefore, we conclude that the predilection for age-related changes within frontal and parietal lobes reflects the superior positioning of these lobes, compared with occipital and temporal lobes, rather than representing lobe-specific effects. Second, it has been proposed that, rather than the anatomy of age-related deterioration being dictated by lobe boundaries, changes follow posterior-to-anterior gradients. Whereas such gradients have been discussed as a global phenomena, observed posterior-to-anterior gradients only when examining superior clusters, and demonstrated posterior-to-anterior gradients within tracts traversing frontal and parietal cortices but not the temporal cortex. In line with these refinements, posterior-to-anterior gradients were repeatedly observed within the parietal lobe, in which the axial center of gravity remains relatively stable and superior. Within the frontal lobe, posterior-to-anterior gradients were not demonstrated; instead, the pattern paralleled axial slice position. Therefore, we conclude that posterior-to-anterior gradients are anatomically specific and appear to be secondary to inferior-to-superior gradients. Third, it has been proposed that age-related changes represent a selective deterioration of specific white matter tracts. Although our voxelwise analyses highlighted the involvement of the anterior thalamic radiation, body and genu of the corpus callosum, and superior longitudinal fasciculus, it does not appear that the gradient effect is merely due to selective deterioration of fiber systems. Longitudinal tractography studies will provide a greater insight into this issue. Within each of the anatomical frameworks discussed, parallels have been drawn between the patterns of age-related decline and the patterns associated with development. Specifically, it has been suggested that the lobes, regions, and tracts that are latest to develop are the first to decline in aging. Longitudinal studies examining gradients across the entire lifespan, rather than solely the adult lifespan, will allow a more direct examination of this hypothesis. Furthermore, it has been speculated that the anatomy of white matter development and decline reflects myelination and myelin breakdown, respectively. Overlap of age-related changes Analyses examining annual change and acceleration of change with age produced highly complementary findings with regard to overlap between significant voxels. Disentangling different profiles of anisotropy and diffusivity changes, and linking each to a distinct biological process, remains controversial, so results should be interpreted with caution. The age at which decline begins Pinpointing the age at which decline in white matter microstructure begins has important implications for public health interventions aimed at promoting healthy aging. Our results indicate that the onset of age-related decline falls toward the later end of such ranges, in the fifth decade. Such findings are in accordance with cross-sectional studies that have reported an absence of age correlations within the temporal and occipital lobes and less clear-cut age trajectories within the hippocampal portion of the cingulum. Age × sex interactions have been reported by some cross-sectional studies , but other studies have reported nonsignificant findings ;. In light of such mixed findings, this is a key area for future research. Strengths and limitations Major strengths of our study included the longitudinal design, large sample size, and the wide age range of participants. Participants passed a thorough screening procedure, minimizing the possibility that psychological or neurological diagnoses confounded results. However, as degenerative conditions can have long-lasting preclinical periods, it is difficult to ensure that subclinical or preclinical conditions did not influence findings. Participants generally performed above average on tests of cognitive functioning and may therefore not be representative of the general population. Possible confounds associated with cross-sectional studies, including between-subject variance and cohort effects, apply to analyses examining correlations with age. With regard to data acquisition and analysis, the study benefitted from the same scanner and sequence being used at both time points. As our primary anatomical aim was to examine continuous gradients of vulnerability across the whole brain, we chose to use a voxelwise statistical approach, which was not without limitations. For example, we only included participants with full datasets in our analyses. It will be important for future studies to use optimized longitudinal statistical approaches that can incorporate incomplete datasets. In conclusion, we have shown that extensive changes in white matter microstructure can be detected longitudinally over 3—5 years and that changes accelerate with advanced age and follow inferior-to-superior gradients of lesser-to-greater vulnerability.