| 1. |
- Bergamino, Maurizio, et al.
(författare)
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Applying a free-water correction to diffusion imaging data uncovers stress-related neural pathology in depression
- 2016
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Ingår i: NeuroImage. - : Elsevier. - 2213-1582. ; 10, s. 336-342
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Tidskriftsartikel (refereegranskat)abstract
- Diffusion tensor imaging (DTI) holds promise for developing our understanding of white-matter pathology in major depressive disorder (MDD). Variable findings in DTI-based investigations ofMDD, however, have thwarted development of this literature. Effects of extra-cellular free-water on the sensitivity of DTI metrics could account for some of this inconsistency. Here we investigated whether applying a free-water correction algorithm to DTI data could improve the sensitivity to detect clinical effects using DTI metrics. Only after applying this correction, we found: a) significantly decreased fractional anisotropy and axial diffusivity (AD) in the left inferior frontooccipital fasciculus (IFOF) in MDD; and b) increased self-reported stress that significantly correlated with decreased IFOF AD in depression. We estimated and confirmed the robustness of differences observed between free-water corrected and uncorrected approaches using bootstrapping. We conclude that applying a free-water correction to DTI data increases the sensitivity of DTI-based metrics to detect clinical effects in MDD. (C) 2015 The Authors. Published by Elsevier Inc.
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| 2. |
- Bergamino, Maurizio, et al.
(författare)
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Statistical differences in the white matter tracts in subjects with depression by using different skeletonized voxel-wise analysis approaches and DTI fitting procedures
- 2017
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Ingår i: Brain Research. - : Elsevier. - 0006-8993 .- 1872-6240. ; 1669, s. 131-140
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Tidskriftsartikel (refereegranskat)abstract
- Major depressive disorder (MDD) is one of the most significant contributors to the global burden of illness. Diffusion tensor imaging (DTI) is a procedure that has been used in several studies to characterize abnormalities in white matter (WM) microstructural integrity in MDD. These studies, however, have provided divergent findings, potentially due to the large variety of methodological alternatives available in conducting DTI research. In order to determine the importance of different approaches to coregistration of DTI-derived metrics to a standard space, we compared results from two different skeletonized voxel-wise analysis approaches: the standard TBBS pipeline and the Advanced Normalization Tools (ANTs) approach incorporating a symmetric image normalization (SyN) algorithm and a group-wise template (ANTs TBSS). We also assessed effects of applying twelve different fitting procedures for the diffusion tensor. For our dataset, lower fractional anisotropy (FA) and axial diffusivity (AD) in depressed subjects compared with healthy controls were found for both methods and for all fitting procedures. No group differences were found for radial and mean diffusivity indices. Importantly, for the AD metric, the normalization methods and fitting procedures showed reliable differences, both in the volume and in the number of significant between-groups difference clusters detected. Additionally, a significant voxel-based correlation, in the left inferior fronto-occipital fasciculus, between AD and self-reported stress was found only for one of the normalization procedure (ANTs TBSS). In conclusion, the sensitivity to detect group-level effects on DTI metrics might depend on the DTI normalization and/or tensor fitting procedures used.
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| 3. |
- Paul, Elisabeth R., 1991-, et al.
(författare)
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Functional Connectivity Between Extrastriate Body Area and Default Mode Network Predicts Depersonalization Symptoms in Major Depression : Findings From an A Priori Specified Multinetwork Comparison
- 2019
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Ingår i: Biological Psychiatry. - : Elsevier. - 2451-9022. ; 4:7, s. 627-635
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundDepersonalization/derealization disorder is a dissociative disorder characterized by feelings of unreality and detachment from the self and surroundings. Depersonalization/derealization disorder is classified as a primary disorder, but depersonalization symptoms are frequently observed in mood and anxiety disorders. In the context of major depressive disorder (MDD), depersonalization symptoms are associated with greater depressive severity as indexed by treatment resistance, inpatient visits, and duration of depressive episodes. In the current investigation, we tested four network-based, neural-functional hypotheses of depersonalization in MDD. These hypotheses were framed in terms of functional relationships between 1) extrastriate body area and default mode network (DMN); 2) hippocampus and DMN; 3) medial prefrontal cortex and ventral striatum; and 4) posterior and anterior insular cortex.MethodsWe conducted functional magnetic resonance imaging during resting state on 28 female patients with MDD and 27 control subjects with no history of a psychiatric disorder. Functional connectivity between seed and target regions as specified by our network-level hypotheses was computed and correlated with scores on the Cambridge Depersonalization Scale. We used a conservative, unbiased bootstrapping procedure to test the significance of neural-behavioral correlations observed under each of the four models tested.ResultsOf the four neural-functional models of depersonalization symptoms tested, only the model proposing that reduced connectivity between the extrastriate body area and DMN predicts higher levels of depersonalization symptoms in MDD was confirmed.ConclusionsOur results indicate that depersonalization/derealization disorder symptoms in patients with depression are related to reduced functional connectivity between brain regions that are proposed to support processing of body-related (extrastriate body area) and autobiographical (DMN) information.
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