Structural Neuroimaging of Anorexia Nervosa: Future Directions in the Quest for Mechanisms Underlying Dynamic Alterations.

Anorexia nervosa (AN) is a serious eating disorder characterized by self-starvation and extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual brain scans, and AN may be a valuable model disorder to study structural neuroplasticity. Structural magnetic resonance imaging studies have found reduced gray matter volume and cortical thinning in acutely underweight patients to normalize following successful treatment. However, some well-controlled studies have found regionally greater gray matter and persistence of structural alterations following long-term recovery. Findings from diffusion tensor imaging studies of white matter integrity and connectivity are also inconsistent. Furthermore, despite the severity of AN, the number of existing structural neuroimaging studies is still relatively low, and our knowledge of the underlying cellular and molecular mechanisms for macrostructural brain changes is rudimentary. We critically review the current state of structural neuroimaging in AN and discuss the potential neurobiological basis of structural brain alterations in the disorder, highlighting impediments to progress, recent developments, and promising future directions. In particular, we argue for the utility of more standardized data collection, adopting a connectomics approach to understanding brain network architecture, employing advanced magnetic resonance imaging methods that quantify biomarkers of brain tissue microstructure, integrating data from multiple imaging modalities, strategic longitudinal observation during weight restoration, and large-scale data pooling. Our overarching objective is to motivate carefully controlled research of brain structure in eating disorders, which will ultimately help predict therapeutic response and improve treatment

Atrial-Selective Approaches for the Treatment of Atrial Fibrillation

Atrial-selective pharmacologic approaches represent promising novel therapeutic options for the treatment of atrial fibrillation (AF). Medical treatment for AF is still more widely applied than interventional therapies but is hampered by several important weaknesses. Besides limited clinical efficacy (cardioversion success and sinus-rhythm maintenance), side effects like ventricular proarrhythmia and negative inotropy are important limitations to present class I and III drug therapy. Although no statistically significant detrimental survival consequences have been documented in trials, constitutional adverse effects might also limit applicability. Cardiac targets for novel atrial-selective antiarrhythmic compounds have been identified, and a large-scale search for safe and effective medications has begun. Several ionic currents (IKACh, IKur) and connexins (Cx-40) are potential targets, because atrial-selective expression makes them attractive in terms of reduced ventricular side-effect liability. Data on most agents are still experimental, but some clinical findings are available. Atrial fibrillation generates a specifically remodeled atrial milieu for which other therapeutic interventions might be effective. Some drugs show frequency-dependent action, whereas others target structurally remodeled atria. This review focuses on potential atrial-selective compounds, summarizing mechanisms of action in vitro and in vivo. It also mentions favorable interventions on the milieu in terms of conventional (such as antifibrotic effects of angiotensin-system antagonism) and innovative gene-therapy approaches that might add to future AF therapeutic options

„Königreich des Hochdeutschen“ – Die Tradierung des Hochdeutsch-Mythos in Hannover

There is a myth that says that the best standard German nationwide is spoken in Hanover. This article deals with the transmission of this myth in public discourse within the city of Hanover itself. The textual testimonies found (for example, on homepages, in literary works, or in advertising) were categorized according to different groups of people as well as economic and governmental institutions, and grouped into narrative patterns. This captured the knowledge and attitudes regarding the topos and revealed dominant thinking patterns. The results show that the myth is strongly anchored in the Hanoverian public in a variety of ways: sometimes it is propagated as fact, at other times it is toned down as hearsay; some perceive it as a trademark of Hanover, others view it critically against the background of the former city dialect (“Hannöversch”)

Human-robot collaborative task planning using anticipatory brain responses

Human-robot interaction (HRI) describes scenarios in which both human and robot work as partners, sharing the same environment or complementing each other on a joint task. HRI is characterized by the need for high adaptability and flexibility of robotic systems toward their human interaction partners. One of the major challenges in HRI is task planning with dynamic subtask assignment, which is particularly challenging when subtask choices of the human are not readily accessible by the robot. In the present work, we explore the feasibility of using electroencephalogram (EEG) based neuro-cognitive measures for online robot learning of dynamic subtask assignment. To this end, we demonstrate in an experimental human subject study, featuring a joint HRI task with a UR10 robotic manipulator, the presence of EEG measures indicative of a human partner anticipating a takeover situation from human to robot or vice-versa. The present work further proposes a reinforcement learning based algorithm employing these measures as a neuronal feedback signal from the human to the robot for dynamic learning of subtask-assignment. The efficacy of this algorithm is validated in a simulation-based study. The simulation results reveal that even with relatively low decoding accuracies, successful robot learning of subtask-assignment is feasible, with around 80% choice accuracy among four subtasks within 17 minutes of collaboration. The simulation results further reveal that scalability to more subtasks is feasible and mainly accompanied with longer robot learning times. These findings demonstrate the usability of EEG-based neuro-cognitive measures to mediate the complex and largely unsolved problem of human-robot collaborative task planning

Reduced pain perception in children and adolescents with ADHD is normalized by methylphenidate

Background: The present study examined pain perception in children and adolescents with ADHD and the interaction between pain perception and the administration of methylphenidate (MPH) in order to generate hypotheses for further research that will help to clarify the association between ADHD diagnosis, MPH treatment and pain perception. Methods: We included 260 children and adolescents of the “German Health Interview and Examination Survey for Children and Adolescents” (KiGGS) and analyzed parent’s assessments of children’s pain distribution and pain perception, as well as the influence of MPH administration on pain perception in affected children and adolescents. Results: Pain perception was associated with ADHD and MPH administration, indicating that children and adolescents suffering from ADHD without MPH treatment were reported to have lower pain perception compared to both, healthy controls (HC) and ADHD patients medicated with MPH. Conclusion: We suggest that reduced pain perception in children and adolescents with ADHD not medicated with MPH may lead to higher risk tolerance by misjudgments of dangerous situations, expanding the importance of MPH administration in affected children and adolescents

