Identification and external validation of a problem cannabis risk network.

Background: Cannabis use is common, particularly during emerging adulthood when brain development is ongoing, and its use is associated with harmful outcomes for a subset of people. An improved understanding of the neural mechanisms underlying risk for problem-level use is critical to facilitate the development of more effective prevention and treatment approaches.

Methods: The current study applied a whole-brain, data-driven, machine-learning approach to identify neural features predictive of problem-level cannabis use in a non-clinical sample of college students (n=191, 58% female) based on reward task functional connectivity data.

Cognitive predictors of mental health trajectories are mediated by inferior frontal and occipital development during adolescence.

Laboratory studies show brain maturation involves synaptic pruning and cognitive development. Human studies suggest links between early cognitive performance and later mental health, but inconsistencies remain. It is unclear if specific brain regions mediate this relationship, and the molecular underpinnings are not well understood.

Hierarchical Neurocognitive Model of Externalizing and Internalizing Comorbidity.

Mounting evidence suggests hierarchical psychopathology factors underlying psychiatric comorbidity. However, the exact neurobiological characterizations of these multilevel factors remain elusive. In this study, leveraging the brain-behavior predictive framework with a 10-year longitudinal imaging-genetic cohort (IMAGEN, ages 14, 19 and 23, = 1,750), we constructed two neural factors underlying externalizing and internalizing symptoms, which were reproducible across six clinical and population-based datasets (ABCD, STRATIFY/ESTRA, ABIDE II, ADHD-200 and XiNan, from age 10 to age 36, = 3,765).

Relationships of eating behaviors with psychopathology, brain maturation and genetic risk for obesity in an adolescent cohort study.

Unhealthy eating, a risk factor for eating disorders (EDs) and obesity, often coexists with emotional and behavioral problems; however, the underlying neurobiological mechanisms are poorly understood. Analyzing data from the longitudinal IMAGEN adolescent cohort, we investigated associations between eating behaviors, genetic predispositions for high body mass index (BMI) using polygenic scores (PGSs), and trajectories (ages 14-23 years) of ED-related psychopathology and brain maturation. Clustering analyses at age 23 years ( = 996) identified 3 eating groups: restrictive, emotional/uncontrolled and healthy eaters.

Genome-wide association study unravels mechanisms of brain glymphatic activity.

Brain glymphatic activity, as indicated by diffusion-tensor imaging analysis along the perivascular space (ALPS) index, is involved in developmental neuropsychiatric and neurodegenerative diseases, but its genetic architecture is poorly understood. Here, we identified 17 unique genome-wide significant loci and 161 candidate genes linked to the ALPS-indexes in a discovery sample of 31,021 individuals from the UK Biobank. Seven loci were replicated in two independent datasets.

Impulsivity behaviors and white matter mediate the relationship between genetic risk for cannabis use disorder and early cannabis use in adolescents.

Background And Aim: Cannabis use disorder (CUD) is strongly influenced by genetic factors; however the mechanisms underpinning this association are not well understood. This study investigated whether a polygenic risk score (PRS) based on a genome-wide association study for CUD in adults predicts cannabis use in adolescents and whether the association can be explained by inter-individual variation in structural properties of brain white matter or risk-taking behaviors.

Design And Setting: Longitudinal and cross-sectional analyses using data from the IMAGEN cohort, a European longitudinal study integrating genetic, neuroimaging and behavioral measures.

Semi-Automated Assessment of Long-Term Olfactory Habituation in Using the Olfactory Arena.

Long-lasting memories are a core aspect of an animal's life. Such memories are characterized by unique molecular mechanisms and often unique circuitry, neither of which are completely understood in vivo. The deep knowledge of the identity and connectivity of neurons of the fruit fly , as well as the sophisticated genetic tools that allow in vivo perturbations and physiology monitoring, make it a remarkably useful organism in which to investigate the molecular mechanisms of long-term memories.

Personality changes during adolescence predict young adult psychosis proneness and mediate gene-environment interplays of schizophrenia risk.

Background: Psychotic symptoms in adolescence are associated with social adversity and genetic risk for schizophrenia. This gene-environment interplay may be mediated by personality, which also develops during adolescence. We hypothesized that (i) personality development predicts later Psychosis Proneness Signs (PPS), and (ii) personality traits mediate the association between genetic risk for schizophrenia, social adversities, and psychosis.

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.

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.

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).

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.

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.

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.

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 behaviour. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1,000 participants.