Variation in moment-to-moment brain state engagement changes across development and contributes to individual differences in executive function.

Neural variability, or variation in brain signals, facilitates dynamic brain responses to ongoing demands. This flexibility is important during development from childhood to young adulthood, a period characterized by rapid changes in experience. However, little is known about how variability in the engagement of recurring brain states changes during development. Such investigations would require the continuous assessment of multiple brain states concurrently. Here, we leverage a new computational framework to study state engagement variability (SEV) during development. A consistent pattern of SEV changing with age was identified across cross-sectional and longitudinal datasets (N>3000). SEV developmental trajectories stabilize around mid-adolescence, with timing varying by sex and brain state. SEV successfully predicts executive function (EF) in youths from an independent dataset. Worse EF is further linked to alterations in SEV development. These converging findings suggest SEV changes over development, allowing individuals to flexibly recruit various brain states to meet evolving needs.

Regional patterns of human cortex development correlate with underlying neurobiology.

Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of the variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.

A robust brain network for sustained attention from adolescence to adulthood that predicts later substance use.

Substance use, including cigarettes and cannabis, is associated with poorer sustained attention in late adolescence and early adulthood. Previous studies were predominantly cross-sectional or under-powered and could not indicate if impairment in sustained attention was a predictor of substance use or a marker of the inclination to engage in such behavior. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1000 participants. Behaviors and brain connectivity associated with diminished sustained attention at age 14 predicted subsequent increases in cannabis and cigarette smoking, establishing sustained attention as a robust biomarker for vulnerability to substance use. Individual differences in network strength relevant to sustained attention were preserved across developmental stages and sustained attention networks generalized to participants in an external dataset. In summary, brain networks of sustained attention are robust, consistent, and able to predict aspects of later substance use.

Automatic rating of incomplete hippocampal inversions evaluated across multiple cohorts.

Incomplete Hippocampal Inversion (IHI), sometimes called hippocampal malrotation, is an atypical anatomical pattern of the hippocampus found in about 20% of the general population. IHI can be visually assessed on coronal slices of T1 weighted MR images, using a composite score that combines four anatomical criteria. IHI has been associated with several brain disorders (epilepsy, schizophrenia). However, these studies were based on small samples. Furthermore, the factors (genetic or environmental) that contribute to the genesis of IHI are largely unknown. Large-scale studies are thus needed to further understand IHI and their potential relationships to neurological and psychiatric disorders. However, visual evaluation is long and tedious, justifying the need for an automatic method. In this paper, we propose, for the first time, to automatically rate IHI. We proceed by predicting four anatomical criteria, which are then summed up to form the IHI score, providing the advantage of an interpretable score. We provided an extensive experimental investigation of different machine learning methods and training strategies. We performed automatic rating using a variety of deep learning models ("conv5-FC3", ResNet and "SECNN") as well as a ridge regression. We studied the generalization of our models using different cohorts and performed multi-cohort learning. We relied on a large population of 2,008 participants from the IMAGEN study, 993 and 403 participants from the QTIM and QTAB studies as well as 985 subjects from the UKBiobank. We showed that deep learning models outperformed a ridge regression. We demonstrated that the performances of the "conv5-FC3" network were at least as good as more complex networks while maintaining a low complexity and computation time. We showed that training on a single cohort may lack in variability while training on several cohorts improves generalization (acceptable performances on all tested cohorts including some that are not included in training). The trained models will be made publicly available should the manuscript be accepted.

Personality, Social Factors, Brain Functioning, Familial Risk, and Trajectories of Alcohol Misuse in Adolescence.

