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Background: Early identification of risk for depression and anxiety disorders is important for prevention, but real-life affective well-being and its biological underpinnings in the population remain understudied. Here, we combined methods from epidemiology, psychology, ecological momentary assessment, and functional magnetic resonance imaging to study real-life and neural affective functions in individuals with subclinical anxiety and depression from a population-based cohort of young adults. Methods: We examined psychological measures, real-life affective valence, functional magnetic resonance imaging amygdala habituation to negative affective stimuli, and the relevance of neural readouts for daily-life affective function in 132 non–help-seeking community individuals. We compared psychological and ecological momentary assessment measures of 61 unmedicated individuals at clinical risk for depression and anxiety (operationalized as subthreshold depression and anxiety symptoms or a former mood or anxiety disorder) with those of 48 nonrisk individuals and 23 persons with a mood or anxiety disorder. We studied risk-associated functional magnetic resonance imaging signals in subsamples with balanced sociodemographic and image quality parameters (26 nonrisk, 26 at-risk persons). Results: Compared with nonrisk persons, at-risk individuals showed significantly decreased real-life affective valence (p = .038), reduced amygdala habituation (familywise error–corrected p = .024, region of interest corrected), and an intermediate psychological risk profile. Amygdala habituation predicted real-life affective valence in control subjects but not in participants at risk (familywise error–corrected p = .005, region of interest corrected). Conclusions: Our data suggest real-life and neural markers for affective alterations in unmedicated community individuals at risk for depression and anxiety and highlight the significance of amygdala habituation measures for the momentary affective experience in real-world environments.

Continuous real-time functional magnetic resonance imaging (fMRI) neurofeedback is gaining increasing scientific attention in clinical neuroscience and may benefit from the short repetition times of modern multiband echoplanar imaging sequences. However, minimizing feedback delay can result in technical challenges. Here, we report a technical problem we experienced during continuous fMRI neurofeedback with multiband echoplanar imaging and short repetition times. We identify the possible origins of this problem, describe our current interim solution and provide openly available workflows and code to other researchers in case they wish to use a similar approach.

Psychological stress and physical activity are interrelated, constituting a relevant association to human health, especially in children. However, the association’s nature remains elusive, i.e., why psychological stress predicts both decreased and increased physical activity. To test whether effects vary as a function of the level of analyses, we derived intensive longitudinal data via accelerometers and stress questionnaires from 74 children across 7 days as they went about their daily routines (n = 513 assessments). Multilevel modelling analyses revealed that between children, higher psychological stress predicted decreased physical activity (standardized beta coefficient = −0.14; p = 0.046). Concurrently, within those children, higher psychological stress predicted increased physical activity across days (standardized beta coefficient = 0.09; p = 0.015). Translated to practice, children who experienced more stress than others moved less, but children were more active on days when they experienced heightened stress. This suggests that the analyses level is crucial to the understanding of the association between psychological stress and physical activity and should be considered to receive unequivocal results. If replicated, e.g., including high-frequency sampling and experimental manipulation in everyday life for in-depth insights on underlying mechanisms and causality, our findings may be translated to individually tailored (digital) prevention and intervention strategies which target children’s distress-feelings despite impairing their heightened physical activity in stressful situations and identify tipping points of chronic stress phases. Therefore, we especially call for more intensive longitudinal data approaches to tackle thus far neglected within-subject issues in the field of physical activity, sport and exercise research.

Introduction: Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. Method: In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. Results: Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that – although more systematic studies are necessary – task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. Conclusion: Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.

Background The majority of knowledge about fibromyalgia syndrome (FMS) derives from studies of female patients. Little is known about the clinical characteristics and treatment outcomes of male FMS patients. Objective We investigated whether male FMS patients differ from female patients in terms of 1.) symptom burden, 2.) psychological characteristics, and 3.) clinical treatment response. Methods For this retrospective cohort study with a prospective posttreatment-follow-up, we identified 263 male (4%) out of 5,541 FMS patients completing a three-week multimodal pain-treatment program. Male FMS patients (51.3±9.1 years) were age- and time-matched (1:4) with female FMS patients (N = 1052, 51.3±9.0 years). Data on clinical characteristics, psychological comorbidities and treatment response were obtained from medical records and validated questionnaires. Results Levels of perceived pain, psychological comorbidity, and functional capacity were similar between genders, although male FMS patients showed a higher prevalence for alcohol abuse. Compared to female patients, male FMS patients experienced themselves less often as overly accommodating (Cohen’s d=-0.42), but more often as self-sacrificing (d = 0.26) or intrusive (d = 0.23). Regarding pain coping, male patients were less likely to utilize mental distraction, rest- and relaxation techniques, or counteractive activities (d = 0.18–0.27). Male FMS patients showed a slightly worse overall response rate than women (69% vs. 77%), although differences between individual outcome measures were small (d

Background Childhood trauma exposures (CTEs) are frequent, well-established risk factor for the development of psychopathology. However, knowledge of the effects of CTEs in healthy individuals in a real life context, which is crucial for early detection and prevention of mental disorders, is incomplete. Here, we use ecological momentary assessment (EMA) to investigate CTE load-dependent changes in daily-life affective well-being and psychosocial risk profile in n = 351 healthy, clinically asymptomatic, adults from the community with mild to moderate CTE. Findings EMA revealed significant CTE dose-dependent decreases in real-life affective valence (p = 0.007), energetic arousal (p = 0.032) and calmness (p = 0.044). Psychosocial questionnaires revealed a broad CTE-related psychosocial risk profile with dose-dependent increases in mental health risk-associated features (e.g., trait anxiety, maladaptive coping, loneliness, daily hassles; p values p values Conclusions Healthy community-based adults with mild to moderate CTE exhibit dose-dependent changes in well-being manifesting in decreases in affective valence, calmness and energy in real life settings, as well as a range of established psychosocial risk features associated with mental health risk. This indicates an approach to early detection, early intervention, and prevention of CTE-associated psychiatric disorders in this at-risk population, using ecological momentary interventions (EMI) in real life, which enhance established protective factors for mental health, such as green space exposure, or social support.

The COVID-19 pandemic strongly impacted people's daily lives. However, it remains unknown how the pandemic situation affects daily-life experiences of individuals with preexisting severe mental illnesses (SMI). In this real-life longitudinal study, the acute onset of the COVID-19 pandemic in Germany did not cause the already low everyday well-being of patients with schizophrenia (SZ) or major depression (MDD) to decrease further. On the contrary, healthy participants’ well-being, anxiety, social isolation, and mobility worsened, especially in healthy individuals at risk for mental disorder, but remained above the levels seen in patients. Despite being stressful for healthy individuals at risk for mental disorder, the COVID-19 pandemic had little additional influence on daily-life well-being in psychiatric patients with SMI. This highlights the need for preventive action and targeted support of this vulnerable population.

