| 1. |
- Bussy, Aurélie, et al.
(author)
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Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia
- 2023
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In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 44:7, s. 2684-2700
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Journal article (peer-reviewed)abstract
- Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.
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| 2. |
- Kühn, Simone, et al.
(author)
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The dynamics of change in striatal activity following updating training
- 2013
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In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 34:7, s. 1530-1541
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Journal article (peer-reviewed)abstract
- Increases in striatal activity have been suggested to mediate training-related improvements in working-memory ability. We investigated the temporal dynamics of changes in task-related brain activity following training of working memory. Participants in an experimental group and an active control group, trained on easier tasks of a constant difficulty in shorter sessions than the experimental group, were measured before, after about 1 week, and after more than 50 days of training. In the experimental group an initial increase of working-memory related activity in the functionally defined right striatum and anatomically defined right and left putamen was followed by decreases, resulting in an inverted u-shape function that relates activity to training over time. Activity increases in the striatum developed slower in the active control group, observed at the second posttest after more than 50 days of training. In the functionally defined left striatum, initial activity increases were maintained after more extensive training and the pattern was similar for the two groups. These results shed new light on the relation between activity in the striatum (especially the putamen) and the effects of working memory training, and illustrate the importance of multiple measurements for interpreting effects of training on regional brain activity.
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| 3. |
- Lövdén, Martin, et al.
(author)
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The dimensionality of between-person differences in white matter microstructure in old age
- 2013
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In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 34:6, s. 1386-1398
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Journal article (peer-reviewed)abstract
- Between-person differences in white matter microstructure may partly generalize across the brain and partly play out differently for distinct tracts. We used diffusion-tensor imaging and structural equation modeling to investigate this issue in a sample of 260 adults aged 60–87 years. Mean fractional anisotropy and mean diffusivity of seven white matter tracts in each hemisphere were quantified. Results showed good fit of a model positing that individual differences in white matter microstructure are structured according to tracts. A general factor, although accounting for variance in the measures, did not adequately represent the individual differences. This indicates the presence of a substantial amount of tract-specific individual differences in white matter microstructure. In addition, individual differences are to a varying degree shared between tracts, indicating that general factors also affect white matter microstructure. Age-related differences in white matter microstructure were present for all tracts. Correlations among tract factors did not generally increase as a function of age, suggesting that aging is not a process with homogenous effects on white matter microstructure across the brain. These findings highlight the need for future research to examine whether relations between white matter microstructure and diverse outcomes are specific or general. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.
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| 4. |
- Petersson, K M, et al.
(author)
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Learning-related effects and functional neuroimaging
- 1999
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In: Human Brain Mapping. - 1065-9471. ; 7:4, s. 43-234
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Journal article (peer-reviewed)abstract
- A fundamental problem in the study of learning is that learning-related changes may be confounded by nonspecific time effects. There are several strategies for handling this problem. This problem may be of greater significance in functional magnetic resonance imaging (fMRI) compared to positron emission tomography (PET). Using the general linear model, we describe, compare, and discuss two approaches for separating learning-related from nonspecific time effects. The first approach makes assumptions on the general behavior of nonspecific effects and explicitly models these effects, i.e., nonspecific time effects are incorporated as a linear or nonlinear confounding covariate in the statistical model. The second strategy makes no a priori assumption concerning the form of nonspecific time effects, but implicitly controls for nonspecific effects using an interaction approach, i.e., learning effects are assessed with an interaction contrast. The two approaches depend on specific assumptions and have specific limitations. With certain experimental designs, both approaches may be used and the results compared, lending particular support to effects that are independent of the method used. A third and perhaps better approach that sometimes may be practically unfeasible is to use a completely temporally balanced experimental design. The choice of approach may be of particular importance when learning-related effects are studied with fMRI.
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| 5. |
- Wenger, Elisabeth, et al.
(author)
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Comparing Manual and Automatic Segmentation of Hippocampal Volumes : Reliability and Validity Issues in Younger and Older Brains
- 2014
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In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 35:8, s. 4236-4248
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Journal article (peer-reviewed)abstract
- We compared hippocampal volume measures obtained by manual tracing to automatic segmentation with FreeSurfer in 44 younger (20-30 years) and 47 older (60-70 years) adults, each measured with magnetic resonance imaging (MRI) over three successive time points, separated by four months. Retest correlations over time were very high for both manual and FreeSurfer segmentations. With FreeSurfer, correlations over time were significantly lower in the older than in the younger age group, which was not the case with manual segmentation. Pearson correlations between manual and FreeSurfer estimates were sufficiently high, numerically even higher in the younger group, whereas intra-class correlation coefficient (ICC) estimates were lower in the younger than in the older group. FreeSurfer yielded higher volume estimates than manual segmentation, particularly in the younger age group. Importantly, FreeSurfer consistently overestimated hippocampal volumes independently of manually assessed volume in the younger age group, but overestimated larger volumes in the older age group to a less extent, introducing a systematic age bias in the data. Age differences in hippocampal volumes were significant with FreeSurfer, but not with manual tracing. Manual tracing resulted in a significant difference between left and right hippocampus (right > left), whereas this asymmetry effect was considerably smaller with FreeSurfer estimates. We conclude that FreeSurfer constitutes a feasible method to assess differences in hippocampal volume in young adults. FreeSurfer estimates in older age groups should, however, be interpreted with care until the automatic segmentation pipeline has been further optimized to increase validity and reliability in this age group.
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