Sex differences in trajectories of cortical development in autistic children from 2-13 years of age.

Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2-13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.

An automated, geometry-based method for hippocampal shape and thickness analysis.

The hippocampus is one of the most studied neuroanatomical structures due to its involvement in attention, learning, and memory as well as its atrophy in ageing, neurological, and psychiatric diseases. Hippocampal shape changes, however, are complex and cannot be fully characterized by a single summary metric such as hippocampal volume as determined from MR images. In this work, we propose an automated, geometry-based approach for the unfolding, point-wise correspondence, and local analysis of hippocampal shape features such as thickness and curvature. Starting from an automated segmentation of hippocampal subfields, we create a 3D tetrahedral mesh model as well as a 3D intrinsic coordinate system of the hippocampal body. From this coordinate system, we derive local curvature and thickness estimates as well as a 2D sheet for hippocampal unfolding. We evaluate the performance of our algorithm with a series of experiments to quantify neurodegenerative changes in Mild Cognitive Impairment and Alzheimer's disease dementia. We find that hippocampal thickness estimates detect known differences between clinical groups and can determine the location of these effects on the hippocampal sheet. Further, thickness estimates improve classification of clinical groups and cognitively unimpaired controls when added as an additional predictor. Comparable results are obtained with different datasets and segmentation algorithms. Taken together, we replicate canonical findings on hippocampal volume/shape changes in dementia, extend them by gaining insight into their spatial localization on the hippocampal sheet, and provide additional, complementary information beyond traditional measures. We provide a new set of sensitive processing and analysis tools for the analysis of hippocampal geometry that allows comparisons across studies without relying on image registration or requiring manual intervention.

A novel geometry-based analysis of hippocampal morphometry in mesial temporal lobe epilepsy.

Hippocampal volumetry is an essential tool in researching and diagnosing mesial temporal lobe epilepsy (mTLE). However, it has a limited ability to detect subtle alterations in hippocampal morphometry. Here, we establish and apply a novel geometry-based tool that enables point-wise morphometric analysis based on an intrinsic coordinate system of the hippocampus. We hypothesized that this point-wise analysis uncovers structural alterations not measurable by volumetry, but associated with histological underpinnings and the neuropsychological profile of mTLE. We conducted a retrospective study in 204 individuals with mTLE and 57 age- and gender-matched healthy subjects. FreeSurfer-based segmentations of hippocampal subfields in 3T-MRI were subjected to a geometry-based analysis that resulted in a coordinate system of the hippocampal mid-surface and allowed for point-wise measurements of hippocampal thickness and other features. Using point-wise analysis, we found significantly lower thickness and higher FLAIR signal intensity in the entire affected hippocampus of individuals with hippocampal sclerosis (HS-mTLE). In the contralateral hippocampus of HS-mTLE and the affected hippocampus of MRI-negative mTLE, we observed significantly lower thickness in the presubiculum. Impaired verbal memory was associated with lower thickness in the left presubiculum. In HS-mTLE histological subtype 3, we observed higher curvature than in subtypes 1 and 2 (all p < .05). These findings could not be observed using conventional volumetry (Bonferroni-corrected p < .05). We show that point-wise measures of hippocampal morphometry can uncover structural alterations not measurable by volumetry while also reflecting histological underpinnings and verbal memory. This substantiates the prospect of their clinical application.

Shape description and volumetry of hippocampus and amygdala in temporal lobe epilepsy - A beneficial combination with a clinical perspective.

Shape-based markers have entered the field of morphometric neuroimaging analysis as a second mainstay alongside conventional volumetric approaches. We aimed to assess the added value of shape description for the analysis of lesional and autoimmune temporal lobe epilepsy (TLE) focusing on hippocampus and amygdala. We retrospectively investigated MRI and clinical data from 65 patients with lesional TLE (hippocampal sclerosis (HS) and astrogliosis) and from 62 patients with limbic encephalitis (LE) with serologically proven autoantibodies. Surface reconstruction and volumetric segmentation were performed with FreeSurfer. For the shape analysis, we used BrainPrint, a tool that utilizes eigenvalues of the Laplace-Beltrami operator on triangular meshes to calculate intra-subject asymmetry. Psychometric tests of memory performance were ascertained, to evaluate clinical relevance of the shape descriptor. The potential benefit of shape in addition to volumetric information for classification was assessed by five-fold repeated cross validation and logistic regression. For the LE group, the best performing classification model consisted of a combination of volume and shape asymmetry (mean AUC = 0.728), the logistic regression model was significantly improved considering both modalities instead of just volume asymmetry. For lesional TLE, the best model only considered volumetric information (mean AUC = 0.867). Shape asymmetry of the hippocampus was largely associated with verbal memory performance only in LE patients (OR = 1.07, p = 0.02). For lesional TLE, shape description is robust, but redundant when compared to volumetric approaches. For LE, in contrast, shape asymmetry as a complementary modality significantly improves the detection of subtle morphometric changes and is further associated with memory performance, which underscores the clinical relevance of shape asymmetry as a novel imaging biomarker.

