| 1. |
- Almby, Kristina E., et al.
(författare)
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Effects of Gastric Bypass Surgery on the Brain : Simultaneous Assessment of Glucose Uptake, Blood Flow, Neural Activity, and Cognitive Function During Normo- and Hypoglycemia
- 2021
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Ingår i: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 70:6, s. 1265-1277
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Tidskriftsartikel (refereegranskat)abstract
- While Roux-en-Y gastric bypass (RYGB) surgery in obese individuals typically improves glycemic control and prevents diabetes, it also frequently causes asymptomatic hypoglycemia. Previous work showed attenuated counterregulatory responses following RYGB. The underlying mechanisms as well as the clinical consequences are unclear. In this study, 11 subjects without diabetes with severe obesity were investigated pre- and post-RYGB during hyperinsulinemic normo-hypoglycemic clamps. Assessments were made of hormones, cognitive function, cerebral blood flow by arterial spin labeling, brain glucose metabolism by F-18-fluorodeoxyglucose (FDG) positron emission tomography, and activation of brain networks by functional MRI. Post- versus presurgery, we found a general increase of cerebral blood flow but a decrease of total brain FDG uptake during normoglycemia. During hypoglycemia, there was a marked increase in total brain FDG uptake, and this was similar for post- and presurgery, whereas hypothalamic FDG uptake was reduced during hypoglycemia. During hypoglycemia, attenuated responses of counterregulatory hormones and improvements in cognitive function were seen postsurgery. In early hypoglycemia, there was increased activation post- versus presurgery of neural networks in brain regions implicated in glucose regulation, such as the thalamus and hypothalamus. The results suggest adaptive responses of the brain that contribute to lowering of glycemia following RYGB, and the underlying mechanisms should be further elucidated.
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| 2. |
- Beckmann, Katrin M., et al.
(författare)
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Increased resting state connectivity in the anterior default mode network of idiopathic epileptic dogs
- 2021
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Epilepsy is one of the most common chronic, neurological diseases in humans and dogs and considered to be a network disease. In human epilepsy altered functional connectivity in different large-scale networks have been identified with functional resting state magnetic resonance imaging. Since large-scale resting state networks have been consistently identified in anesthetised dogs' application of this technique became promising in canine epilepsy research. The aim of the present study was to investigate differences in large-scale resting state networks in epileptic dogs compared to healthy controls. Our hypothesis was, that large-scale networks differ between epileptic dogs and healthy control dogs. A group of 17 dogs (Border Collies and Greater Swiss Mountain Dogs) with idiopathic epilepsy was compared to 20 healthy control dogs under a standardized sevoflurane anaesthesia protocol. Group level independent component analysis with dimensionality of 20 components, dual regression and two-sample t test were performed and revealed significantly increased functional connectivity in the anterior default mode network of idiopathic epileptic dogs compared to healthy control dogs (p = 0.00060). This group level differences between epileptic dogs and healthy control dogs identified using a rather simple data driven approach could serve as a starting point for more advanced resting state network analysis in epileptic dogs.
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| 3. |
- Beckmann, Katrin M., et al.
(författare)
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Resting state networks of the canine brain under sevoflurane anaesthesia
- 2020
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:4
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Tidskriftsartikel (refereegranskat)abstract
- Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has become an established technique in humans and reliably determines several resting state networks (RSNs) simultaneously. Limited data exist about RSN in dogs. The aim of this study was to investigate the RSNs in 10 healthy beagle dogs using a 3 tesla MRI scanner and subsequently perform group-level independent component analysis (ICA) to identify functionally connected brain networks. Rs-fMRI sequences were performed under steady state sevoflurane inhalation anaesthesia. Anaesthetic depth was titrated to the minimum level needed for immobilisation and mechanical ventilation of the patient. This required a sevoflurane MAC between 0.8 to 1.2. Group-level ICA dimensionality of 20 components revealed distributed sensory, motor and higher-order networks in the dogs' brain. We identified in total 7 RSNs (default mode, primary and higher order visual, auditory, two putative motor-somatosensory and one putative somatosensory), which are common to other mammals including humans. Identified RSN are remarkably similar to those identified in awake dogs. This study proves the feasibility of rs-fMRI in anesthetized dogs and describes several RSNs, which may set the basis for investigating pathophysiological characteristics of various canine brain diseases.
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| 4. |
- Giannakopoulos, Panteleimon, et al.
