Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group.

The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

Validation of non-REM sleep stage decoding from resting state fMRI using linear support vector machines.

A growing body of literature suggests that changes in consciousness are reflected in specific connectivity patterns of the brain as obtained from resting state fMRI (rs-fMRI). As simultaneous electroencephalography (EEG) is often unavailable, decoding of potentially confounding sleep patterns from rs-fMRI itself might be useful and improve data interpretation. Linear support vector machine classifiers were trained on combined rs-fMRI/EEG recordings from 25 subjects to separate wakefulness (S0) from non-rapid eye movement (NREM) sleep stages 1 (S1), 2 (S2), slow wave sleep (SW) and all three sleep stages combined (SX). Classifier performance was quantified by a leave-one-subject-out cross-validation (LOSO-CV) and on an independent validation dataset comprising 19 subjects. Results demonstrated excellent performance with areas under the receiver operating characteristics curve (AUCs) close to 1.0 for the discrimination of sleep from wakefulness (S0|SX), S0|S1, S0|S2 and S0|SW, and good to excellent performance for the classification between sleep stages (S1|S2:~0.9; S1|SW:~1.0; S2|SW:~0.8). Application windows of fMRI data from about 70 s were found as minimum to provide reliable classifications. Discrimination patterns pointed to subcortical-cortical connectivity and within-occipital lobe reorganization of connectivity as strongest carriers of discriminative information. In conclusion, we report that functional connectivity analysis allows valid classification of NREM sleep stages.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group.

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen's d=-0.14, % difference=-1.24). This effect was driven by patients with recurrent MDD (Cohen's d=-0.17, % difference=-1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen's d=-0.20, % difference=-1.85) and a trend toward smaller amygdala (Cohen's d=-0.11, % difference=-1.23) and larger lateral ventricles (Cohen's d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Interferon ß-1a reduces increased interleukin-16 levels in multiple sclerosis patients.

OBJECTIVES: There is convergent evidence for an important role of interleukin-16 (IL-16) in the pathogenesis of multiple sclerosis (MS). IL-16 serves as a chemoattractant for different immune cells that are involved in developing lesions. Here, we compared IL-16 levels of MS patients and controls and addressed the long-term effect of IFN-ß, the most common immunomodulatory MS therapy, on IL-16 serum levels in MS patients over 2 years. Beyond this, we analysed the expression of IL-16 in two CD4(+) T-cell subsets, Th1 and Th17 cells, which are important autoimmune mediators and affected by IFN-ß treatment, derived from myelin-specific T-cell transgenic mice. MATERIALS AND METHODS: IL-16 serum levels of 17 controls and of 16 MS patients before therapy and at months 1, 2, 3, 6, 9, 12 and 24 during IFN-ß1a therapy were determined by ELISA. MRI was performed before therapy, at months 12 and 24. IL-16 expression of in vitro differentiated murine myelin oligodendrocyte glycoprotein (MOG)-specific Th1 and Th17 cells was quantified by real-time PCR. RESULTS: Before therapy, MS patients showed significantly elevated IL-16 levels compared with controls irrespective of disease activity determined by MRI. Therapy with IFN-ß1a led to a significant linear decrease in IL-16 serum levels beginning after 2 months. MOG-specific Th17 cells expressed more IL-16 than Th1 cells. CONCLUSIONS: Reduction in increased IL-16 levels may be of relevance for the therapeutic effect of IFN-ß1a in MS. Easily accessible IL-16 serum levels hold a potential as biomarker of treatment efficacy in MS.

Ventromedial prefrontal cortex activity and rapid eye movement sleep are associated with subsequent fear expression in human subjects.