The concept ‘nociplastic pain’ has been developed for patients in whom clinical and psychophysical findings suggest a predominant central sensitization type of pain that is not fully explained as nociceptive or neuropathic. Here we tested, how well the recently published grading system differentiates between chronic primary pain or chronic secondary pain conditions. We recruited patients with Fibromyalgia (FMS, 41), Complex Regional Pain Syndrome (CRPS, 11), Osteoarthritis (OA, 21) or Peripheral Nerve Injury (PNI, 8). We used clinical history, pain drawings, Quantitative Sensory Testing (QST) and questionnaires to classify patients’ pains as possibly or probably ‘nociplastic’ in nature.All FMS and CRPS patients exhibited widespread or regional pain that was not explainable by nociceptive nor neuropathic mechanisms. Widespread pain in 12 OA patients was fully explained as nociceptive and regional pain in 4 PNI patients as neuropathic in all but one in each group. QST provided evidence for hypersensitivity in 9/11 CRPS patients but only 27/41 FMS patients (possible ‘nociplastic pain’). 82% of the CRPS patients but only 54% of FMS patients reported a history of hypersensitivity and mental comorbidities (probable ‘nociplastic pain’). We suggest that clinical examination of hypersensitivity should be done in more than one region and that adding a high tender point count as evidence for hypersensitivity phenomena may be useful. Further we suggest to switch the sequence of steps so that self-reported hypersensitivity and comorbidities come before clinical examination of hypersensitivity; Since the ‘nociplastic pain’ concept calls for brainstem and cortical plasticity we discuss in detail potential measurement strategies.

The specific role of white matter (WM) microstructure in parkinsonism among patients with schizophrenia spectrum disorders (SSD) is largely unknown. To determine whether topographical alterations of WM microstructure contribute to parkinsonism in SSD patients, we examined healthy controls (HC, n=16) and SSD patients with and without parkinsonism, as defined by Simpson-Angus Scale total score of ≥4 (SSD-P, n=33) or

Aberrant limbic circuit reactivity to negative stimuli might be related to alterations in emotion processing and regulation in alcohol use disorder (AUD). The current study tested for the first time in AUD the hypothesis of aberrant amygdala habituation to repeated aversive stimuli-a robust and reliable neuroimaging marker for emotion processing. We explored the link between deficits in habituation to adverse childhood experience (ACE), a common risk factor for impaired emotion regulation and AUD. AUD individuals (N = 36) and healthy controls (HC; N = 26) participated in an observational case-control functional magnetic resonance imaging (fMRI) study. An established habituation index was used to investigate processing of aversive emotional faces of the amygdala. AUD individuals showed an overall deficit in amygdala habituation (right: t = 4.26, pFWE = 0.004; left: t = 4.79, pFWE ≤ 0.001). Amygdala habituation was significantly related to increased exposure to ACE in HC (t = 3.88, pFWE = 0.012), whereas this association was not observed in AUD individuals (T = 1.80, pFWE = 0.662). Further, a significant association between higher alcohol consumption and reduced amygdala habituation (right: R

Background Difficulties in social communication are a defining clinical feature of autism. However, the underlying neurobiological heterogeneity has impeded targeted therapies and requires new approaches to identifying clinically relevant bio-behavioural subgroups. In the largest autism cohort to date, we comprehensively examined difficulties in facial expression recognition, a key process in social communication, as a bio-behavioural stratification biomarker, and validated them against clinical features and neurofunctional responses. Methods Between 255 and 488 participants aged 6–30 years with autism, typical development and/or mild intellectual disability completed the Karolinska Directed Emotional Faces task, the Reading the Mind in the Eyes Task and/or the Films Expression Task. We first examined mean-group differences on each test. Then, we used a novel intersection approach that compares two centroid and connectivity-based clustering methods to derive subgroups based on the combined performance across the three tasks. Measures and subgroups were then related to clinical features and neurofunctional differences measured using fMRI during a fearful face-matching task. Results We found significant mean-group differences on each expression recognition test. However, cluster analyses showed that these were driven by a low-performing autistic subgroup (~ 30% of autistic individuals who performed below 2SDs of the neurotypical mean on at least one test), while a larger subgroup (~ 70%) performed within 1SD on at least 2 tests. The low-performing subgroup also had on average significantly more social communication difficulties and lower activation in the amygdala and fusiform gyrus than the high-performing subgroup. Limitations Findings of autism expression recognition subgroups and their characteristics require independent replication. This is currently not possible, as there is no other existing dataset that includes all relevant measures. However, we demonstrated high internal robustness (91.6%) of findings between two clustering methods with fundamentally different assumptions, which is a critical pre-condition for independent replication. Conclusions We identified a subgroup of autistic individuals with expression recognition difficulties and showed that this related to clinical and neurobiological characteristics. If replicated, expression recognition may serve as bio-behavioural stratification biomarker and aid in the development of targeted interventions for a subgroup of autistic individuals.

Background: Although many studies have explored atypicalities in gray matter (GM) and white matter (WM) morphology of autism, most of them relied on unimodal analyses that did not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish brain patterns of modalities that differentiate between individuals with and without autism and explore associations between these brain patterns and clinical measures in the autism group. Methods: We studied 183 individuals with autism and 157 nonautistic individuals (age range, 6–30 years) in a large, deeply phenotyped autism dataset (EU-AIMS LEAP [European Autism Interventions—A Multicentre Study for Developing New Medications Longitudinal European Autism Project]). Linked independent component analysis was used to link all participants’ GM volume and WM diffusion tensor images, and group comparisons of modality shared variances were examined. Subsequently, we performed univariate and multivariate brain-behavior correlation analyses to separately explore the relationships between brain patterns and clinical profiles. Results: One multimodal pattern was significantly related to autism. This pattern was primarily associated with GM volume in bilateral insula and frontal, precentral and postcentral, cingulate, and caudate areas and co-occurred with altered WM features in the superior longitudinal fasciculus. The brain-behavior correlation analyses showed a significant multivariate association primarily between brain patterns that involved variation of WM and symptoms of restricted and repetitive behavior in the autism group. Conclusions: Our findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism and show that the complex clinical autism phenotype can be interpreted by brain covariation patterns that are spread across the brain involving both cortical and subcortical areas.

Translational research in neuroscience is increasingly focusing on the analysis of multi-modal data, in order to account for the biological complexity of suspected disease mechanisms. Recent advances in machine learning have the potential to substantially advance such translational research through the simultaneous analysis of different data modalities. This review focuses on one of such approaches, the so-called “multi-task learning” (MTL), and describes its potential utility for multi-modal data analyses in neuroscience. We summarize the methodological development of MTL starting from conventional machine learning, and present several scenarios that appear particularly suitable for its application. For these scenarios, we highlight different types of MTL algorithms, discuss emerging technological adaptations, and provide a step-by-step guide for readers to apply the MTL approach in their own studies. With its ability to simultaneously analyze multiple data modalities, MTL may become an important element of the analytics repertoire used in future neuroscience research and beyond.

Self-regulation, the ability to guide behavior according to one’s goals, plays an integral role in understanding loss of control behaviors a pertinent example being substance use disorders (SUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors often occur, namely in real life situations outside the laboratory. Moreover, lab-based experimental tasks are criticized for poor test–retest reliability and a lack of construct validity. These concerns might in part explain why ecological validity of experimental measures—their ability to predict real-life behavior—is low. To address these shortcomings, we assessed the reliability and construct validity of four smartphone-based experimental tasks designed to measure cognitive control and decision-making. To facilitate future clinical applicability we recruited a large (N=488) sample of individuals with SUD. Joint modeling of measurement sessions increased the reliability of task measures from moderate to good and often excellent levels. In line with theories of cognitive control and motivation, three latent factors reflecting cognitive control and decision-making in the context of gains and losses best described the data. As proof of concept, we show that a latent cognitive control score based on joint modeling, yielded stronger correlations with drinking behavior than single task scores based on separate modeling. These findings indicate that in individuals with SUD, smartphone-based ambulatory experimental assessments can reliably index functions of cognitive control and decision-making, with plausible construct validity. Our findings provide evidence for rich possibilities arising from longitudinal experimental studies in SUD as well as in psychiatry, neuroscience, and psychology more generally.