(författare)
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Less agreeable, better preserved? : A PET amyloid and MRI study in a community-based cohort
- 2020
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Ingår i: Neurobiology of Aging. - : Elsevier. - 0197-4580 .- 1558-1497. ; 89, s. 24-31
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Tidskriftsartikel (refereegranskat)abstract
- The relationship between personality profiles and brain integrity in old age is still a matter of debate. We examined the association between Big Five factor and facet scores and MRI brain volume changes on a 54-month follow-up in 65 elderly controls with 3 neurocognitive assessments (baseline, 18 months, and 54 months), structural brain MRI (baseline and 54 months), brain amyloid PET during follow-up, and APOE genotyping. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models were used to identify predictors of volume loss including time, age, sex, personality, amyloid load, presence of APOE epsilon 4 allele, and cognitive evolution. Lower agreeableness factor scores (and 4 of its facets) were associated with lower volume loss in the hippocampus, entorhinal cortex, amygdala, mesial temporal lobe, and precuneus bilaterally. Higher openness factor scores (and 2 of its facets) were also associated with lower volume loss in the left hippocampus. Our findings persisted when adjusting for confounders in multivariable models. These data suggest that the combination of low agreeableness and high openness is an independent predictor of better preservation of brain volume in areas vulnerable to neurodegeneration. (C) 2020 Elsevier Inc. All rights reserved.
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| 5. |
- Giannakopoulos, Panteleimon, et al.
(författare)
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Personality Factors' Impact on the Structural Integrity of Mentalizing Network in Old Age : A Combined PET-MRI Study
- 2020
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Ingår i: Frontiers in Psychiatry. - : Frontiers Media SA. - 1664-0640. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- The mentalizing network (MN) treats social interactions based on our understanding of other people's intentions and includes the medial prefrontal cortex (mPFC), temporoparietal junction (TPJ), posterior cingulate cortex (PCC), precuneus (PC), and amygdala. Not all elders are equally affected by the aging-related decrease of mentalizing abilities. Personality has recently emerged as a strong determinant of functional connectivity in MN areas. However, its impact on volumetric changes across the MN in brain aging is still unknown. To address this issue, we explored the determinants of volume decrease in MN components including amyloid burden, personality, and APOE genotyping in a previously established cohort of 130 healthy elders with a mean follow-up of 54 months. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models corrected for multiple comparisons were used to identify predictors of volume loss including time, age, sex, personality, amyloid load, presence of APOE epsilon 4 allele, and cognitive evolution. In cases with higher Agreeableness scores, there were lower volume losses in PCC, PC, and amygdala bilaterally. This was also the case for the right mPFC in elders displaying lower Agreeableness and Conscientiousness. In multiple regression models, the effect of Agreeableness was still observed in left PC and right amygdala and that of Conscientiousness was still observed in right mPFC volume loss (26.3% of variability, significant age and sex). Several Agreeableness (Modesty) and Conscientiousness (order, dutifulness, achievement striving, and self-discipline) facets were positively related to increased volume loss in cortical components of the MN. In conclusion, these data challenge the beneficial role of higher levels of Agreeableness and Conscientiousness in old age, showing that they are associated with an increased rate of volume loss within the MN.
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| 6. |
- Giannakopoulos, Panteleimon, et al.
(författare)
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Prediction of Subtle Cognitive Decline in Normal Aging : Added Value of Quantitative MRI and PET Imaging
- 2021
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Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media S.A.. - 1663-4365. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Quantitative imaging processing tools have been proposed to improve clinic-radiological correlations but their added value at the initial stages of cognitive decline is still a matter of debate. We performed a longitudinal study in 90 community-dwelling elders with three neuropsychological assessments during a 4.5 year follow-up period, and visual assessment of medial temporal atrophy (MTA), white matter hyperintensities, cortical microbleeds (CMB) as well as amyloid positivity, and presence of abnormal FDG-PET patterns. Quantitative imaging data concerned ROI analysis of MRI volume, amyloid burden, and FDG-PET metabolism in several AD-signature areas. Multiple regression models, likelihood-ratio tests, and areas under the receiver operating characteristic curve (AUC) were used to compare quantitative imaging markers to visual inspection. The presence of more or equal to four CMB at inclusion and slight atrophy of the right MTL at follow-up were the only parameters to be independently related to the worst cognitive score explaining 6% of its variance. This percentage increased to 24.5% when the ROI-defined volume loss in the posterior cingulate cortex, baseline hippocampus volume, and MTL metabolism were also considered. When binary classification of cognition was made, the area under the ROC curve increased from 0.69 for the qualitative to 0.79 for the mixed imaging model. Our data reveal that the inclusion of quantitative imaging data significantly increases the prediction of cognitive changes in elderly controls compared to the single consideration of visual inspection.