In humans, activity patterns in the ventromedial prefrontal cortex (vmPFC) have been found to be predictive of subsequent fear memory consolidation. Pioneering work in rodents has further shown that vmPFC-amygdala theta synchronization is correlated with fear memory consolidation. We aimed to evaluate whether vmPFC activity during fear conditioning is (1) correlated with fear expression the subsequent day and whether (2) this relationship is mediated by rapid eye movement (REM) sleep. We analyzed data from 17 young healthy subjects undergoing a fear conditioning task, followed by a fear extinction task 24 h later, both recorded with simultaneous skin conductance response (SCR) and functional magnetic resonance imaging measurements, with a polysomnographically recorded night sleep in between. Our results showed a correlation between vmPFC activity during fear conditioning and subsequent REM sleep amount, as well as between REM sleep amount and SCR to the conditioned stimulus 24 h later. Moreover, we observed a significant correlation between vmPFC activity during fear conditioning and SCR responses during extinction, which was no longer significant after controlling for REM sleep amount. vmPFC activity during fear conditioning was further correlated with sleep latency. Interestingly, hippocampus activity during fear conditioning was correlated with stage 2 and stage 4 sleep amount. Our results provide preliminary evidence that the relationship between REM sleep and fear conditioning and extinction observed in rodents can be modeled in healthy human subjects, highlighting an interrelated set of potentially relevant trait markers.

Brain volume and diffusion markers as predictors of disability and short-term disease evolution in multiple sclerosis.

BACKGROUND AND PURPOSE: MRI markers of neuroaxonal damage in MS have emerged as critical long-term predictors of MS-related disability. Here we investigated the potential of whole-brain diffusivity and brain volume for the prediction of cross-sectional disability and short- to medium-term clinical evolution. MATERIALS AND METHODS: In this multimodal prospective longitudinal MRI study of 54 patients with MS (87% under immunomodulatory therapy, baseline and follow-up at a median of 12 months), ADC histogram analysis, WM lesion load, BPF, whole-brain atrophy rate, MSFC score, and EDSS score were obtained. A total of 44 patients with no relapse at both time points were included. RESULTS: At both time points, ADC histogram analysis provided robust predictors of the MSFC scores (maximal R(2) = 0.576, P < .001), incorporated cognition and fine-motor skill subscores, and EDSS scores. Significant changes beyond physiologic age-related changes at follow-up were noted for ADC histogram markers and BPF. Stronger diffusivity alterations and brain volume at baseline predicted MSFC decline, as demonstrated by multiple linear regression analysis (mean ADC, R(2) = 0.203; P = .003) and lower baseline BPF in patients with declined compared with stable MSFC scores (P = .001). Results were independent of intercurrent relapses. CONCLUSIONS: Diffusion histogram analysis provided stable surrogates of disability in MS and proved sensitive for monitoring disease progression during a median of 12 months. Advanced neuroaxonal pathology at baseline was indicative of an increased risk for sustained progression during a median of 12 months, independent of intercurrent relapses.

Cognitive function in acromegaly: description and brain volumetric correlates.

In acromegaly, we reported on increased rates of affective disorders such as dysthymia and depression, as well as structural brain changes. Objective of this study was to determine if cognitive impairments in patients with acromegaly exist and whether such impairments are associated with structural brain alterations defined by magnetic resonance imaging (MRI). In this cross-sectional study, 55 patients with biochemically confirmed acromegaly were enrolled. MRI data were compared with 87 control subjects. Main outcome measures were performance levels in 13 cognitive tests covering the domains of attention, memory and executive function, with performance below the cut-off level of the 16th percentile rated as impaired. In addition, individual global and hippocampal volume changes were defined for each patient in reference to a normative sample. We found that up to 33.3% of the patients were impaired in the attention, up to 24.1% in the memory, and up to 16.7% in the executive function domain. 67.3% of the patients failed to reach the cut-off level in at least one subtest. MRI demonstrated increased global, left and right hippocampal grey matter and white matter, particularly early in the disease course. Rather few positive than expected negative correlations could be established between the hippocampal grey matter gain and cognitive performance. Cognitive dysfunction, particularly attentional deficits, are common in acromegaly, rendering neuropsychological testing essential in the diagnostic work-up.

The neural correlates of negative prediction error signaling in human fear conditioning.