Importance: The development of an alcohol use disorder in adolescence is associated with increased risk of future alcohol dependence. The differential associations of risk factors with alcohol use over the course of 8 years are important for preventive measures. Objective: To determine the differential associations of risk-taking aspects of personality, social factors, brain functioning, and familial risk with hazardous alcohol use in adolescents over the course of 8 years. Design, Setting, and Participants: The IMAGEN multicenter longitudinal cohort study included adolescents recruited from European schools in Germany, the UK, France, and Ireland from January 2008 to January 2019. Eligible participants included those with available neuropsychological, self-report, imaging, and genetic data at baseline. Adolescents who were ineligible for magnetic resonance imaging or had serious medical conditions were excluded. Data analysis was conducted from July 2021 to September 2022. Exposure: Personality testing, psychosocial factors, brain functioning, and familial risk of alcohol misuse. Main Outcome and Measures: Hazardous alcohol use as measured with the Alcohol Use Disorders Identification Test scores, a main planned outcome of the IMAGEN study. Alcohol misuse trajectories at ages 14, 16, 19, and 22 years were modeled using latent growth curve models. Results: A total of 2240 adolescents (1110 female [49.6%] and 1130 male [50.4%]) were included in the study. There was a significant negative association of psychosocial resources (ß = -0.29; SE = 0.03; P < .001) with the general risk of alcohol misuse as well as a significant positive association of the risk-taking aspects of personality with the intercept (ß = 0.19; SE = 0.04; P < .001). Furthermore, there were significant positive associations of the social domain (ß = 0.13; SE = 0.02; P < .001) and the personality domain (ß = 0.07; SE = 0.02; P < .001) with trajectories of alcohol misuse development over time (slope). Family history of substance misuse was negatively associated with general risk of alcohol misuse (ß = -0.04; SE = 0.02; P = .045) and its development over time (ß = -0.03; SE = 0.01; P = .01). Brain functioning showed no significant association with intercept or slope of alcohol misuse in the model. Conclusions and Relevance: The findings of this cohort study suggest known risk factors of adolescent drinking may contribute differentially to future alcohol misuse. This approach may inform more individualized preventive interventions.

[Climate crisis and psychiatry]. / Klimakrise und Psychiatrie.

BACKGROUND: The climate crisis is increasingly leading to negative consequences for mental health and is of growing importance for psychiatric and psychotherapeutic care. OBJECTIVE: The effects of the climate crisis on mental health and its significance for psychiatric and psychotherapeutic care are presented. Recommendations for sustainability in psychiatric and psychotherapeutic practice are provided. MATERIAL AND METHODS: A narrative review of the literature was conducted for this article. RESULTS: The climate crisis has direct, indirect and intersectional negative effects on mental health. Sustainable and preventive recommendations for the practice include promoting health literacy, faster access to psychotherapy and online counselling, supporting social networks, promoting employment and reducing poverty, homelessness and social isolation. It is recommended to increase the proportion of outpatient care and to streamline administrative processes. The use of disposable products should be minimized and the application of instrumental diagnostics and materials should be optimized according to guidelines. Digital interventions should be considered more frequently in the clinical practice and sustainable facility management should be improved. Access to green spaces for the general population and patients should be facilitated. CONCLUSION: Due to the negative impact of the climate crisis on mental health, sustainability should be promoted in psychiatric and psychotherapeutic care.

Coupled changes between ruminating thoughts and resting-state brain networks during the transition into adulthood.

Perseverative negative thoughts, known as rumination, might arise from emotional challenges and preclude mental health when transitioning into adulthood. Due to its multifaceted nature, rumination can take several ruminative response styles, that diverge in manifestations, severity, and mental health outcomes. Still, prospective ruminative phenotypes remain elusive insofar. Longitudinal study designs are ideal for stratifying ruminative response styles, especially with resting-state functional MRI whose setup naturally elicits people's ruminative traits. Here, we considered self-rated questionnaires on rumination and psychopathology, along with resting-state functional MRI data in 595 individuals assessed at age 18 and 22 from the IMAGEN cohort. We conducted independent component analysis to characterize eight single static resting-state functional networks in each subject and session and furthermore conducted a dynamic analysis, tackling the time variations of functional networks during the entire scanning time. We then investigated their longitudinal mediation role between changes in three ruminative response styles (reflective pondering, brooding, and depressive rumination) and changes in internalizing and co-morbid externalizing symptoms. Four static and two dynamic networks longitudinally differentiated these ruminative styles and showed complemental sensitivity to internalizing and co-morbid externalizing symptoms. Among these networks, the right frontoparietal network covaried with all ruminative styles but did not play any mediation role towards psychopathology. The default mode, the salience, and the limbic networks prospectively stratified these ruminative styles, suggesting that maladaptive ruminative styles are associated with altered corticolimbic function. For static measures, only the salience network played a longitudinal causal role between brooding rumination and internalizing symptoms. Dynamic measures highlighted the default-mode mediation role between the other ruminative styles and co-morbid externalizing symptoms. In conclusion, we identified the ruminative styles' psychometric and neural outcome specificities, supporting their translation into applied research on young adult mental healthcare.

Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modeling.