Early adverse environmental exposures during brain development are widespread risk factors for the onset of severe mental disorders and strong and consistent predictors of stress-related mental and physical illness and reduced life expectancy. Current evidence suggests that early negative experiences alter plasticity processes during developmentally sensitive time windows and affect the regular functional interaction of cortical and subcortical neural networks. This, in turn, may promote a maladapted development with negative consequences on the mental and physical health of exposed individuals. In this review, we discuss the role of functional magnetic resonance imaging-based functional connectivity phenotypes as potential biomarker candidates for the consequences of early environmental exposures-including but not limited to-childhood maltreatment. We take an expanded concept of developmentally relevant adverse experiences from infancy over childhood to adolescence as our starting point and focus our review of functional connectivity studies on a selected subset of functional magnetic resonance imaging-based phenotypes, including connectivity in the limbic and within the frontoparietal as well as default mode networks, for which we believe there is sufficient converging evidence for a more detailed discussion in a developmental context. Furthermore, we address specific methodological challenges and current knowledge gaps that complicate the interpretation of early stress effects on functional connectivity and deserve particular attention in future studies. Finally, we highlight the forthcoming prospects and challenges of this research area with regard to establishing functional connectivity measures as validated biomarkers for brain developmental processes and individual risk stratification and as target phenotypes for mechanism-based interventions.

BackgroundDuring the COVID-19 pandemic telemedicine became essential in maintaining diagnostic procedures and treatment in psychiatry. However, it is still an open question if telemedicine is a feasible treatment option for all groups of psychiatric patients alike. This prospective monocentric observational trial was conducted to assess the general applicability of telemedical treatment in a naturalistic psychiatric outpatient cohort and to identify groups of disorders and clusters of psychopathology that respond particularly well to telemedical treatment considering sociodemographic characteristics and patients' perspectives.MethodsPatients were recruited April 2020–April 2021 and asked to fill out the WHO-5 and the SCL-90R at baseline, after 4–6 and 8–12 weeks and a feedback-survey. Additionally, medical records, psychopathology, psychosocial functioning, and socio-demographic data were analyzed. Primary outcomes were well-being, psychopathology and functioning during treatment. Secondly, diagnostic groups and psychopathology linked to a superior treatment-response were determined with respect to patients' subjective experiences.ResultsOut of 1.385 patients, 254—mostly with hyperkinetic (35.3%) and depressive disorders (24.6%)—took part. Well-being and SCL-90R total scores improved substantially (both p < 0.001). CGI and GAF scores were worse in depressed subjects (both p < 0.05). Improvement was mainly seen in depressed patients; chronic disorders experienced a decline in well-being. Sociodemographic characteristics could not explain this difference. Particularly female (r = 0.413) patients found telepsychiatry equivalent to conventional treatment. The more virtual sessions participants attended the more likely they were to find telepsychiatry equal to conventional treatment (r = 0.231).ConclusionTelemedicine is an effective treatment for patients with depression under naturalistic conditions. Telemedical consultations are a simple and reliable way of monitoring symptom severity and directing treatment choices during the treatment of depressive disorders. Patients with depression benefited more from telemedical treatment compared to participants with chronic non-episodic psychiatric disorders. Future research needs to concentrate on improving telemedical treatment options suited for the latter conditions. Psychiatric telemedicine yielded overall high degrees of satisfaction among users.

While sensorimotor abnormalities in schizophrenia (SZ) are of increasing scientific interest, little is known about structural changes and their developmental origins that may underlie parkinsonism. This multimodal magnetic resonance imaging (MRI) study examined healthy controls (HC, n = 20) and SZ patients with (SZ-P, n = 38) and without (SZ-nonP, n = 35) parkinsonism, as defined by Simpson-Angus Scale total scores of ≥4 or ≤1, respectively. Using the Computational Anatomy Toolbox (CAT12), voxel- and surface-based morphometry were applied to investigate cortical and subcortical gray matter volume (GMV) and three cortical surface markers of distinct neurodevelopmental origin: cortical thickness (CTh), complexity of cortical folding (CCF) and sulcus depth. In a subgroup of patients (29 SZ-nonP, 25 SZ-P), resting-state fMRI data were also analyzed using a regions-of-interest approach based on fractional amplitude of low frequency fluctuations (fALFF). SZ-P patients showed increased CCF in the left supplementary motor cortex (SMC) and decreased left postcentral sulcus (PCS) depth compared to SZ-nonP patients (p 0.05, FWE-corrected at cluster level). In SMC, CCF was associated negatively with activity, which also differed significantly between the patient groups and between patients and HC. In regression models, severity of parkinsonism was associated negatively with left middle frontal CCF and left anterior cingulate CTh. These data provide novel insights into altered trajectories of cortical development in SZ patients with parkinsonism. These cortical surface changes involve the sensorimotor system, suggesting abnormal neurodevelopmental processes tightly coupled with cortical activity and subcortical morphology that convey increased risk for sensorimotor abnormalities in SZ.

ZusammenfassungPsychische Erkrankungen sind weit verbreitet und ein bedeutendes Problem des allgemeinen Gesundheitswesens. Das Risiko, irgendwann im Laufe des Lebens eine psychische Erkrankung zu entwickeln, liegt bei rund 40 %. Psychische Erkrankungen zählen damit zu den epidemiologisch bedeutsamsten Erkrankungen. Trotz der Einführung neuerer Psychopharmaka, störungsspezifischer Psychotherapie und Stimulationstechniken zeigen viele der Betroffenen immer noch eine unzureichende Symptomremission und einen chronischen Verlauf. Durch den konzeptuellen und technischen Fortschritt der letzten Jahre wird eine neue, flexiblere und personalisierte Form der fachpsychiatrischen Patientenversorgung ermöglicht. Sowohl die traditionellen Therapie- und Organisationskonzepte als auch neuere dezentral arbeitende, modular aufgebaute, stationär-teilstationär-ambulante Einheiten werden zusammen mit innovativen digitalen Technologien vielen betroffenen Menschen mit psychischen Erkrankungen individualisierte Therapieoptionen bieten, welche ihre Symptome bestmöglich lindern und ihre Lebensqualität erheblich verbessern könnten. Das primäre Ziel der engen Verknüpfung von modernen Versorgungskonzepten und innovativen Technologien ist es, ein umfassendes Therapie- und Nachsorgekonzept (innerhalb und außerhalb der Klinik) für die individuellen Bedürfnisse von Menschen mit psychischer Erkrankung bereitzustellen. Nicht zuletzt wird dadurch auch eine ortsunabhängige Verfügbarkeit der fachärztlichen Behandlung erreicht. In der Psychiatrie des 21. Jahrhunderts müssen moderne Versorgungsstrukturen mit der aktuellen Dynamik der digitalen Transformation effektiv verknüpft werden. Die vorliegende selektive Übersichtsarbeit widmet sich den theoretischen und praktischen Gesichtspunkten eines sektorenübergreifenden Behandlungssystems kombiniert mit innovativen digitalen Technologien im psychiatrisch-psychotherapeutischen Fachbereich am Beispiel des Zentralinstituts für Seelische Gesundheit in Mannheim.