Automated olfactory bulb segmentation on high resolutional T2-weighted MRI.

The neuroimage analysis community has neglected the automated segmentation of the olfactory bulb (OB) despite its crucial role in olfactory function. The lack of an automatic processing method for the OB can be explained by its challenging properties (small size, location, and poor visibility on traditional MRI scans). Nonetheless, recent advances in MRI acquisition techniques and resolution have allowed raters to generate more reliable manual annotations. Furthermore, the high accuracy of deep learning methods for solving semantic segmentation problems provides us with an option to reliably assess even small structures. In this work, we introduce a novel, fast, and fully automated deep learning pipeline to accurately segment OB tissue on sub-millimeter T2-weighted (T2w) whole-brain MR images. To this end, we designed a three-stage pipeline: (1) Localization of a region containing both OBs using FastSurferCNN, (2) Segmentation of OB tissue within the localized region through four independent AttFastSurferCNN - a novel deep learning architecture with a self-attention mechanism to improve modeling of contextual information, and (3) Ensemble of the predicted label maps. For this work, both OBs were manually annotated in a total of 620 T2w images for training (n=357) and testing. The OB pipeline exhibits high performance in terms of boundary delineation, OB localization, and volume estimation across a wide range of ages in 203 participants of the Rhineland Study (Dice Score (Dice): 0.852, Volume Similarity (VS): 0.910, and Average Hausdorff Distance (AVD): 0.215 mm). Moreover, it also generalizes to scans of an independent dataset never encountered during training, the Human Connectome Project (HCP), with different acquisition parameters and demographics, evaluated in 30 cases at the native 0.7 mm HCP resolution (Dice: 0.738, VS: 0.790, and AVD: 0.340 mm), and the default 0.8 mm pipeline resolution (Dice: 0.782, VS: 0.858, and AVD: 0.268 mm). We extensively validated our pipeline not only with respect to segmentation accuracy but also to known OB volume effects, where it can sensitively replicate age effects (ß=-0.232, p<.01). Furthermore, our method can analyze a 3D volume in less than a minute (GPU) in an end-to-end fashion, providing a validated, efficient, and scalable solution for automatically assessing OB volumes.

Insulin resistance accounts for metabolic syndrome-related alterations in brain structure.

Metabolic syndrome (MetS) is a major public health burden worldwide and associated with brain abnormalities. Although insulin resistance is considered a pivotal feature of MetS, its role in the pathogenesis of MetS-related brain alterations in the general population is unclear. Therefore, in 973 participants (mean age 52.5 years) of the population-based Rhineland Study, we assessed brain morphology in relation to MetS and insulin resistance, and evaluated to what extent the pattern of structural brain changes seen in MetS overlap with those associated with insulin resistance. Cortical reconstruction and volumetric segmentation were obtained from high-resolution brain images at 3 Tesla using FreeSurfer. The relations between metabolic measures and brain structure were assessed through (generalized) linear models. Both MetS and insulin resistance were associated with smaller cortical gray matter volume and thickness, but not with white matter or subcortical gray matter volume. Age- and sex-adjusted vertex-based brain morphometry demonstrated that MetS and insulin resistance were related to cortical thinning in a similar spatial pattern. Importantly, no independent effect of MetS on cortical gray matter was observed beyond the effect of insulin resistance. Our findings suggest that addressing insulin resistance is critical in the prevention of MetS-related brain changes in later life.

FastSurfer - A fast and accurate deep learning based neuroimaging pipeline.

Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands or tens of thousands of individuals. In this work we propose a fast and accurate deep learning based neuroimaging pipeline for the automated processing of structural human brain MRI scans, replicating FreeSurfer's anatomical segmentation including surface reconstruction and cortical parcellation. To this end, we introduce an advanced deep learning architecture capable of whole-brain segmentation into 95 classes. The network architecture incorporates local and global competition via competitive dense blocks and competitive skip pathways, as well as multi-slice information aggregation that specifically tailor network performance towards accurate segmentation of both cortical and subcortical structures. Further, we perform fast cortical surface reconstruction and thickness analysis by introducing a spectral spherical embedding and by directly mapping the cortical labels from the image to the surface. This approach provides a full FreeSurfer alternative for volumetric analysis (in under 1 â€‹min) and surface-based thickness analysis (within only around 1 â€‹h runtime). For sustainability of this approach we perform extensive validation: we assert high segmentation accuracy on several unseen datasets, measure generalizability and demonstrate increased test-retest reliability, and high sensitivity to group differences in dementia.

Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease.

Biomarkers useful for the predementia stages of Alzheimer's disease are needed. Electroencephalography and magnetoencephalography (MEG) are expected to provide potential biomarker candidates for evaluating the predementia stages of Alzheimer's disease. However, the physiological relevance of EEG/MEG signal changes and their role in pathophysiological processes such as amyloid-ß deposition and neurodegeneration need to be elucidated. We evaluated 28 individuals with mild cognitive impairment and 38 cognitively normal individuals, all of whom were further classified into amyloid-ß-positive mild cognitive impairment (n = 17, mean age 74.7 ± 5.4 years, nine males), amyloid-ß-negative mild cognitive impairment (n = 11, mean age 73.8 ± 8.8 years, eight males), amyloid-ß-positive cognitively normal (n = 13, mean age 71.8 ± 4.4 years, seven males), and amyloid-ß-negative cognitively normal (n = 25, mean age 72.5 ± 3.4 years, 11 males) individuals using Pittsburgh compound B-PET. We measured resting state MEG for 5 min with the eyes closed, and investigated regional spectral patterns of MEG signals using atlas-based region of interest analysis. Then, the relevance of the regional spectral patterns and their associations with pathophysiological backgrounds were analysed by integrating information from Pittsburgh compound B-PET, fluorodeoxyglucose-PET, structural MRI, and cognitive tests. The results demonstrated that regional spectral patterns of resting state activity could be separated into several types of MEG signatures as follows: (i) the effects of amyloid-ß deposition were expressed as the alpha band power augmentation in medial frontal areas; (ii) the delta band power increase in the same region was associated with disease progression within the Alzheimer's disease continuum and was correlated with entorhinal atrophy and an Alzheimer's disease-like regional decrease in glucose metabolism; and (iii) the global theta power augmentation, which was previously considered to be an Alzheimer's disease-related EEG/MEG signature, was associated with general cognitive decline and hippocampal atrophy, but was not specific to Alzheimer's disease because these changes could be observed in the absence of amyloid-ß deposition. The results suggest that these MEG signatures may be useful as unique biomarkers for the predementia stages of Alzheimer's disease.

Impact of FAAH genetic variation on fronto-amygdala function during emotional processing.

Recent translational studies identified a common endocannabinoid polymorphism, FAAH C385A, in the gene for the fatty acid amide hydrolase (FAAH). This polymorphism alters endocannabinoid anandamide levels, which are known to be involved in the fronto-amygdala circuitry implicated in mood regulation and anxiety-like behaviors. While it has been shown that the variant that selectively enhances fronto-amygdala connectivity at rest is associated with decreased anxiety-like behaviors, no study so far has investigated whether this finding of FAAH-related differential plasticity extends to task-related differential functional expression and regulation during negative emotional processing. Using an imaging genetics approach, this study aimed to replicate and extend prior findings by examining functional activity and task-related connectivity in fronto-amygdala regions during emotion reactivity and emotional down-regulation of negative affect. Therefore, 48 healthy young adults underwent a functional MRI resting state measurement, completed an emotion regulation paradigm and provided self-reports on anxiety and use of emotion regulation strategies. In line with previous studies, preliminary evidence suggests that A-allele carriers demonstrate stronger fronto-amygdala connectivity during rest. In addition, exploratory whole-brain analyses indicate differential functional activity of A-allele carriers during emotion reactivity and emotion regulation. There were no associations with anxiety-related self-reports and use of emotional regulation strategies. Further research using larger samples and polygenic approaches is indicated to clarify the precise role and its underlying mechanisms in emotion processing.