In a temporal difference (TD) learning approach to classical conditioning, a prediction error (PE) signal shifts from outcome deliverance to the onset of the conditioned stimulus. Omission of an expected outcome results in a negative PE signal, which is the initial step towards successful extinction. In order to visualize negative PE signaling during fear conditioning, we employed combined functional magnetic resonance (fMRI) and skin conductance response (SCR) measurements in a conditioning task with visual stimuli and mild electrical shocks. Positive PE signaling was associated with increased activation in the bilateral insula, supplementary motor area, brainstem, and visual cortices. Negative PE signaling was associated with increased activation in the ventromedial and dorsolateral prefrontal cortices, the left lateral orbital gyrus, the middle temporal gyri, angular gyri, and visual cortices. The involvement of the ventromedial prefrontal and orbitofrontal cortex in extinction learning has been well documented, and this study provides evidence for the notion that these regions are already involved in negative PE signaling during fear conditioning.

Cervicothoracic intradural arachnoid cyst misdiagnosed as motor neuron disease.

Recognizing syndromes which mimic ALS is crucial both to avoid giving this diagnosis erroneously and since there may be appropriate treatments. We report a 63-year-old woman diagnosed with possible ALS five years ago based on upper and lower motor neuron signs with typical electrophysiology and normal cranial MRI. At reassessment, spinal MRI revealed a cervicothoracic cyst with cord compression that was successfully treated neurosurgically. Histopathology confirmed an arachnoid origin as suspected from MRI. Spinal cysts may mimic ALS and need to be thoroughly excluded by appropriate imaging.

The neural correlates and temporal sequence of the relationship between shock exposure, disturbed sleep and impaired consolidation of fear extinction.

Consolidation of extinction learning is a primary mechanism disrupted in posttraumatic stress disorder (PTSD), associated with hypoactivity of the ventromedial prefrontal cortex and hippocampus. A role for rapid eye movement (REM) sleep disturbances in this failure to consolidate extinction learning has been proposed. We performed functional magnetic resonance imaging (fMRI) with simultaneous skin conductance response (SCR) measurements in 16 healthy participants during conditioning/extinction and later recall of extinction. The visual stimuli were basic geometric forms and electrical shocks functioned as the unconditioned stimulus. Between the conditioning/extinction and recall sessions, participants received a 90-min sleep window in the sleep laboratory. This daytime sleep was polysomnographically recorded and scored by professionals blind to the study design. Only seven out of 16 participants had REM sleep; participants without REM sleep had a significantly slower decline of both SCR and neural activity of the laterodorsal tegmentum in response to electrical shocks during conditioning. At recall of fear extinction, participants with preceding REM sleep had a reduced SCR and stronger activation of the left ventromedial prefrontal cortex and bilateral lingual gyrus in response to the extinguished stimulus than participants lacking REM sleep. This study indicates that trait-like differences in shock reactivity/habituation (mediated by the brainstem) are predictive of REM sleep disruption, which in turn is associated with impaired consolidation of extinction (mediated by the ventromedial prefrontal cortex). These findings help understand the neurobiological basis and the temporal sequence of the relationship between shock exposure, disturbed sleep and impaired consolidation of extinction, as observed in PTSD.

Macroscopic brain architecture changes and white matter pathology in acromegaly: a clinicoradiological study.

Although long-term exposure of the brain to increased GH/IGF-1 likely influences cerebral functions, no in vivo studies have been directed towards changes of the brain structure in acromegaly. Here, we used high resolution magnetic resonance images to compare volumes of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) of forty-four patients with acromegaly to an age and gender matched, healthy control group (n = 44). In addition, white matter lesions (WMLs) were quantified and graded. Patients exhibited larger GM (+3.7% compared with controls, P = 0.018) and WM volumes (+5.1%, P = 0.035) at the expense of CSF. Differences of WML counts between patients and controls were subtle, however, showing more patients in the 21-40 lesions category (P = 0.044). In conclusion, this MRI study provides first evidence that acromegalic patients exhibit disturbances of the macroscopic brain tissue architecture. Furthermore, acromegalic patients may have an increased risk of neurovascular pathology, likely due to secondary metabolic and vascular comorbidities.

Independent component analysis applied to pharmacological magnetic resonance imaging (phMRI): new insights into the functional networks underlying panic attacks as induced by CCK-4.