The balance of excitation and inhibition is a key functional property of cortical microcircuits which changes through the lifespan. Adolescence is considered a crucial period for the maturation of excitation-inhibition balance. This has been primarily observed in animal studies, yet human in vivo evidence on adolescent maturation of the excitation-inhibition balance at the individual level is limited. Here, we developed an individualized in vivo marker of regional excitation-inhibition balance in human adolescents, estimated using large-scale simulations of biophysical network models fitted to resting-state functional magnetic resonance imaging data from two independent cross-sectional (N = 752) and longitudinal (N = 149) cohorts. We found a widespread relative increase of inhibition in association cortices paralleled by a relative age-related increase of excitation, or lack of change, in sensorimotor areas across both datasets. This developmental pattern co-aligned with multiscale markers of sensorimotor-association differentiation. The spatial pattern of excitation-inhibition development in adolescence was robust to inter-individual variability of structural connectomes and modeling configurations. Notably, we found that alternative simulation-based markers of excitation-inhibition balance show a variable sensitivity to maturational change. Taken together, our study highlights an increase of inhibition during adolescence in association areas using cross sectional and longitudinal data, and provides a robust computational framework to estimate microcircuit maturation in vivo at the individual level.

Investigating grey matter volumetric trajectories through the lifespan at the individual level.

Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14-23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.

[Challenges in the treatment of opioid dependence]. / Aktuelle Herausforderungen in der Behandlung der Opioidabhängigkeit.

BACKGROUND: The number of persons using opioids has increased worldwide in the last decade, particularly the use of opioid analgesics in North America and Africa. In Germany, the prevalence of heroin addiction has remained relatively stable. METHOD: Narrative review of the literature. RESULTS: Opioid-assisted maintenance treatment (OMT) with the established substances methadone, levomethadone, slow-release morphine and buprenorphine is recommended as the first-line treatment for heroin dependence. The OMT reduces the use of heroin, mortality and individual suffering and improves the quality of life and physical health. A diamorphine and heroine-assisted treatment is an option for people who do not benefit from conventional OMT. An alternative to the use of diamorphine could be treatment with hydromorphone hydrochloride. The regulations on carrying out maintenance treatment in the Controlled Substances Prescription Act and the guidelines of the Federal Medical Association in Germany have been loosened based on the experiences of the COVID-19 pandemic, for example with respect to take-home prescriptions. There is an ongoing intensive discussion on how to deal with the decreasing number of outpatient clinics offering OMT. CONCLUSION: The first-line treatment for opioid addiction is opioid-assisted substitution treatment, including diamorphine and heroin-assisted treatment. Long-acting depot medications and implants still play a subordinate role.

Level of structural integration in people with schizophrenia and schizoaffective disorders - applicability and associations with clinical parameters.

Introduction: The psychic structure of people with psychosis has been the subject of theoretical and qualitative considerations. However, it has not been sufficiently studied quantitatively. Therefore, the aim of this study was to explore the structural abilities of people diagnosed with schizophrenia and schizoaffective psychosis using the Levels of Structural Integration Axis of the Operationalized Psychodynamic Diagnosis System (OPD-2-LSIA). The study aimed to determine possible associations between the OPD-2-LSIA and central parameters of illness. Additionally, possible structural differences between people diagnosed with schizophrenia and schizoaffective psychosis were tested. Methods: This cross-sectional study included 129 outpatients with schizophrenia or schizoaffective disorders. Measures of structural integration, symptom load, severity of illness, cognition, and social functioning were obtained. Descriptive statistics were used to analyze the overall structural level and the structural dimensions. Correlation coefficients were computed to measure the associations between OPD-2-LSIA and variables regarding the severity of illness and psychosocial functioning. Regression models were used to measure the influence of illness-related variables on OPD-2-LSIA, and the influence of OPD-2-LSIA on psychosocial functioning. Participants diagnosed with schizophrenia and schizoaffective disorders were examined with regard to possible group differences. Results: The results of the OPD-2-LSIA showed that the overall structural level was between 'moderate to low' and 'low level of structural integration'. Significant correlations were found between OPD-2-LSIA and psychotic symptoms (but not depressive symptoms), as well as between OPD-2-LSIA and psychosocial functioning. It was found that variables related to severity of illness had a significant impact on OPD-2-LSIA, with psychotic, but not depressive symptoms being significant predictors. OPD-2-LSIA was found to predict psychosocial functioning beyond symptoms and cognition. No significant differences were found between participants with schizophrenia and schizoaffective psychosis. There was also no correlation found between OPD-2-LSIA and depressive symptomatology (except for the subdimension Internal communication). Discussion: Contrary to theoretical assumptions, the results of the study show a heterogenous picture of the psychic structure of people with psychosis. The associations between OPD-2-LSIA and severity of illness, particularly psychotic symptomatology, as well as the influence of OPD-2-LSIA on psychosocial functioning, are discussed.