Systemic and Ocular Determinants of Peripapillary Retinal Nerve Fiber Layer Thickness Measurements in the European Eye Epidemiology (E3) Population.

PURPOSE: To investigate systemic and ocular determinants of peripapillary retinal nerve fiber layer thickness (pRNFLT) in the European population. DESIGN: Cross-sectional meta-analysis. PARTICIPANTS: A total of 16 084 European adults from 8 cohort studies (mean age range, 56.9±12.3-82.1±4.2 years) of the European Eye Epidemiology (E3) consortium. METHODS: We examined associations with pRNFLT measured by spectral-domain OCT in each study using multivariable linear regression and pooled results using random effects meta-analysis. MAIN OUTCOME MEASURES: Determinants of pRNFLT. RESULTS: Mean pRNFLT ranged from 86.8±21.4 µm in the Rotterdam Study I to 104.7±12.5 µm in the Rotterdam Study III. We found the following factors to be associated with reduced pRNFLT: Older age (ß = -0.38 µm/year; 95% confidence interval [CI], -0.57 to -0.18), higher intraocular pressure (IOP) (ß = -0.36 µm/mmHg; 95% CI, -0.56 to -0.15), visual impairment (ß = -5.50 µm; 95% CI, -9.37 to -1.64), and history of systemic hypertension (ß = -0.54 µm; 95% CI, -1.01 to -0.07) and stroke (ß = -1.94 µm; 95% CI, -3.17 to -0.72). A suggestive, albeit nonsignificant, association was observed for dementia (ß = -3.11 µm; 95% CI, -6.22 to 0.01). Higher pRNFLT was associated with more hyperopic spherical equivalent (ß = 1.39 µm/diopter; 95% CI, 1.19-1.59) and smoking (ß = 1.53 µm; 95% CI, 1.00-2.06 for current smokers compared with never-smokers). CONCLUSIONS: In addition to previously described determinants such as age and refraction, we found that systemic vascular and neurovascular diseases were associated with reduced pRNFLT. These may be of clinical relevance, especially in glaucoma monitoring of patients with newly occurring vascular comorbidities.

Transcranial electrical stimulation of the occipital cortex during visual perception modifies the magnitude of BOLD activity: A combined tES-fMRI approach.

The aim of this study was to investigate if the blood oxygenation level-dependent (BOLD) changes in the visual cortex can be used as biomarkers reflecting the online and offline effects of transcranial electrical stimulation (tES). Anodal transcranial direct current stimulation (tDCS) and 10Hz transcranial alternating current stimulation (tACS) were applied for 10min duration over the occipital cortex of healthy adults during the presentation of different visual stimuli, using a crossover, double-blinded design. Control experiments were also performed, in which sham stimulation as well as another electrode montage were used. Anodal tDCS over the visual cortex induced a small but significant further increase in BOLD response evoked by a visual stimulus; however, no aftereffect was observed. Ten hertz of tACS did not result in an online effect, but in a widespread offline BOLD decrease over the occipital, temporal, and frontal areas. These findings demonstrate that tES during visual perception affects the neuronal metabolism, which can be detected with functional magnetic resonance imaging (fMRI).

Additive gene-environment effects on hippocampal structure in healthy humans.

Hippocampal volume loss has been related to chronic stress as well as genetic factors. Although genetic and environmental variables affecting hippocampal volume have extensively been studied and related to mental illness, limited evidence is available with respect to G × E interactions on hippocampal volume. The present MRI study investigated interaction effects on hippocampal volume between three well-studied functional genetic variants (COMT Val158Met, BDNF Val66Met, 5-HTTLPR) associated with hippocampal volume and a measure of environmental adversity (life events questionnaire) in a large sample of healthy humans (n = 153). All three variants showed significant interactions with environmental adversity with respect to hippocampal volume. Observed effects were additive by nature and driven by both recent as well as early life events. A consecutive analysis of hippocampal subfields revealed a spatially distinct profile for each genetic variant suggesting a specific role of 5-HTTLPR for the subiculum, BDNF Val66Met for CA4/dentate gyrus, and COMT Val158Met for CA2/3 volume changes. The present study underscores the importance of G × E interactions as determinants of hippocampal volume, which is crucial for the neurobiological understanding of stress-related conditions, such as mood disorders or post-traumatic stress disorder (PTSD).