BackgroundAberrant brain connectivity during emotional processing, especially within the fronto-limbic pathway, is one of the hallmarks of major depressive disorder (MDD). However, the methodological heterogeneity of previous studies made it difficult to determine the functional and etiological implications of specific alterations in brain connectivity. We previously reported alterations in psychophysiological interaction measures during emotional face processing, distinguishing depressive pathology from at-risk/resilient and healthy states. Here, we extended these findings by effective connectivity analyses in the same sample to establish a refined neural model of emotion processing in depression.MethodsThirty-seven patients with MDD, 45 first-degree relatives of patients with MDD and 97 healthy controls performed a face-matching task during functional magnetic resonance imaging. We used dynamic causal modeling to estimate task-dependent effective connectivity at the subject level. Parametric empirical Bayes was performed to quantify group differences in effective connectivity.ResultsMDD patients showed decreased effective connectivity from the left amygdala and left lateral prefrontal cortex to the fusiform gyrus compared to relatives and controls, whereas patients and relatives showed decreased connectivity from the right orbitofrontal cortex to the left insula and from the left orbitofrontal cortex to the right fusiform gyrus compared to controls. Relatives showed increased connectivity from the anterior cingulate cortex to the left dorsolateral prefrontal cortex compared to patients and controls.ConclusionsOur results suggest that the depressive state alters top-down control of higher visual regions during face processing. Alterations in connectivity within the cognitive control network present potential risk or resilience mechanisms.

At present, current diagnostic criteria and systems neglect affective symptom expression in catatonia. This potentially serious omission could explain why putative contributions of limbic system structures, such as amygdala, hippocampus or hypothalamus, to catatonia in schizophrenia spectrum disorders (SSD) have been scarcely investigated so far. To determine whether topographical alterations of the amygdala, hippocampus and hypothalamus contribute to catatonia in SSD patients, we conducted structural magnetic resonance imaging (MRI) of SSD patients with (SSD-Cat, n = 30) and without (SSD-nonCat, n = 28) catatonia as defined by a Northoff Catatonia Rating Scale (NCRS) total score of ≥3 and =0, respectively, in comparison with healthy controls (n = 20). FreeSurfer v7.2 was used for automated segmentation of the amygdala and its 9 nuclei, hippocampus and its 21 subfields and hypothalamus and its associated 5 subunits. SSD-Cat had significantly smaller anterior inferior hypothalamus, cortical nucleus of amygdala, and hippocampal fimbria volumes when compared to SSD-nonCat. SSD-Cat had significantly smaller amygdala, hippocampus and hypothalamus whole and subunit volumes when compared to healthy controls. In SSD-Cat according to DSM-IV-TR (n = 44), we identified positive correlations between Brief Psychiatric Rating Scale (BPRS) item #2 (reflecting anxiety) and respective amygdala nuclei as well as negative correlation between NCRS behavioral score and hippocampus subiculum head. The lower volumes of respective limbic structures involved in affect regulation may point towards central affective pathomechanisms in catatonia.

Longitudinal cohort studies with early start and life span perspectives are increasingly recognized as being crucial to uncover developmental trajectories as well as risk and resilience factors of psychiatric disorders.The importance of longitudinal studies is presented and the main findings of the Mannheim study of children at risk (MARS), the adolescent brain cognitive development (ABCD), the pediatric and adolescent health survey (Kinder- und Jugendgesundheitssurvey, KiGGS) and the AIMS longitudinal European autism project (LEAP) cohort studies are described.A literature search was carried out in MEDLINE.The MARS followed participants with psychosocial and organic risks over more than 30 years starting from birth and showed the importance of early risk factors (prenatal period up to early childhood) for neuropsychosocial development. The ABCD cohort study (start 9-10 years old) underlined the developmental significance of early socioemotional and prenatal risks as well as toxin exposure. The KiGGS cohort followed children and adolescents from age 0-17 years up to the ages of 10-28 years. Main findings underline the importance of the socioeconomic status and gender-specific effects with respect to sensitive periods for the onset and trajectories of psychiatric disorders. The AIMS cohort followed patients with and without autism spectrum disorders aged between 6 and 30 years and first results revealed small effects regarding group differences. Further, cohort studies starting prenatally along with deep phenotyping are warranted to uncover the complex etiology of mental disorders.Existing cohort studies on early mental development have shown specific focal points. To identify general and specific risk and resilience factors for psychiatric disorders and to model trajectories, there is a need for multimodal integration of data sets.HINTERGRUND: Kohortenstudien mit frühem Beginn und Lebensspannenperspektive sind essenziell, um die Verläufe psychiatrischer Erkrankungen sowie deren Risiko- und Resilienzfaktoren zu beleuchten.Die Bedeutung von Längsschnittstudien wird dargestellt und exemplarisch die Mannheimer Risikokinderstudie (MARS), die ABCD (Adolescent Brain Cognitive Development), KiGGS (Kinder- und Jugendgesundheitssurvey) und AIMS LEAP (Longitudinal European Autism Project) -Kohortenstudien beschrieben.Es erfolgte eine Literatursuche in MEDLINE.Die MARS begleitet Teilnehmer mit psychosozialen und organischen Risiken seit über 30 Jahren von der Geburt an und hat gezeigt, dass Risiken vor und kurz nach Geburt bis in die frühe Kindheit besonders wichtig für die neurobiologische und psychische Entwicklung sind. Die ABCD-Kohortenstudie (Beginn 9–10 Jahre) unterstreicht die Wichtigkeit früher sozioemotionaler, pränataler Risiken sowie Toxinexposition für die Entwicklung. Die KiGGS-Kohortenstudie, die Kinder und Jugendliche von 0 bis 17 Jahren bis zum Alter von 10 bis 28 Jahre verfolgte, hebt die Bedeutung des sozioökonomischen Status sowie auch geschlechtsspezifischer Effekte hinsichtlich sensitiver Perioden für das Auftreten psychischer Auffälligkeiten sowie deren Verlauf hervor. Die AIMS-Kohortenstudie begleitet Menschen mit und ohne Autismusspektrumstörungen im Alter von 6 bis 30 Jahren, wobei erste Befunde auf Gruppenebene kleine Effekte zeigen.Existierende Kohortenstudien zur frühen psychischen Entwicklung weisen spezifische Schwerpunkte auf. Um allgemeine und spezifische Risiko- und Resilienzfaktoren zu identifizieren und trajektorielle Verläufe zu modellieren, können bestehende multimodale Datensätze integriert werden. Weitere epidemiologische und klinische Kohortenstudien mit Beginn in der Pränatalzeit sowie multidimensionale Untersuchungsstrategien (deep phenotyping) sind erforderlich, um die komplexe Ätiopathogenese psychischer Störungen weiter zu entschlüsseln.