Prevalence of mental, behavioural or neurodevelopmental disorders according to the International Classification of Diseases 11: a scoping review protocol.

INTRODUCTION: Due to a change in diagnostic prerequisites and the inclusion of novel diagnostic entities, the implementation of the 11th revision of the International Classification of Diseases (ICD-11) will presumably change prevalence rates of specific mental, behavioural or neurodevelopmental disorders and result in an altered prevalence rate for this grouping overall. This scoping review aims to summarise the characteristics of primary studies examining the prevalence of mental, behavioural or neurodevelopmental disorders based on ICD-11 criteria. The knowledge attained through this review will primarily characterise the methodological approaches of this research field and additionally assist in deciding which psychiatric diagnoses are-given the current literature-most relevant for subsequent systematic reviews and meta-analyses intended to approximate the magnitude of prevalence rates while providing a first glimpse of the range of expected (differences in) prevalence rates in these conditions. METHODS AND ANALYSIS: MEDLINE, Embase, Web of Science and PsycINFO will be searched from 2011 to present without any language filters. This scoping review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review guidelines.We will consider (a) cross-sectional and longitudinal studies (b) focusing on the prevalence rates of mental, behavioural or neurodevelopmental disorders (c) using ICD-11 criteria for inclusion. The omission of (a) case numbers and sample size, (b) study period and period of data collection or (c) diagnostic procedures on full-text level is considered an exclusion criterion.This screening will be conducted by two reviewers independently from one another and a third reviewer will be consulted with disagreements. Data extraction and synthesis will focus on outlining methodological aspects. ETHICS AND DISSEMINATION: We intend to publish our review in a scientific journal. As the primary data are publicly available, we do not require research ethics approval.

Correlation of striatal dopamine D2/3 receptor availability with GABA level in the anterior cingulate cortex in healthy controls but not in alcohol-dependent subjects and individuals at high risk: A multimodal magnetic resonance spectroscopy and positron emission tomography study.

BACKGROUND: The association of impaired dopaminergic neurotransmission with the development and maintenance of alcohol use disorder is well known. More specifically, reduced dopamine D2/3 receptors in the striatum of subjects with alcohol dependence (AD) compared to healthy controls have been found in previous studies. Furthermore, alterations of gamma-aminobutyric acid (GABA) and glutamate (Glu) levels in the anterior cingulate cortex (ACC) of AD subjects have been documented in several studies. However, the interaction between cortical Glu levels and striatal dopamine D2/3 receptors has not been investigated in AD thus far. METHODS: This study investigated dopamine D2/3 receptor availability via 18F-fallypride positron emission tomography (PET) and GABA as well as Glu levels via magnetic resonance spectroscopy (MRS) in 19 detoxified AD subjects, 18 healthy controls (low risk, LR) controls and 19 individuals at high risk (HR) for developing AD, carefully matched for sex, age and smoking status. RESULTS: We found a significant negative correlation between GABA levels in the ACC and dopamine D2/3 receptor availability in the associative striatum of LR but not in AD or HR individuals. Contrary to our expectations, we did not observe a correlation between Glu concentrations in the ACC and striatal D2/3 receptor availability. CONCLUSIONS: The results may reflect potential regulatory cortical mechanisms on mesolimbic dopamine receptors and their disruption in AD and individuals at high risk, mirroring complex neurotransmitter interactions associated with the pathogenesis of addiction. This is the first study combining 18F-fallypride PET and MRS in AD subjects and individuals at high risk.

A framework for a brain-derived nosology of psychiatric disorders.