Barking up the wrong biomarker? Correspondence to Shobeiri et al. (2022) “Serum and plasma levels of brain-derived neurotrophic factor in individuals with eating disorders (EDs): a systematic review and meta-analysis”

Despite intensified research efforts into the underlying (neuro-)biology of eating disorders (EDs), only few reliable biomarkers of diagnostic or prognostic value have been identified to date. One promising line of research has focused on the role of peripheral blood-based biomarkers as potential contributors to the complex pathophysiology of EDs. One such candidate marker is brain-derived neurotrophic factor (BDNF), a neurotrophin broadly implicated in neuronal plasticity and food-intake regulation. A growing number of studies have targeted BDNF in EDs; culminating in several recent well-powered and controlled case–control studies, comprehensive meta-analyses, and review articles. In the current correspondence, we aim to put the recent meta-analysis of Shobeiri et al. (J Eat Disord 10(1):105, 2022) into perspective and argue that the finding suggestive of lower BDNF concentrations across individuals with EDs in comparison to healthy controls needs to be interpreted with caution. While this finding is compatible with those from earlier meta-analyses, it may be biased due to several reasons; most notably by the applied study selection procedures, insufficient consideration of influential determinants of BDNF concentrations, and generalization of results across the ED spectrum without sufficient statistical power. Further controlled and comprehensive studies are necessary to establish BDNF as a clinically informative biomarker of EDs

Automatic and Controlled Processing : Implications for Eating Behavior

It is a widely held view that humans have control over their food choices and consumption. However, research also suggests that eating behavior is often triggered by contextual cues and guided by automaticities and habits. Interestingly, the dichotomy between automatic and controlled processing has recently been challenged, suggesting that they may be intertwined. In a large female sample (n = 567), we investigated the hypothesis that task-based and self-reported measures of automatic and controlled processing would interact and impact self-reported eating behavior. Results analyzed via structural equation modeling suggest that automatic, but not controlled processing, during a modified flanker task, including a context-specific proportion congruent (CSPC) manipulation, was inversely associated with self-reported self-control. The influence of self-control on unhealthy eating behavior (i.e., uncontrolled and emotional eating, heightened consumption of fat and sugar) was only indirect via habitual behavior, which itself had a strong direct impact. Unhealthy eating was further associated with real-life outcomes (e.g., body mass index (BMI)). Our findings suggest that eating behavior may indeed be guided primarily by automaticities and habits, whereas self-control might facilitate this association. Having self-control over eating might therefore be most effective by avoiding contextual cues eliciting undesired automatic behavior and establishing habits that serve long-term goals.Peer reviewe

Automatic and Controlled Processing: Implications for Eating Behavior

It is a widely held view that humans have control over their food choices and consumption. However, research also suggests that eating behavior is often triggered by contextual cues and guided by automaticities and habits. Interestingly, the dichotomy between automatic and controlled processing has recently been challenged, suggesting that they may be intertwined. In a large female sample (n = 567), we investigated the hypothesis that task-based and self-reported measures of automatic and controlled processing would interact and impact self-reported eating behavior. Results analyzed via structural equation modeling suggest that automatic, but not controlled processing, during a modified flanker task, including a context-specific proportion congruent (CSPC) manipulation, was inversely associated with self-reported self-control. The influence of self-control on unhealthy eating behavior (i.e., uncontrolled and emotional eating, heightened consumption of fat and sugar) was only indirect via habitual behavior, which itself had a strong direct impact. Unhealthy eating was further associated with real-life outcomes (e.g., body mass index (BMI)). Our findings suggest that eating behavior may indeed be guided primarily by automaticities and habits, whereas self-control might facilitate this association. Having self-control over eating might therefore be most effective by avoiding contextual cues eliciting undesired automatic behavior and establishing habits that serve long-term goals

Meta Gene Set Enrichment Analyses Link miR-137-regulated Pathways With Schizophrenia Risk

Background: A single nucleotide polymorphism (SNP) within MIR137, the host gene for miR-137, has been identified repeatedly as a risk factor for schizophrenia. Previous genetic pathway analyses suggest that potential targets of this microRNA (miRNA) are also highly enriched in schizophrenia-relevant biological pathways, including those involved in nervous system development and function. Methods: In this study, we evaluated the schizophrenia risk of miR-137 target genes within these pathways. Gene set enrichment analysis of pathway-specific miR-137 targets was performed using the stage 1 (21,856 subjects) schizophrenia genome wide association study data from the Psychiatric Genomics Consortium and a small independent replication cohort (244 subjects) from the Mind Clinical Imaging Consortium and Northwestern University. Results: Gene sets of potential miR-137 targets were enriched with variants associated with schizophrenia risk, including target sets involved in axonal guidance signaling, Ephrin receptor signaling, long-term potentiation, PKA signaling, and Sertoli cell junction signaling. The schizophrenia-risk association of SNPs in PKA signaling targets was replicated in the second independent cohort. Conclusions: These results suggest that these biological pathways may be involved in the mechanisms by which this MIR137 variant enhances schizophrenia risk. SNPs in targets and the miRNA host gene may collectively lead to dysregulation of target expression and aberrant functioning of such implicated pathways. Pathway-guided gene set enrichment analyses should be useful in evaluating the impact of other miRNAs and target genes in different diseases