Physical activity is beneficial for human physical health and well-being. Accordingly, the association between physical activity and mood in everyday life has been a subject of several Ambulatory Assessment studies. This mechanism has been studied in children, adults, and the elderly, but neglected in adolescents. It is critical to examine this mechanism in adolescents because adolescence plays a key role in human development and adolescents’ physical activity behavior translates into their behavior in adulthood. We investigated adolescents’ mood in relation to distinct physical activities: incidental activity such as climbing stairs; exercise activity, such as skating; and sports, such as playing soccer. We equipped 134 adolescents aged 12-17 years with accelerometers and GPS-triggered electronic diaries to use in their everyday life. Adolescents reported on mood repeatedly in real time across 7 days, and these data were analyzed using multilevel-modeling. After incidental activity, adolescents felt better and more energized. After exercise, adolescents felt better but less calm. After sports, adolescents felt less energized. Analyses of the time course of the effects confirmed our findings. Physical activity influences mood in adolescents’ everyday life, but has distinct effects depending on the kind of physical activity. Our results suggest incidental and exercise activities entail higher post-bout valence compared to sports in competitive settings. These findings may serve as an important empirical basis for the targeted application of distinct physical activities to foster well-being in adolescence.

Catatonia is characterized by motor, affective and behavioral abnormalities. To date, the specific role of white matter (WM) abnormalities in schizophrenia spectrum disorders (SSD) patients with catatonia is largely unknown. In this study, diffusion magnetic resonance imaging (dMRI) data were collected from 111 right-handed SSD patients and 28 healthy controls. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). We used whole-brain tract-based spatial statistics (TBSS), tractometry (along tract statistics using TractSeg) and graph analytics (clustering coefficient—CCO, local betweenness centrality—BC) to provide a framework of specific WM microstructural abnormalities underlying catatonia in SSD. Following a categorical approach, post hoc analyses showed differences in fractional anisotrophy (FA) measured via tractometry in the corpus callosum, corticospinal tract and thalamo-premotor tract as well as increased CCO as derived by graph analytics of the right superior parietal cortex (SPC) and left caudate nucleus in catatonic patients (NCRS total score ≥ 3; n = 30) when compared to non-catatonic patients (NCRS total score = 0; n = 29). In catatonic patients according to DSM-IV-TR (n = 43), catatonic symptoms were associated with FA variations (tractometry) of the left corticospinal tract and CCO of the left orbitofrontal cortex, primary motor cortex, supplementary motor area and putamen. This study supports the notion that structural reorganization of WM bundles connecting orbitofrontal/parietal, thalamic and striatal regions contribute to catatonia in SSD patients.

Rapid worldwide urbanization benefits humans in many aspects, but the prevalence of common psychiatric disorders is increased in urban populations. While the impact of city living and urban upbringing on mental health is well established, it remains elusive which of the multiple factors of urban living convey risk and resilience for mental disorders. For example, air pollutants, traffic noises and fragmented social networks are some of the highly interdependent and complex influences of city living suggested to be detrimental for mental health. In contrast, urban green spaces, social contacts and physical activity have been associated with increased well-being. Knowledge on underlying mechanisms of these associations is crucial for both city planning and healthcare as it informs on how to build environments and to intervene in a way that fosters mental health yet reduces psychiatric disorders. Thus, real-life studies in urban contexts have been launched making use of recent methodological advancements: Mobile devices (e.g. smartphones) to gather intensive longitudinal mental health data, stationary sensor output providing specific context information (e.g. on weather conditions and air pollution), combinations with traditional and modern neuroimaging techniques (e.g. functional near-infrared spectroscopy and portable magnetic-encephalogram caps) and modern virtual reality setups allowing for increasingly realistic and ecological valid simulation of complex urban environments. Here we review selected methodological developments, state-of-the-art approaches as well as technological frontiers and provide examples for their application, highlighting promising potential of these novel methods for tackling the urgent urbanicity societal issue of the 21st century with a view to improve urban contexts conducive to mental health.

Previous studies have provided evidence for an alteration of genetic coexpression in schizophrenia (SCZ). However, such analyses have thus far lacked biological specificity for individual genes, which may be critical for identifying illness-relevant effects. Therefore, we applied machine learning to identify gene-specific coexpression differences at the individual subject level and compared these between individuals with SCZ, bipolar disorder, major depressive disorder (MDD), autism spectrum disorder (ASD), and healthy controls. Utilizing transcriptome-wide gene expression data from 21 independent datasets, comprising a total of 9509 participants, we identified a reproducible decrease of BCL11A coexpression across 4 SCZ datasets that showed diagnostic specificity for SCZ when compared with ASD and MDD. We further demonstrate that individual-level coexpression differences can be combined in multivariate coexpression scores that show reproducible illness classification across independent datasets in SCZ and ASD. This study demonstrates that machine learning can capture gene-specific coexpression differences at the individual subject level for SCZ and identify novel biomarker candidates.

Motor abnormalities in schizophrenia spectrum disorders (SSD) have increasingly attracted scientific interest in the past years. However, the neural mechanisms underlying parkinsonism in SSD are unclear. The present multimodal magnetic resonance imaging (MRI) study examined SSD patients with and without parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥4 (SAS group, n = 22) or

Common variation in the gene encoding the neuron-specific RNA splicing factor RNA Binding Fox-1 Homolog 1 (RBFOX1) has been identified as a risk factor for several psychiatric conditions, and rare genetic variants have been found causal for autism spectrum disorder (ASD). Here, we explored the genetic landscape of RBFOX1 more deeply, integrating evidence from existing and new human studies as well as studies in Rbfox1 knockout mice. Mining existing data from large-scale studies of human common genetic variants, we confirmed gene-based and genome-wide association of RBFOX1 with risk tolerance, major depressive disorder and schizophrenia. Data on six mental disorders revealed copy number losses and gains to be more frequent in ASD cases than in controls. Consistently, RBFOX1 expression appeared decreased in post-mortem frontal and temporal cortices of individuals with ASD and prefrontal cortex of individuals with schizophrenia. Brain-functional MRI studies demonstrated that carriers of a common RBFOX1 variant, rs6500744, displayed increased neural reactivity to emotional stimuli, reduced prefrontal processing during cognitive control, and enhanced fear expression after fear conditioning, going along with increased avoidance behaviour. Investigating Rbfox1 neuron-specific knockout mice allowed us to further specify the role of this gene in behaviour. The model was characterised by pronounced hyperactivity, stereotyped behaviour, impairments in fear acquisition and extinction, reduced social interest, and lack of aggression; it provides excellent construct and face validity as an animal model of ASD. In conclusion, convergent translational evidence shows that common variants in RBFOX1 are associated with a broad spectrum of psychiatric traits and disorders, while rare genetic variation seems to expose to early-onset neurodevelopmental psychiatric disorders with and without developmental delay like ASD, in particular. Studying the pleiotropic nature of RBFOX1 can profoundly enhance our understanding of mental disorder vulnerability.

