Explaining variability in ciclosporin exposure in adult kidney transplant recipients

International audienc

Extraversion is linked to volume of the orbitofrontal cortex and amygdala

Contains fulltext : 103145.pdf (publisher's version ) (Open Access)Neuroticism and extraversion are personality factors associated with the vulnerability for developing depression and anxiety disorders, and are possibly differentially related to brain structures implicated in the processing of emotional information and the generation of mood states. To date, studies on brain morphology mainly focused on neuroticism, a dimension primarily related to negative affect, yielding conflicting findings concerning the association with personality, partially due to methodological issues and variable population samples under study. Recently, extraversion, a dimension primarily related to positive affect, has been repeatedly inversely related to with symptoms of depression and anxiety disorders. In the present study, high resolution structural T1-weighted MR images of 65 healthy adults were processed using an optimized Voxel Based Morphometry (VBM) approach. Multiple regression analyses were performed to test for associations of neuroticism and extraversion with prefrontal and subcortical volumes. Orbitofrontal and right amygdala volume were both positively related to extraversion. Extraversion was differentially related to volume of the anterior cingulate cortex in males (positive) and females (negative). Neuroticism scores did not significantly correlate with these brain regions. As extraversion is regarded a protective factor for developing anxiety disorders and depression and has been related to the generation of positive affect, the present results indicate that the reduced likelihood of developing affective disorders in individuals high on extraversion is related to modulation of emotion processing through the orbitofrontal cortex and the amygdala.6 p

Melioidosis in travelers: An analysis of Dutch melioidosis registry data 1985–2018

Background: Melioidosis, caused by the Gram-negative bacterium Burkholderia pseudomallei, is an opportunistic infection across the tropics. Here, we provide a systematic overview of imported human cases in a non-endemic country over a 25-year period. Methods: All 5

The relation between statistical power and inference in fMRI

<div><p>Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects), and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial—especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20–30) display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate) prediction methods and meta-analyses with related synthesis-oriented approaches.</p></div

Examples of the sampling simulation.

<p>Two different brain-behavior correlation distributions (full sample n = 10.000): <b>(a)</b> Weak Diffuse (WD) and <b>(b)</b> Strong Localized (SL). The scatter plots display the voxel (indicated by a green circle in the image) with the strongest absolute correlation between its brain activity (y-axis) and the behavioral variable (x-axis). The color bar indicates the effect size (Pearson’s r). From these two full samples, 4 random subsamples are drawn with two different sample sizes: <b>(c)</b> n = 30 from the WD full sample <b>(d)</b> n = 30 from the SL full sample <b>(e)</b> n = 150 from the WD full sample <b>(f)</b> n = 150 from the SL full sample. For each subsample a <i>p</i> < .01 uncorrected threshold is applied. The distribution of the maximum effect sizes (absolute values) obtained from the subsampling procedure are shown for the <b>(g)</b> WD scenario and <b>(h)</b> SL scenario. The thick black lines indicate the maximum correlation of the full sample. Small samples (n = 30) of the WD scenario show a large discrepancy (<i>overestimation</i> of the effect sizes and <i>underestimation</i> of the spatial extend of brain-behavior correlations) with the full sample effects, and the WD subsamples appear more similar to the SL scenario. Larger samples of the WD scenario (n = 150) show less, but still substantial discrepancy with the full sample effects. For the SL scenario there is a small discrepancy between subsamples of either sample size and the full sample effects.</p

Main effect of the HCP social cognition task.

<p>(a) effects for the TOM>CON contrast in the full sample (n = 485). The colors reflect effect size (Cohen's d). (b) number of significant voxels and mean d in significant voxels as a function of subsample size. (c) Results of TOM>CON contrast for 16 random subsamples of n = 15. TOM; theory of Mind. CON; control condition.</p

A randomized pharmacological fMRI trial investigating d-cycloserine and brain plasticity mechanisms in learned pain responses

Learning and negative outcome expectations can increase pain sensitivity, a phenomenon known as nocebo hyperalgesia. Here, we examined how a targeted pharmacological manipulation of learning would impact nocebo responses and their brain correlates. Participants received either a placebo (n = 27) or a single 80 mg dose of d-cycloserine (a partial NMDA receptor agonist; n = 23) and underwent fMRI. Behavioral conditioning and negative suggestions were used to induce nocebo responses. Participants underwent pre-conditioning outside the scanner. During scanning, we first delivered baseline pain stimulations, followed by nocebo acquisition and extinction phases. During acquisition, high intensity thermal pain was paired with supposed activation of sham electrical stimuli (nocebo trials), whereas moderate pain was administered with inactive electrical stimulation (control trials). Nocebo hyperalgesia was induced in both groups (p &lt; 0.001). Nocebo magnitudes and brain activations did not show significant differences between d-cycloserine and placebo. In acquisition and extinction, there were significantly increased activations bilaterally in the amygdala, ACC, and insula, during nocebo compared to control trials. Nocebo acquisition trials also showed increased vlPFC activation. Increased opercular activation differentiated nocebo-augmented pain aggravation from baseline pain. These results support the involvement of integrative cognitive-emotional processes in nocebo hyperalgesia.Applied Ergonomics and Desig

Voxel-based morphometry multi-center mega-analysis of brain structure in social anxiety disorder

Social anxiety disorder (SAD) is a prevalent and disabling mental disorder, associated with significant psychiatric comorbidity. Previous research on structural brain alterations associated with SAD has yielded inconsistent results concerning the direction of the changes in graymatter (GM) in various brain regions, as well as on the relationship between brain structure and SAD-symptomatology. These heterogeneous findings are possibly due to limited sample sizes. Multisite imaging offers new opportunities to investigate SAD-related alterations in brain structure in larger samples. An international multi-center mega-analysis on the largest database of SAD structural T1-weighted 3T MRI scans to date was performed to compare GM volume of SAD-patients (n = 174) and healthy control (HC)-participants (n = 213) using voxel-based morphometry. A hypothesis-driven region of interest (ROI) approach was used, focusing on the basal ganglia, the amygdala-hippocampal complex, the prefrontal cortex, and the parietal cortex. SAD-patients had larger GM volume in the dorsal striatum when compared to HC-participants. This increase correlated positively with the severity of self-reported social anxiety symptoms. No SAD-related differences in GM volume were present in the other ROIs. Thereby, the results of this mega-analysis suggest a role for the dorsal striatum in SAD, but previously reported SAD-related changes in GM in the amygdala, hippocampus, precuneus, prefrontal cortex and parietal regions were not replicated. Our findings emphasize the importance of large sample imaging studies and the need for meta-analyses like those performed by the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium