Within-person biological mechanisms of mood variability in childhood and adolescence.

Mood variability, the day-to-day fluctuation in mood, differs between individuals and develops during adolescence. Because adolescents show higher mood variability and average mood than children and adults, puberty might be a potential biological mechanism underlying this increase. The goal of this preregistered developmental study was to examine the neural and hormonal underpinnings of adolescent-specific within-person changes in mood variability, with a specific focus on testosterone, cortisol, pubertal status, and resting-state functional brain connectivity. Data from two longitudinal cohorts were used: the L-CID twin study (aged 7-13, N at the first timepoint = 258) and the accelerated Leiden Self-Concept study (SC; aged 11-21, N at the first timepoint = 138). In both studies resting-state functional magnetic resonance imaging (rs-fMRI) data was collected, as well as daily mood. Additionally, in the SC study self-reported puberty testosterone and cortisol were collected. Random intercept cross-lagged panel models (RI-CLPM) were used to study the within-person relations between these biological measures and mood variability and average mood. Mood variability and average mood peaked in adolescence and testosterone levels and self-reported puberty also showed an increase. Connectivity between prefrontal cortex (dlPFC and vmPFC) and subcortical regions (caudate, amygdala) decreased across development. Moreover, higher testosterone predicted average negative mood at the next time point, but not vice versa. Further, stronger vmPFC-amygdala functional connectivity predicted decreases in mood variability. Here, we show that brain connectivity during development is an important within-person biological mechanism of the development of mood in adolescents. PRACTITIONER POINTS: Mood variability peaks in adolescence. Within-person changes in testosterone predict within-person changes in mood. Within-person changes in vmPFC-amygdala connectivity predict within-person changes in mood variability.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

The role of autism and alexithymia traits in behavioral and neural indicators of self-concept and self-esteem in adolescence.

LAY ABSTRACT: Developing a positive view of the self is important for maintaining a good mental health, as feeling negative about the self increases the risk of developing internalizing symptoms such as feelings of depression and anxiety. Even though autistic individuals regularly struggle with these internalizing feelings, and both self-concept and internalizing feelings are known to develop during adolescence, there is a lack of studies investigating the development of positive self-concept and self-esteem in autistic adolescents. Here, we studied academic, physical, and prosocial self-concept as well as self-esteem in adolescent males with and without autism on both the behavioral and neural level. We additionally focused on similarities in one's own and peers' perspectives on the self, and we assessed a potential role of alexithymia (i.e. having trouble identifying and describing one's feelings) in developing a more negative view of the self. Results showed that there were no group differences in self-esteem, self-concept, or underlying neural activation. This shows that autistic adolescent males use the same neural processes when they evaluate their traits. However, regardless of clinical diagnosis, a higher number of autism traits was related to a less positive physical and prosocial self-concept, whereas more difficulty identifying one's feelings was related to lowered self-esteem and less activation in medial prefrontal cortex during self-evaluations. Therefore, in treatment of autistic adolescents with low self-esteem, it is important to take into account and possibly aim to improve alexithymic traits as well.

Developing body estimation in adolescence is associated with neural regions that support self-concept.

Both self-concept, the evaluation of who you are, and the physical body undergo changes throughout adolescence. These two processes might affect the development of body image, a complex construct that comprises one's thoughts, feelings, and perception of one's body. This study aims to better understand the development of body image in relation to self-concept development and its neural correlates. Adolescents (aged 11-24) from the longitudinal Leiden Self-Concept study were followed for three consecutive years (NT1 = 160, NT2 = 151, and NT3 = 144). Their body image was measured using a figure rating scale and body dissatisfaction questionnaire. Body estimation was calculated based on figure ratings relative to their actual body mass index (BMI). Additionally, participants evaluated their physical appearance traits in an functional magnetic resonance imaging (fMRI) task. Results revealed that body estimation and body dissatisfaction increased with age. Heightened inferior parietal lobe (IPL) activation during physical self-evaluation was associated with lower body estimation, meaning that the neural network involved in thinking about one's physical traits is more active for individuals who perceive themselves as larger than they are. IPL activity showed continued development during adolescence, suggesting an interaction between neural development and body perception. These findings highlight the complex interplay between affective, perceptual, and biological factors in shaping body image.

Can adolescents be game changers for 21st-century societal challenges?

Adolescents growing up in the 21st century face novel challenges that affect today's adolescents differently compared with previous generations. Adolescents' prosocial values and social engagement can contribute in unique ways to combatting societal challenges. Participatory research provides tools to transform adolescents' prosocial motivations into drivers for societal change.

Trust in adolescence: Development, mechanisms and future directions.

Trust is the glue of society. While the trust we place in close others is crucial for our wellbeing, trust in strangers is important to fulfill needs that families and friends cannot provide. Adolescence is an important phase for the development of trust in strangers, because the social world of adolescents expands tremendously. We provide an overview of the development of trust in adolescence by reviewing studies that used the trust game, an experimental paradigm to measure trust between dyads during monetary exchange. We start from the notion that trust is a form of social reinforcement learning in which prior beliefs about the trustworthiness of others are continuously updated by new information. Within this framework, development in adolescence is characterized by increasing uncertainty of prior beliefs, a greater tolerance of uncertainty, and a greater tendency to seek and use new information. Accordingly, there is evidence for an increase in initial trust and better adaptation of trust during repeated interactions. Childhood psychological and social-economic adversity may impact this development negatively. To further our understanding of these individual differences, we suggest ways in which the trust game can be enriched to capture trust dilemmas that are relevant to youth with diverse backgrounds.

Observational reinforcement learning in children and young adults.