Recent large-scale, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with general intelligence. The cumulative influence of these loci on brain structure is unknown. We examined if cortical morphology mediates the relationship between GWAS-derived polygenic scores for intelligence (PSi) and g-factor. Using the effect sizes from one of the largest GWAS meta-analysis on general intelligence to date, PSi were calculated among 10 P value thresholds. PSi were assessed for the association with g-factor performance, cortical thickness (CT), and surface area (SA) in two large imaging-genetics samples (IMAGEN N = 1651; IntegraMooDS N = 742). PSi explained up to 5.1% of the variance of g-factor in IMAGEN (F1,1640 = 12.2–94.3; P

Background Heightened amygdala response to threatening cues has been repeatedly observed in borderline personality disorder (BPD). A previous report linked hyperactivation to deficient amygdala habituation to repeated stimuli, but the biological underpinnings are incompletely understood. Methods We examined a sample of 120 patients with BPD and 115 healthy control subjects with a well-established functional magnetic resonance imaging emotional face processing task to replicate the previously reported amygdala habituation deficit in BPD and probed this neural phenotype for associations with symptom severity and early social risk exposure. Results Our results confirm a significant reduction in amygdala habituation to repeated negative stimuli in BPD (pFWE = .015, peak-level familywise error [FWE] corrected for region of interest). Post hoc comparison and regression analysis did not suggest a role for BPD clinical state (pFWE > .56) or symptom severity (pFWE > .45) for this phenotype. Furthermore, deficient amygdala habituation was significantly related to increased exposure to adverse childhood experiences (pFWE = .013, region of interest corrected). Conclusions Our data replicate a prior report on deficient amygdala habituation in BPD and link this neural phenotype to early adversity, a well-established social environmental risk factor for emotion dysregulation and psychiatric illness.

Background:Social integration is a major resilience factor for staying healthy. However, the COVID-19-pandemic led to unprecedented restrictions in social life. The consequences of these social lockdowns on momentary well-being are yet not fully understood.Method:We investigated the individual affective benefit from social interactions in a longitudinal birth cohort study. We used two real-time, real-life ecological momentary assessments once before and once during the initial lockdown of the pandemic (N~6800 total observations) to determine the protective role of social interactions on well-being. Moreover, we used a multimethod approach combining the ecological assessment data with individual risk and resilience factors to analyze the moderating mechanisms of personality, neurobiology and genes.Results:Social contacts were linked to higher positive affect both during normal times and during the COVID-19 pandemic, highlighting the beneficial role of social embedding. Moreover, this relationship was moderated by amygdala volume, neuroticism and polygenic risk for schizophrenia. In detail, participants with a larger left amygdala volume and higher trait neuroticism exhibited an affective benefit from more social interactions prior to the pandemic. This pattern changed during the pandemic with participants with smaller amygdala volumes and lower neurotic traits showing a social affective gain during the pandemic. Moreover, participants with low genetic risk for schizophrenia showed an affective benefit from social interactions irrespective of the time point.Conclusion:Our results highlight the protective role of social integration on momentary well-being. Thereby, we offer new insights into how this relationship is differently affected by a person’s, neurobiology, personality, and genes under adverse circumstances.

Die atemberaubende technologische Entwicklung im Bereich des mobilen Computings, der Smartphones und Wearables eroffnet fur die psychiatrische Forschung und Therapie neue Moglichkeiten. Wearables erlauben nicht nur, objektive Auspragungen psychischer Symptomatik im Alltag und in Echtzeit zu erfassen, sondern sie konnen uber kontinuierliches Monitoring und die Analyse relevanter Parameter bedeutsame Situationen/Kontexte und Zeitpunkte definieren, bei denen dann erweiterte Assessments oder Interventionen implementiert werden konnen. Am Beispiel der grunflacheninduzierten Stimmungsverbesserung, dem motivationsfordernden Verhaltensfeedback und dem Geofencing zur Detektion beginnender Trinkepisoden zeigen wir auf, wie Echtzeitanalysen und -feedback von Wearables in der psychiatrischen Forschung und Versorgung genutzt werden konnen.

BackgroundLimbic-cortical imbalance is an established model for the neurobiology of major depressive disorder (MDD), but imaging genetics studies have been contradicting regarding potential risk and resilience mechanisms. Here, we re-assessed previously reported limbic-cortical alterations between MDD relatives and controls in combination with a newly acquired sample of MDD patients and controls, to disentangle pathology, risk, and resilience.MethodsWe analyzed functional magnetic resonance imaging data and negative affectivity (NA) of MDD patients (n = 48), unaffected first-degree relatives of MDD patients (n = 49) and controls (n = 109) who performed a faces matching task. Brain response and task-dependent amygdala functional connectivity (FC) were compared between groups and assessed for associations with NA.ResultsGroups did not differ in task-related brain activation but activation in the superior frontal gyrus (SFG) was inversely correlated with NA in patients and controls. Pathology was associated with task-independent decreases of amygdala FC with regions of the default mode network (DMN) and decreased amygdala FC with the medial frontal gyrus during faces matching, potentially reflecting a task-independent DMN predominance and a limbic-cortical disintegration during faces processing in MDD. Risk was associated with task-independent decreases of amygdala-FC with fronto-parietal regions and reduced faces-associated amygdala-fusiform gyrus FC. Resilience corresponded to task-independent increases in amygdala FC with the perigenual anterior cingulate cortex (pgACC) and increased FC between amygdala, pgACC, and SFG during faces matching.ConclusionOur results encourage a refinement of the limbic-cortical imbalance model of depression. The validity of proposed risk and resilience markers needs to be tested in prospective studies. Further limitations are discussed.

The relationship between transdiagnostic, dimensional, and categorical approaches to psychiatric nosology is under intense debate. To inform this discussion, we studied neural systems linked to reward anticipation across a range of disorders and behavioral dimensions. We assessed brain responses to reward expectancy in a large sample of 221 participants, including patients with schizophrenia (SZ; n = 27), bipolar disorder (BP; n = 28), major depressive disorder (MD; n = 31), autism spectrum disorder (ASD; n = 25), and healthy controls (n = 110). We also characterized all subjects with an extensive test battery from which a cognitive, affective, and social functioning factor was constructed. These factors were subsequently related to functional responses in the ventral striatum (vST) and neural networks linked to it. We found that blunted vST responses were present in SZ, BP, and ASD but not in MD. Activation within the vST predicted individual differences in affective, cognitive, and social functioning across diagnostic boundaries. Network alterations extended beyond the reward network to include regions implicated in executive control. We further confirmed the robustness of our results in various control analyses. Our findings suggest that altered brain responses during reward anticipation show transdiagnostic alterations that can be mapped onto dimensional measures of functioning. They also highlight the role of executive control of reward and salience signaling in the disorders we study and show the power of systems-level neuroscience to account for clinically relevant behaviors., Schizophrenia Bulletin, 46 (3), ISSN:0586-7614, ISSN:1745-1701

Social interactions are essential to our daily life. We tested the hypothesis that social interactions during joint attention (JA) require bidirectional communication, each with a different mechanism. We used a novel multivariate functional connectivity analysis, which enables obtaining directed pathways between four regions at each time-frequency point, with hyper-scanning MRI data of real-time JA interaction. Constructing multiple “4-regional directed pathways” and counting the number of times, regions engaged in feedforward or feedback processes in the ‘sender’ or the ‘receiver brains, we obtained the following. (1) There were more regions in feedforward than in feedback processes (125 versus 99). (2) The right hemisphere was more involved in feedforward (74 versus 33), while the left hemisphere in feedback (66 versus 51). (3) The dmPFC was more engaged in feedforward (73 versus 44) while the TPJ in both (49 versus 45). (4) The dmPFC was more involved in the sending processes (i.e. initiation of feedforward and feedback) while the TPJ in the receiving processes. (5) JA interaction was involved with high MRI frequencies (0.04–0.1 Hz), while continues interactions by low MRI frequencies (0.01–0.04 Hz). (6) Initiation and responding to JA (i.e. IJA and RJA) evolved with composite neural systems: similar systems for pathways that included the dmPFC, vmPFC and the STS, and different systems for pathways that included the TPJ, vmPFC, PCC and the STS. These findings have important consequences in the basic understanding of social interaction and could help in diagnose and follow-up of social impairments.