Association Between Accelerometer-Derived Physical Activity Measurements and Brain Structure: A Population-Based Cohort Study.

BACKGROUND AND OBJECTIVES: While there is growing evidence that physical activity promotes neuronal health, studies examining the relation between physical activity and brain morphology remain inconclusive. We therefore examined whether objectively quantified physical activity is related to brain volume, cortical thickness, and gray matter density in a large cohort study. In addition, we assessed molecular pathways that may underlie the effects of physical activity on brain morphology. METHODS: We used cross-sectional baseline data from 2,550 eligible participants (57.6% women; mean age: 54.7 years, range: 30-94 years) of a prospective cohort study. Physical activity dose (metabolic equivalent hours and step counts) and intensity (sedentary and light-intensity and moderate-to-vigorous intensity activities) were recorded with accelerometers. Brain volumetric, gray matter density, and cortical thickness measures were obtained from 3T MRI scans using FreeSurfer and Statistical Parametric Mapping. The relation of physical activity (independent variable) and brain structure (outcome) was examined with polynomial multivariable regression, while adjusting for age, sex, intracranial volume, education, and smoking. Using gene expression profiles from the Allen Brain Atlas, we extracted molecular signatures associated with the effects of physical activity on brain morphology. RESULTS: Physical activity dose and intensity were independently associated with larger brain volumes, gray matter density, and cortical thickness of several brain regions. The effects of physical activity on brain volume were most pronounced at low physical activity quantities and differed between men and women and across age. For example, more time spent in moderate-to-vigorous intensity activities was associated with greater total gray matter volume, but the relation leveled off with more activity (standardized ß [95% CIs]: 1.37 [0.35-2.39] and -0.70 [-1.25 to -0.15] for the linear and quadratic terms, respectively). The strongest effects of physical activity were observed in motor regions and cortical regions enriched for genes involved in mitochondrial respiration. DISCUSSION: Our findings suggest that physical activity benefits brain health, with the strongest effects in motor regions and regions with a high oxidative demand. While young adults may particularly profit from additional high-intensity activities, older adults may already benefit from light-intensity activities. Physical activity and reduced sedentary time may be critical in the prevention of age-associated brain atrophy and neurodegenerative diseases.

Should we keep some distance from distancing? Regulatory and post-regulatory effects of emotion downregulation.

Emotion regulation is an indispensable part of mental health and adaptive behavior. Research into emotion regulation processes has largely focused on the concurrent effects of volitional emotion regulation. However, there is scarce evidence considering post-regulatory effects with regard to neural mechanisms and emotional experiences. Therefore, we compared concurrent effects of cognitive emotion regulation with effects at different (immediate, short- and long-term) time intervals. In an fMRI study with N = 46 (N = 30 at re-exposure) young healthy adults, we compared neuronal responses to negative and neutral pictures while participants had to distance themselves from or to actively permit emotions in response to these pictures. We investigated the temporal dynamics of activation changes related to regulation in cognitive control brain networks as well as in the amygdala during stimulation (concurrent effects, timepoint 1) and post-stimulation (immediate, timepoint 2), as well as during re-exposure with the same pictures after short (10 minutes, timepoint 3) and long (1 week, timepoint 4) time intervals. At timepoint 1, negative pictures (versus neutral pictures) elicited a strong response in regions of affective processing, including the amygdala. Distancing (as compared to permit) led to a decrease of this response, and to an increase of activation in the right middle frontal and inferior parietal cortex. We observed an interaction effect of time (stimulation vs. post-stimulation) and regulation (distance vs. permit), indicating a partial reversal of regulation effects during the post-stimulation phase (timepoint 2). Similarly, after 10 minutes (timepoint 3) and after 1 week (timepoint 4), activation in the amygdala was higher during pictures that participants were previously instructed to distance from as compared to permit. These results show that the temporal dynamics are highly variable both within experimental trials and across brain regions. This can even take the form of paradoxical aftereffects at immediate and persistent effects at prolonged time scales.

A Functional MRI Paradigm for Efficient Mapping of Memory Encoding Across Sensory Conditions.