Current psychiatric diagnoses are not defined by neurobiological measures which hinders the development of therapies targeting mechanisms underlying mental illness 1,2 . Research confined to diagnostic boundaries yields heterogeneous biological results, whereas transdiagnostic studies often investigate individual symptoms in isolation. There is currently no paradigm available to comprehensively investigate the relationship between different clinical symptoms, individual disorders, and the underlying neurobiological mechanisms. Here, we propose a framework that groups clinical symptoms derived from ICD-10/DSM-V according to shared brain mechanisms defined by brain structure, function, and connectivity. The reassembly of existing ICD-10/DSM-5 symptoms reveal six cross-diagnostic psychopathology scores related to mania symptoms, depressive symptoms, anxiety symptoms, stress symptoms, eating pathology, and fear symptoms. They were consistently associated with multimodal neuroimaging components in the training sample of young adults aged 23, the independent test sample aged 23, participants aged 14 and 19 years, and in psychiatric patients. The identification of symptom groups of mental illness robustly defined by precisely characterized brain mechanisms enables the development of a psychiatric nosology based upon quantifiable neurobiological measures. As the identified symptom groups align well with existing diagnostic categories, our framework is directly applicable to clinical research and patient care.

Distinct personality profiles associated with disease risk and diagnostic status in eating disorders.

BACKGROUND: Personality traits have been associated with eating disorders (EDs) and comorbidities. However, it is unclear which personality profiles are premorbid risk rather than diagnostic markers. METHODS: We explored associations between personality and ED-related mental health symptoms using canonical correlation analyses. We investigated personality risk profiles in a longitudinal sample, associating personality at age 14 with onset of mental health symptoms at ages 16 or 19. Diagnostic markers were identified in a sample of young adults with anorexia nervosa (AN, n = 58) or bulimia nervosa (BN, n = 63) and healthy controls (n = 47). RESULTS: Two significant premorbid risk profiles were identified, successively explaining 7.93 % and 5.60 % of shared variance (Rc2). The first combined neuroticism (canonical loading, rs = 0.68), openness (rs = 0.32), impulsivity (rs = 0.29), and conscientiousness (rs = 0.27), with future onset of anxiety symptoms (rs = 0.87) and dieting (rs = 0.58). The other, combined lower agreeableness (rs = -0.60) and lower anxiety sensitivity (rs = -0.47), with future deliberate self-harm (rs = 0.76) and purging (rs = 0.55). Personality profiles associated with "core psychopathology" in both AN (Rc2 = 80.56 %) and BN diagnoses (Rc2 = 64.38 %) comprised hopelessness (rs = 0.95, 0.87) and neuroticism (rs = 0.93, 0.94). For BN, this profile also included impulsivity (rs = 0.60). Additionally, extraversion (rs = 0.41) was associated with lower depressive risk in BN. LIMITATIONS: The samples were not ethnically diverse. The clinical cohort included only females. There was non-random attrition in the longitudinal sample. CONCLUSIONS: The results suggest neuroticism and impulsivity as risk and diagnostic markers for EDs, with neuroticism and hopelessness as shared diagnostic markers. They may inform the design of more personalised prevention and intervention strategies.

Unraveling robust brain-behavior links of depressive complaints through granular network models for understanding heterogeneity.

BACKGROUND: Depressive symptoms are highly prevalent, present in heterogeneous symptom patterns, and share diverse neurobiological underpinnings. Understanding the links between psychopathological symptoms and biological factors is critical in elucidating its etiology and persistence. We aimed to evaluate the utility of using symptom-brain network models to parse the heterogeneity of depressive complaints in a large adolescent sample. METHODS: We used data from the third wave of the IMAGEN study, a multi-center panel cohort study involving 1317 adolescents (52.49 % female, mean ± SD age = 18.5 ± 0.7). Two network models were estimated: one including an overall depressive symptom severity sum score based on the Adolescent Depression Rating Scale (ADRS), and one incorporating individual ADRS item scores. Both networks included measures of cortical thickness in several regions (insula, cingulate, mOFC, fusiform gyrus) and hippocampal volume derived from neuroimaging. RESULTS: The network based on individual item scores revealed associations between cortical thickness measures and specific depressive complaints, obscured when using an aggregate depression severity score. Notably, the insula's cortical thickness showed negative associations with cognitive dysfunction (partial cor. = -0.15); the cingulate's cortical thickness showed negative associations with feelings of worthlessness (partial cor. = -0.10), and mOFC was negatively associated with anhedonia (partial cor. = -0.05). LIMITATIONS: This cross-sectional study relied on the self-reported assessment of depression complaints and used a non-clinical sample with predominantly healthy participants (19 % with depression or sub-threshold depression). CONCLUSIONS: This study showcases the utility of network models in parsing heterogeneity in depressive complaints, linking individual complaints to specific neural substrates. We outline the next steps to integrate neurobiological and cognitive markers to unravel MDD's phenotypic heterogeneity.