Pharmacological magnetic resonance imaging (phMRI) is a method to study effects of psychopharmacological agents on neural activation. Changes of the blood oxygen level dependent (BOLD), the basis of functional MRI (fMRI), are typically obtained at relatively high sampling frequencies. This has more recently been exploited in the field of fMRI by applying independent component analysis (ICA), an explorative data analysis method decomposing activation into distinct neural networks. While already successfully used to investigate resting network and task-induced activity, its use in phMRI is new. Further extension of this method to tensorial probabilistic ICA (tensor PICA) allows to group similar brain activation across the anatomical, temporal, subject or session domain. This approach is useful for pharmacological experiments when no pharmacokinetic model exists. We exemplify this method using data from a placebo-controlled cholecystokinine-4 (CCK-4) injection experiment performed on 16 neuropsychiatrically and medically healthy males (age 25.6 +/- 4.2 years). Tensor PICA identified strong increases in activity in 12 networks. Comparison with results gained from the standard approach (voxelwise regression analysis) revealed good reproduction of areas previously associated with CCK-4 action, such as the anterior cingulate, orbitofrontal cortex, cerebellum, temporolateral, left parietal and insular areas, striatum, and precuneus. Several other components such as the dorsal anterior cingulate and medial prefrontal cortex were identified, suggesting higher sensitivity of the method. Exploration of the time courses of each activated network revealed differences, that might be lost when a fixed time course is modeled, e. g. neuronal responses to an acoustic warning signal prior to injection. Comparison of placebo and CCK-4 runs further showed that a proportion of networks are newly elicited by CCK-4 whereas other components are significantly active in the placebo conditions but further enhanced by CCK-4. In conclusion, group ICA is a promising tool for phMRI studies that allows quantifying and visualizing the modulation of neural networks by pharmacological interventions.

Pituitary imaging abnormalities in patients with and without hypopituitarism after traumatic brain injury.

Recent evidence suggests that patients with traumatic brain injury (TBI) are at substantial risk of hypopituitarism. The pathomechanisms, however, are not completely understood yet. Little is known about the association of morphological changes in the sella region with pituitary function in TBI. In this study, we assessed morphological abnormalities of the sella region in patients with TBI and their relation to endocrine function. We studied magnetic resonance (MR) or computed tomography (CT) scans of 22 patients with TBI [17 men, 5 women, age (mean+/-SD) 43.5+/-10.6 yr, time after trauma 17.4 +/-15.0 yr]. Of these, 15 patients had some degree of hypopituitarism. We found abnormalities of the sella region in 80% of the patients with hypopituitarism and 29% of those without hypopituitarism (Fisher's exact test, p=0.032). The most common abnormality was loss of volume or empty sella, followed by native signal inhomogeneities, perfusion deficit, and lack of neurohypophyseal signal. Our results indicate that pituitary imaging abnormalities are more common in TBI patients with hypopituitarism than those without. Both immediate trauma-induced pathology as necrosis and hemorrhage as well as multifactorial mid- to long-term changes may underlie these abnormalities.

Assessing DTI data quality using bootstrap analysis.

Diffusion tensor imaging (DTI) is an established method for characterizing and quantifying ultrastructural brain tissue properties. However, DTI-derived variables are affected by various sources of signal uncertainty. The goal of this study was to establish an objective quality measure for DTI based on the nonparametric bootstrap methodology. The confidence intervals (CIs) of white matter (WM) fractional anisotropy (FA) and Clinear were determined by bootstrap analysis and submitted to histogram analysis. The effects of artificial noising and edge-preserving smoothing, as well as enhanced and reduced motion were studied in healthy volunteers. Gender and age effects on data quality as potential confounds in group comparison studies were analyzed. Additional noising showed a detrimental effect on the mean, peak position, and height of the respective CIs at 10% of the original background noise. Inverse changes reflected data improvement induced by edge-preserving smoothing. Motion-dependent impairment was also well depicted by bootstrap-derived parameters. Moreover, there was a significant gender effect, with females displaying less dispersion (attributable to elevated SNR). In conclusion, the bootstrap procedure is a useful tool for assessing DTI data quality. It is sensitive to both noise and motion effects, and may help to exclude confounding effects in group comparisons.