We introduce a new and time-efficient memory-encoding paradigm for functional magnetic resonance imaging (fMRI). This paradigm is optimized for mapping multiple contrasts using a mixed design, using auditory (environmental/vocal) and visual (scene/face) stimuli. We demonstrate that the paradigm evokes robust neuronal activity in typical sensory and memory networks. We were able to detect auditory and visual sensory-specific encoding activities in auditory and visual cortices. Also, we detected stimulus-selective activation in environmental-, voice-, scene-, and face-selective brain regions (parahippocampal place and fusiform face area). A subsequent recognition task allowed the detection of sensory-specific encoding success activity (ESA) in both auditory and visual cortices, as well as sensory-unspecific positive ESA in the hippocampus. Further, sensory-unspecific negative ESA was observed in the precuneus. Among others, the parallel mixed design enabled sustained and transient activity comparison in contrast to rest blocks. Sustained and transient activations showed great overlap in most sensory brain regions, whereas several regions, typically associated with the default-mode network, showed transient rather than sustained deactivation. We also show that the use of a parallel mixed model had relatively little influence on positive or negative ESA. Together, these results demonstrate a feasible, versatile, and brief memory-encoding task, which includes multiple sensory stimuli to guarantee a comprehensive measurement. This task is especially suitable for large-scale clinical or population studies, which aim to test task-evoked sensory-specific and sensory-unspecific memory-encoding performance as well as broad sensory activity across the life span within a very limited time frame.

Genetic variation of serotonin receptor function affects prepulse inhibition of the startle.

Prepulse inhibition (PPI) is the attenuation of the startle response towards an instantaneous and intense stimulus when preceded by a weaker non-startling stimulus. Deficits in this sensorimotor gating process have been associated with the pathophysiology of schizophrenia and other psychiatric disorders. Among the neurotransmitters involved in PPI modulation, serotonin (5-HT) has so far received comparably little attention. While a recent pharmacological study suggests an important role of different 5-HT receptor (5-HTR) subtypes in PPI modulation, the mechanisms by which 5-HTR impact on PPI remain to be further elucidated. Therefore, we employed a molecular genetic approach in order to examine whether PPI is associated with two functional 5-HTR gene polymorphisms, 5-HTR1A C-1019G and 5-HTR2A T102C. In a sample of 81 healthy volunteers, we found no significant main effects of the polymorphisms, but a significant interaction effect on PPI at short (50 ms) and mid-long (150 ms) pulse-prepulse intervals. The presence of the 5-HTR2A T allele (reported to result in higher 5-HTR2A expression) led to attenuated PPI only in the absence of the 5-HTR1A G allele (reported to result in reduced 5-HTR1A autoreceptor expression). Our results may indicate that a higher 5-HTR2A expression together with a reduced 5-HTR1A autoreceptor expression and consequently, elevated firing rates of serotonergic neurons results in elevated 5-HTR2A activation by serotonin which could potently attenuate PPI. While further research into the molecular mechanisms underlying this interaction is needed, our results underscore the role of 5-HTR in PPI modulation and further implicate the 5-HTR1A G-1019C and the 5-HTR2A T102C polymorphisms in the pathophysiology of schizophrenia.

Cognitive emotion regulation and personality: an analysis of individual differences in the neural and behavioral correlates of successful reappraisal.

A common and mostly effective emotion regulation strategy is reappraisal. During reappraisal, activity in cognitive control brain regions increases and activity in brain regions associated with emotion responding (e.g., the amygdala) diminishes. Immediately after reappraisal, it has been observed that activity in the amygdala increases again, which might reflect a paradoxical aftereffect. While there is extensive empirical evidence for these neural correlates of emotion regulation, only few studies targeted the association with individual differences in personality traits. The aim of this study is to investigate these associations more thoroughly. Seventy-six healthy participants completed measures of broad personality traits (Big Five, Positive and Negative Affect) as well as of more narrow traits (habitual use of emotion regulation) and performed an experimental fMRI reappraisal task. Participants were instructed to either permit their emotions or to detach themselves from the presented negative and neutral pictures. After each picture, a relaxation period was included. Reappraisal success was determined by arousal ratings and activity in the amygdala. During reappraisal, we found activation in the prefrontal cortex and deactivation in the left amygdala. During the relaxation period, an immediate aftereffect was found in occipital regions and marginally in the amygdala. Neither personality traits nor habitual use of emotion regulation predicted reappraisal success or the magnitude of the aftereffect. We replicated typical activation and deactivation patterns during intentional emotion regulation and partially replicated the immediate aftereffect in the amygdala. However, there was no association between personality traits and emotion regulation success.