The current study aimed to identify alterations in brain activation and connectivity related to nociceptive processing and pain sensitization in major depressive disorder (MDD), using repetitive heat pain stimulation during functional magnetic resonance imaging (fMRI) in 37 MDD patients and 33 healthy controls. Regional activation did not differ between groups, but functional connectivity was significantly decreased in MDD in a neural network connecting frontal, temporal and occipital areas (family-wise error-corrected pFWE = 0.045). Supporting analyses suggested a significant association between network connectivity and trait neuroticism (p = 0.007) but not with the clinical state or familiar risk of MDD (all p values > 0.13). Our data relate a network-based phenotype for altered pain processing and antinociceptive control to MDD and encourage future studies on the shared intermediate neural psychological risk architecture of MDD and chronic pain.

Previous studies have linked the low expression variant of a variable number of tandem repeat polymorphism in the monoamine oxidase A gene (MAOA‐L) to the risk for impulsivity and aggression, brain developmental abnormalities, altered cortico‐limbic circuit function, and an exaggerated neural serotonergic tone. However, the neurobiological effects of this variant on human brain network architecture are incompletely understood. We studied healthy individuals and used multimodal neuroimaging (sample size range: 219–284 across modalities) and network‐based statistics (NBS) to probe the specificity of MAOA‐L‐related connectomic alterations to cortical‐limbic circuits and the emotion processing domain. We assessed the spatial distribution of affected links across several neuroimaging tasks and data modalities to identify potential alterations in network architecture. Our results revealed a distributed network of node links with a significantly increased connectivity in MAOA‐L carriers compared to the carriers of the high expression (H) variant. The hyperconnectivity phenotype primarily consisted of between‐lobe (“anisocoupled”) network links and showed a pronounced involvement of frontal‐temporal connections. Hyperconnectivity was observed across functional magnetic resonance imaging (fMRI) of implicit emotion processing (p FWE = .037), resting‐state fMRI (p FWE = .022), and diffusion tensor imaging (p FWE = .044) data, while no effects were seen in fMRI data of another cognitive domain, that is, spatial working memory (p FWE = .540). These observations are in line with prior research on the MAOA‐L variant and complement these existing data by novel insights into the specificity and spatial distribution of the neurogenetic effects. Our work highlights the value of multimodal network connectomic approaches for imaging genetics.

Psychiatric morbidity is high in cities, so identifying potential modifiable urban protective factors is important. We show that exposure to urban green space improves well-being in naturally behaving male and female city dwellers, particularly in districts with higher psychiatric incidence and fewer green resources. Higher green-related affective benefit was related to lower prefrontal activity during negative-emotion processing, which suggests that urban green space exposure may compensate for reduced neural regulatory capacity. Tost et al. show that urban green space exposure improves well-being, particularly in people dwelling in relatively deprived areas and showing less prefrontal activity during emotion processing, a neural signature that is linked to mental health risk.

Studying the neural processing of faces can illuminate the mechanisms of compromised social expertise in autism. To resolve a longstanding debate, we examined whether differences in configural face processing in autism are underpinned by quantitative differences in the activation of typical face processing pathways, or the recruitment of non-typical neural systems.We investigated spatial and temporal characteristics of event-related EEG responses to upright and inverted faces in a large sample of children, adolescents, and adults with and without autism. We examined topographic analyses of variance and global field power to identify group differences in the spatial and temporal response to face inversion. We then examined how quasi-stable spatiotemporal profiles - microstates - are modulated by face orientation and diagnostic group.Upright and inverted faces produced distinct profiles of topography and strength in the topographical analyses. These topographical profiles differed between diagnostic groups in adolescents, but not in children or adults. In the microstate analysis, the autistic group showed differences in the activation strength of normative microstates during early-stage processing at all ages, suggesting consistent quantitative differences in the operation of typical processing pathways; qualitative differences in microstate topographies during late-stage processing became prominent in adults, suggesting the increasing involvement of non-typical neural systems with processing time and over development.These findings suggest that early difficulties with configural face processing may trigger later compensatory processes in autism that emerge in later development.

This cohort study examines the association of daily-life social affective benefit with brain structure and psychiatric risk and resilience measures in 2 independent community-based samples.

Insight into illness in schizophrenia (SZ) patients has a major impact on treatment adherence and outcome. Previous studies have linked distinct deviations of brain structure to illness insight, specifically in frontoparietal and subcortical regions. Some of these abnormalities are thought to reflect aberrant cortical development. In this study, we used cross-sectional data to examine associations between illness insight and two cortical surface markers that are known to follow distinct neurodevelopmental trajectories, i.e. cortical gyrification (CG) and thickness (CT). CG and CT was investigated in SZ patients (n = 82) and healthy controls (HC, n = 48) using 3 T structural magnetic resonance imaging. Illness insight in SZ patients was measured using the OSSTI scale, an instrument that provides information on two distinct dimensions of illness insight, i.e. treatment adherence (OSSTI-A) and identification of disease-related symptoms (OSSTI-I). CT and CG were computed using the Computational Anatomy Toolbox (CAT12). Whole-brain and regions-of-interest (ROI)-based analyses were performed. SZ patients showed higher CG in anterior cingulate, superior frontal and temporal gyrus and reduced CG in insular and superior frontal cortex when compared to HC. SZ patients showed decreased CT in pre- and paracentral, occipital, cingulate, frontoparietal and temporal regions. Illness insight in SZ patients was significantly associated with both CG and CT in the left inferior parietal lobule (OSSTI-A) and the right precentral gyrus (CG/OSSTI-A, CT/OSSTI-I). The data support a multi-parametric neuronal model with both pre- and postnatal brain developmental factors having an impact on illness insight in patients with SZ.

BackgroundAberrant brain connectivity during emotional processing, especially within the fronto-limbic pathway, is one of the hallmarks of major depressive disorder (MDD). However, a lack of systematic approaches in previous studies made it difficult to determine whether a specific alteration in brain connectivity reflects a cause, correlate, or effect of the disorder. The current study aimed to investigate neural mechanisms that correspond to disease, risk and resilience in major depression during implicit processing of emotion cues.MethodsForty-eight patients with MDD, 49 first-degree relatives of patients with MDD and 103 healthy controls performed a face-matching task during functional magnetic resonance imaging. We used dynamic causal modelling to estimate task-dependent effective connectivity at the subject level. Parametric empirical Bayes was then performed to quantify group differences in effective connectivity.ResultsDepressive pathology was associated with decreased effective connectivity from the left amygdala and left dorsolateral prefrontal cortex to the right fusiform gyrus, whereas familial risk for depression corresponded to decreased connectivity from the right orbitofrontal cortex to the left insula and from the left orbitofrontal cortex to the right fusiform gyrus. Resilience for depression was related to increased connectivity from the anterior cingulate cortex to the left dorsolateral prefrontal cortex.ConclusionsOur results suggest that the depressive state alters top-down control of higher visual regions during the processing of emotional faces, whereas increased connectivity within the cognitive control network promotes resilience to depression.