Observational learning is essential for the acquisition of new behavior in educational practices and daily life and serves as an important mechanism for human cognitive and social-emotional development. However, we know little about its underlying neurocomputational mechanisms from a developmental perspective. In this study we used model-based fMRI to investigate differences in observational learning and individual learning between children and younger adults. Prediction errors (PE), the difference between experienced and predicted outcomes, related positively to striatal and ventral medial prefrontal cortex activation during individual learning and showed no age-related differences. PE-related activation during observational learning was more pronounced when outcomes were worse than predicted. Particularly, negative PE-coding in the dorsal medial prefrontal cortex was stronger in adults compared to children and was associated with improved observational learning in children and adults. The current findings pave the way to better understand observational learning challenges across development and educational settings.

Mood variability during adolescent development and its relation to sleep and brain development.

Mood swings, or mood variability, are associated with negative mental health outcomes. Since adolescence is a time when mood disorder onset peaks, mood variability during this time is of significant interest. Understanding biological factors that might be associated with mood variability, such as sleep and structural brain development, could elucidate the mechanisms underlying mood and anxiety disorders. Data from the longitudinal Leiden self-concept study (N = 191) over 5 yearly timepoints was used to study the association between sleep, brain structure, and mood variability in healthy adolescents aged 11-21 at baseline in this pre-registered study. Sleep was measured both objectively, using actigraphy, as well as subjectively, using a daily diary self-report. Negative mood variability was defined as day-to-day negative mood swings over a period of 5 days after an MRI scan. It was found that negative mood variability peaked in mid-adolescence in females while it linearly increased in males, and average negative mood showed a similar pattern. Sleep duration (subjective and objective) generally decreased throughout adolescence, with a larger decrease in males. Mood variability was not associated with sleep, but average negative mood was associated with lower self-reported energy. In addition, higher thickness in the dorsolateral prefrontal cortex (dlPFC) compared to same-age peers, suggesting a delayed thinning process, was associated with higher negative mood variability in early and mid-adolescence. Together, this study provides an insight into the development of mood variability and its association with brain structure.

From developmental neuroscience to policy: A novel framework based on participatory research.

Insights from developmental neuroscience are not always translated to actionable policy decisions. In this review, we explore the potential of bridging the gap between developmental neuroscience and policy through youth participatory research approaches. As the current generation of adolescents lives in an increasingly complex and rapidly changing society, their lived experiences are crucial for both research and policy. Moreover, their active involvement holds significant promise, given their heightened creativity and need to contribute. We therefore advocate for a transdisciplinary framework that fosters collaboration between developmental scientists, adolescents, and policy makers in addressing complex societal challenges. We highlight the added value of adolescents' lived experiences in relation to two pressing societal issues affecting adolescents' mental health: performance pressure and social inequality. By integrating firsthand lived experiences with insights from developmental neuroscience, we provide a foundation for progress in informed policy decisions.

Pregnancy renders anatomical changes in hypothalamic substructures of the human brain that relate to aspects of maternal behavior.

Animal studies have shown that pregnancy is associated with neural adaptations that promote maternal care. The hypothalamus represents a central structure of the mammalian maternal brain and hormonal priming of specific hypothalamic nuclei plays a key role in the induction and expression of maternal behavior. In humans, we have previously demonstrated that becoming a mother involves changes in grey matter anatomy, primarily in association areas of the cerebral cortex. In the current study, we investigated whether pregnancy renders anatomical changes in the hypothalamus. Using an advanced delineation technique, five hypothalamic substructures were defined in longitudinal MRI scans of 107 women extracted from two prospective pre-conception cohort studies, including 50 women who were scanned before and after pregnancy and 57 nulliparous control women scanned at a similar time interval. We showed that becoming a mother is associated with volume reductions in the anterior-superior, superior tuberal and posterior hypothalamus. In addition, these structural changes related to hormonal levels during pregnancy and specific aspects of self-reported maternal behavior in late pregnancy, including maternal-fetal attachment and nesting behavior. These findings show that pregnancy leads to changes in hypothalamic anatomy and suggest that these contribute to the development of maternal behavior in humans, supporting the conservation of key aspects of maternal brain circuitry and their role in maternal behavior across species.

Growing Up Together in Society (GUTS): A team science effort to predict societal trajectories in adolescence and young adulthood.

Our society faces a great diversity of opportunities for youth. The 10-year Growing Up Together in Society (GUTS) program has the long-term goal to understand which combination of measures best predict societal trajectories, such as school success, mental health, well-being, and developing a sense of belonging in society. Our leading hypothesis is that self-regulation is key to how adolescents successfully navigate the demands of contemporary society. We aim to test these questions using socio-economic, questionnaire (including experience sampling methods), behavioral, brain (fMRI, sMRI, EEG), hormonal, and genetic measures in four large cohorts including adolescents and young adults. Two cohorts are designed as test and replication cohorts to test the developmental trajectory of self-regulation, including adolescents of different socioeconomic status thereby bridging individual, family, and societal perspectives. The third cohort consists of an entire social network to examine how neural and self-regulatory development influences and is influenced by whom adolescents and young adults choose to interact with. The fourth cohort includes youth with early signs of antisocial and delinquent behavior to understand patterns of societal development in individuals at the extreme ends of self-regulation and societal participation, and examines pathways into and out of delinquency. We will complement the newly collected cohorts with data from existing large-scale population-based and case-control cohorts. The study is embedded in a transdisciplinary approach that engages stakeholders throughout the design stage, with a strong focus on citizen science and youth participation in study design, data collection, and interpretation of results, to ensure optimal translation to youth in society.

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation.

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.