Gray Matter Alterations Associated With Dissociation in Female Survivors of Childhood Trauma.

OBJECTIVE: Across various axis-1 disorders, the severity of dissociative symptoms is significantly related to a history of childhood traumatization. Thus, the question arises if coping with childhood trauma leads to neural adaptations that enhance the frequency of dissociative processing during adulthood. The aim of the two reported studies therefore was to identify and replicate gray matter alterations associated with dissociation. METHODS AND RESULTS: In a first study, whole-brain MRI data were acquired for 22 female in-patients with trauma-spectrum disorders and a history of severe childhood trauma. Voxel-based morphometry (VBM) was carried out to test for significant correlations between dissociation (depersonalization/derealization) severity and gray matter volume. Dissociation severity was positively associated with volume in the left angular gyrus. This result was diagnosis-invariant. The replication study involved 26 female in-patients with trauma-spectrum disorders and 25 healthy controls. No significant association between dissociation severity and brain volume in a left angular gyrus region of interest located at the peak identified in study 1 was identified and no significant group difference in this region could be established. CONCLUSION: The angular gyrus has previously been implicated in the processing of agency and vestibular integration as well as dissociative processing. The current attempt at a direct replication of brain volume alterations however, failed. The data thus only partially support the notion that dissociative processing is associated trans-diagnostically with structural brain alterations in the left angular gyrus and independent replication in a larger patient sample is essential.

The real-life costs of emotion regulation in anorexia nervosa: a combined ecological momentary assessment and fMRI study.

Regulation of emotions is necessary for successful attainment of short-term and long-term goals. However, over-regulation may also have its costs. In anorexia nervosa (AN), forgoing food intake despite emaciation and endocrine signals that promote eating is an example of "too much" self-control. Here we investigated whether voluntary emotion regulation in AN patients comes with associated disorder-relevant costs. Thirty-five patients with acute AN and thirty-five age-matched healthy controls (HCs) performed an established emotion regulation paradigm during functional magnetic resonance imaging after an overnight fast. The task required reducing emotions induced by positively valenced pictures via distancing. We calculated a neural regulation score from responses recorded in a reward-related brain region of interest (ventral striatum; VS) by subtracting activation measured on "positive distance" trials from that elicited under the "positive watch" (baseline) condition. Complementing the imaging data, we used ecological momentary assessment (EMA) to probe disorder-related rumination and affect six times/day for 2 weeks following the scanning session. The neural regulation score indicating reduced VS activation during emotion regulation was used as a predictor in hierarchical linear models with EMA measures as outcomes. No group differences in neural activity were found for the main contrasts of the task. However, regulation of VS activity was associated with increased body-related rumination and increased negative affect in AN, but not in HC. In line with this finding, correlational analysis with longitudinal BMI measurements revealed a link between greater VS regulation and poorer treatment outcome after 60 and 90 days. Together, these results identify a neural correlate of altered emotion regulation in AN, which seems to be detrimental to psychological well-being and may interfere with recovery.

Early functional network alterations in asymptomatic elders at risk for Alzheimer's disease.

Amyloid-ß (Aß) deposition is known to starts decades before the onset of clinical symptoms of Alzheimer's disease (AD), however, the detailed pathophysiological processes underlying this preclinical period are not well understood. This study aimed to investigate functional network alterations in cognitively intact elderly individuals at risk for AD, and assessed the association between these network alterations and changes in Aß deposition, glucose metabolism, and brain structure. Forty-five cognitively normal elderly subjects, who were classified into Aß-positive (CN+) and Aß-negative (CN-) groups using 11C-Pittsburgh compound B PET, underwent resting state magnetoencephalography measurements, 18F-fluorodeoxyglucose PET (FDG-PET) and structural MRI. Results demonstrated that in the CN+ group, functional connectivity (FC) within the precuneus was significantly decreased, whereas it was significantly enhanced between the precuneus and the bilateral inferior parietal lobules in the low-frequency bands (theta and delta). These changes were suggested to be associated with local cerebral Aß deposition. Most of Aß+ individuals in this study did not show any metabolic or anatomical changes, and there were no significant correlations between FC values and FDG-PET or MRI volumetry data. These results demonstrate that functional network alterations, which occur in association with Aß deposition, are detectable using magnetoencephalography before metabolic and anatomical changes are seen.