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| 7. |
- Haller, Sven, et al.
(författare)
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PET amyloid in normal aging : direct comparison of visual and automatic processing methods
- 2020
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Ingår i: Scientific Reports. - : NATURE RESEARCH. - 2045-2322. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Assessment of amyloid deposits is a critical step for the identification of Alzheimer disease (AD) signature in asymptomatic elders. Whether the different amyloid processing methods impacts on the quality of clinico-radiological correlations is still unclear. We directly compared in 155 elderly controls with extensive neuropsychological testing at baseline and 4.5 years follow-up three approaches: (i) operator-dependent standard visual reading, (ii) operator-independent automatic SUVR with four different reference regions, and (iii) novel operator and region of reference-independent automatic A beta-index. The coefficient of variance was used to examine inter-individual variability for each processing method. Using visually-established amyloid positivity as the gold standard, the area under the receiver operating characteristic curve (ROC) was computed. Linear regression models were used to assess the association between changes in continuous cognitive score and amyloid uptake values. In SUVR analyses, the coefficient of variance varied from 1.718 to 1.762 according to the area of reference and was of - 3.045 for the A beta-index method. Compared to the visual rating, A beta-index method showed the largest area under the ROC curve [0.9568 (95% CI 0.9252, 0.98833)]. The best cut-off score was of - 0.3359 with sensitivity and specificity values of 0.97 and 0.83, respectively. Only the A beta-index was related to more severe decrement of cognitive performances [regression coefficient: 9.103 (95% CI 1.148, 17.058)]. The A beta-index is considered as preferred option in asymptomatic elders, since it is operator-independent, avoids the selection of reference area, is closer to established visual scoring and correlates with the evolution of cognitive performances.
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| 8. |
- Haller, Sven, et al.
(författare)
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Susceptibility-weighted Imaging : Technical Essentials and Clinical Neurologic Applications
- 2021
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Ingår i: Radiology. - : RADIOLOGICAL SOC NORTH AMERICA. - 0033-8419 .- 1527-1315. ; 299:1, s. 3-26
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Tidskriftsartikel (refereegranskat)abstract
- Susceptibility-weighted imaging (SWI) evolved from simple two-dimensional T2*-weighted sequences to three-dimensional sequences with improved spatial resolution and enhanced susceptibility contrast. SWI is an MRI sequence sensitive to compounds that distort the local magnetic field (eg, calcium and iron), in which the phase information can differentiate. But the term SWI is colloquially used to denote high-spatial-resolution susceptibility-enhanced sequences across different MRI vendors and sequences even when phase information is not used. The imaging appearance of SWI and related sequences strongly depends on the acquisition technique. Initially, SWI and related sequences were mostly used to improve the depiction of findings already known from standard two-dimensional T2*-weighted neuroimaging: more microbleeds in patients who are aging or with dementia or mild brain trauma; increased conspicuity of superficial siderosis in Alzheimer disease and amyloid angiopathy; and iron deposition in neurodegenerative diseases or abnormal vascular structures, such as capillary telangiectasia. But SWI also helps to identify findings not visible on standard T2*-weighted images: the nigrosome 1 in Parkinson disease and dementia with Lewy bodies, the central vein and peripheral rim signs in multiple sclerosis, the peripheral rim sign in abscesses, arterial signal loss related to thrombus, asymmetrically prominent cortical veins in stroke, and intratumoral susceptibility signals in brain neoplasms. (C) RSNA, 2021
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| 9. |
- Haugg, Amelie, et al.
(författare)
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Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?
- 2020
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 41:14, s. 3839-3854
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Tidskriftsartikel (refereegranskat)abstract
- Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.
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| 10. |
- Haugg, Amelie, et al.
(författare)
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Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.
- 2021
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Ingår i: NeuroImage. - : Elsevier. - 1053-8119 .- 1095-9572. ; 237
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Tidskriftsartikel (refereegranskat)abstract
- Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.
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