Background: Altered ventral striatal (vST) activation to reward expectancy is a well-established intermediate phenotype for psychiatric disorders, specifically schizophrenia (SZ). Preclinical research suggests that striatal alterations are related to a reduced inhibition by the hippocampal formation, but its role in human transdiagnostic reward-network dysfunctions is not well understood. Methods: We performed functional magnetic resonance imaging during reward processing in 728 individuals including healthy control subjects (n = 396), patients (SZ: n = 46; bipolar disorder: n = 45; major depressive disorder: n = 60), and unaffected first-degree relatives (SZ: n = 46; bipolar disorder: n = 50; major depressive disorder: n = 85). We assessed disorder-specific differences in functional vST-hippocampus coupling and transdiagnostic associations with dimensional measures of positive, negative, and cognitive symptoms. We also probed the genetic underpinning using polygenic risk scores for SZ in a subset of healthy participants (n = 295). Results: Functional vST-hippocampus coupling was 1) reduced in patients with SZ and bipolar disorder (pFWE < .05, small-volume corrected [SVC]); 2) associated transdiagnostically to dimensional measures of positive (pFWE = .01, SVC) and cognitive (pFWE = .02, SVC), but not negative, (pFWE > .05, SVC) symptoms; and 3) reduced in first-degree relatives of patients with SZ (pFWE = .017, SVC) and linked to the genetic risk for SZ in healthy participants (p = .035). Conclusions: We provide evidence that reduced vST-hippocampus coupling during reward processing is an endophenotype for SZ linked to positive and cognitive symptoms, supporting current preclinical models of the emergence of psychosis. Moreover, our data indicate that vST-hippocampus coupling is familial and linked to polygenic scores for SZ, supporting the use of this measure as an intermediate phenotype for psychotic disorders.

The relative roles of brainstem, thalamus and striatum in parkinsonism in schizophrenia spectrum disorder (SSD) patients are largely unknown. To determine whether topographical alterations of the brainstem, thalamus and striatum contribute to parkinsonism in SSD patients, we conducted structural magnetic resonance imaging (MRI) of SSD patients with (SSD-P, n = 35) and without (SSD-nonP, n = 64) parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥ 4 and n = 20). FreeSurfer v6.0 was used for segmentation of four brainstem regions (medulla oblongata, pons, superior cerebellar peduncle and midbrain), caudate nucleus, putamen and thalamus. Patients with parkinsonism had significantly smaller medulla oblongata (p = 0.01, false discovery rate (FDR)-corrected) and putamen (p = 0.02, FDR-corrected) volumes when compared to patients without parkinsonism. Across the entire patient sample (n = 99), significant negative correlations were identified between (a) medulla oblongata volumes and both SAS total (p = 0.034) and glabella-salivation (p = 0.007) scores, and (b) thalamic volumes and both SAS total (p = 0.033) and glabella-salivation (p = 0.007) scores. These results indicate that brainstem and thalamic structures as well as basal ganglia-based motor circuits play a crucial role in the pathogenesis of parkinsonism in SSD.

Mental disorders are widespread and a major public health problem. The risk of developing a mental disorder at some point in life is around 40%. Therefore, mental disorders are among the most common diseases. Despite the introduction of newer psychotropic drugs, disorder-specific psychotherapy and stimulation techniques, many of those affected still show insufficient symptom remission and a chronic course of the disorder. Conceptual and technological progress in recent years has enabled a new, more flexible and personalized form of mental health care. Both the traditional therapeutic concepts and newer decentralized, modularly structured, track units, together with innovative digital technologies, will offer individualized therapeutic options in order to alleviate symptoms and improve quality of life of patients with mental illnesses. The primary goal of closely combining inpatient care concepts with innovative technologies is to provide comprehensive therapy and aftercare concepts for all individual needs of patients with mental disorders. Last but not least, this also ensures that specialist psychiatric treatment is available regardless of location. In twenty-first century psychiatry, modern care structures must be effectively linked to the current dynamics of digital transformation. This narrative review is dedicated to the theoretical and practical aspects of a cross-sectoral treatment system combined with innovative digital technologies in the psychiatric-psychotherapeutic field. The authors aim to illuminate these therapy modalities using the example of the Central Institute of Mental Health in Mannheim.Psychische Erkrankungen sind weit verbreitet und ein bedeutendes Problem des allgemeinen Gesundheitswesens. Das Risiko, irgendwann im Laufe des Lebens eine psychische Erkrankung zu entwickeln, liegt bei rund 40 %. Psychische Erkrankungen zählen damit zu den epidemiologisch bedeutsamsten Erkrankungen. Trotz der Einführung neuerer Psychopharmaka, störungsspezifischer Psychotherapie und Stimulationstechniken zeigen viele der Betroffenen immer noch eine unzureichende Symptomremission und einen chronischen Verlauf. Durch den konzeptuellen und technischen Fortschritt der letzten Jahre wird eine neue, flexiblere und personalisierte Form der fachpsychiatrischen Patientenversorgung ermöglicht. Sowohl die traditionellen Therapie- und Organisationskonzepte als auch neuere dezentral arbeitende, modular aufgebaute, stationär-teilstationär-ambulante Einheiten werden zusammen mit innovativen digitalen Technologien vielen betroffenen Menschen mit psychischen Erkrankungen individualisierte Therapieoptionen bieten, welche ihre Symptome bestmöglich lindern und ihre Lebensqualität erheblich verbessern könnten. Das primäre Ziel der engen Verknüpfung von modernen Versorgungskonzepten und innovativen Technologien ist es, ein umfassendes Therapie- und Nachsorgekonzept (innerhalb und außerhalb der Klinik) für die individuellen Bedürfnisse von Menschen mit psychischer Erkrankung bereitzustellen. Nicht zuletzt wird dadurch auch eine ortsunabhängige Verfügbarkeit der fachärztlichen Behandlung erreicht. In der Psychiatrie des 21. Jahrhunderts müssen moderne Versorgungsstrukturen mit der aktuellen Dynamik der digitalen Transformation effektiv verknüpft werden. Die vorliegende selektive Übersichtsarbeit widmet sich den theoretischen und praktischen Gesichtspunkten eines sektorenübergreifenden Behandlungssystems kombiniert mit innovativen digitalen Technologien im psychiatrisch-psychotherapeutischen Fachbereich am Beispiel des Zentralinstituts für Seelische Gesundheit in Mannheim.

Among research disciplines, neuroscience has introduced the most fundamental changes in the way in which mental disease states are conceptualized and pursued. Nowhere is this more obvious than in translational medicine. The slow, arduous empirical process of finding new treatments must be properly incentivized for this work to be done by the current and next generation of psychiatric neuroscientists. Here, the toolboxes such as evolving biomarkers (e.g., imaging, transomic and functional biomarkers) genetics are discussed in relation to translational issues in mental diseases.