Developmental Cognitive Neuroscience

BACKGROUNDVariation in pubertal maturation relative to same-age, same-sex peers (pubertal timing) has been linked to increased risk for depressive symptoms during adolescence. This developmental period is also characterized by substantial reorganization of functional brain networks. However, how pubertal timing relates to resting-state functional connectivity (rsFC) changes and depression risk remains unclear. METHODSWe examined pubertal timing and rsFC associations in preadolescents aged 9-11 years from the Adolescent Brain Cognitive Development (ABCD) Study. Pubertal timing was estimated using a puberty age gap approach based on parent-reported physical development. Linear mixed-effects and Bayesian multilevel models were used to assess cross-sectional and longitudinal associations between pubertal timing and rsFC across large-scale functional brain networks. We also tested whether rsFC differences explained associations between pubertal timing and later depressive symptoms. RESULTSEarlier pubertal timing was associated with heterogeneous rsFC patterns, with stronger and more widespread effects in females. In females, earlier pubertal timing was associated with rsFC increases and decreases across sensory-motor and association networks, whereas in males, associations were more limited and localized to sensorimotor and cerebellar systems. Longitudinally, earlier pubertal timing in females predicted reductions in rsFC at the 2-year follow-up, with no significant associations in males. rsFC differences did not explain the pubertal timing and later depressive symptoms association. CONCLUSIONSPubertal timing is associated with sex-specific patterns of brain functional connectivity during early adolescence, with greater heterogeneity and broader network involvement in females. These findings suggest that pubertal maturation contributes to early reorganization of functional brain networks, although these changes did not explain subsequent depressive symptoms.

Resting state networks RSNs measured through functional connectivity FC emerge in utero and are detectable within hours of birth. Although neonatal growth metrics predict later neurodevelopmental outcomes and structural brain maturation their relationship to early functional network organization remains poorly understood. We examined associations between anthropometric growth metrics and resting state FC in a cohort of healthy near term and term born neonates using functional near infrared spectroscopy fNIRS acquired during the first few days of life. Task free fNIRS data were recorded in 121 neonates 67 males 55 percent mean postnatal age equals 25.6 hours mean gestational age equals 38.63 weeks. Based on birthweight percentiles 12 9 percent newborns were small for gestational age SGA and 13 11 percent were large for gestational age LGA. Growth metrics included birth weight for gestational age z score BGZ head circumference for gestational age z score HGZ birth weight for length z score BLZ and z scored Ponderal Index PIz. Whole brain FC was calculated as the mean Fisher Z transformed correlation across valid channel pairs. Channel wise associations were examined using general linear and linear mixed effects models controlling for gestational age postnatal age and sex. Linear and quadratic terms were tested and multiple comparisons were controlled using the false discovery rate. None of the anthropometric measures were associated with global FC however significant nonlinear quadratic relationships emerged at the channel pair level. BGZ B range equals negative 0.102 to negative 0.074 FDR corrected p less than 0.005 and PIz B range equals negative 0.088 to negative 0.074 FDR corrected p less than 0.001 demonstrated negative quadratic associations with inter and intra hemispheric connectivity such that newborns with both lower SGA and higher LGA growth values showed reduced FC relative to those with average growth. In contrast HGZ demonstrated positive quadratic associations B range equals 0.051 to 0.074 FDR corrected p less than 0.001 with infants at the lower and higher ends of the head size distribution exhibiting increased FC relative to infants near the mean. BLZ showed no significant associations after correction. Results indicate that early somatic growth is reflected in the organization of neonatal functional brain networks and that deviations from average growth whether smaller or larger are associated with altered regional connectivity. Findings suggest that neonatal growth metrics may provide an accessible marker of early brain health reflected in regionally specific functional connectivity patterns.

Adolescent psychopathology is partly rooted in measurable disruptions across key neural networks, yet the field still lacks an integrated, multimodal understanding of these brain-behavior links. Here, we examined how structural, microstructural, and functional measures across corticostriatal, corticolimbic, and executive control networks relate to psychopathology domains and explored how these associations predicted future psychosocial functioning. We used data from the Adolescent Brain Cognitive DevelopmentSM Study (n=5,408) and ran a regularized canonical correlation analysis to identify distinct modes of covariation between multiple brain measures and psychopathology domains when youth were 13-14 years old. The resulting canonical brain and psychopathology scores were used to predict school-related impairment one year later. First, higher diffusivity and decreased activation during a reward task across all three networks as well as lower corticostriatal surface area were related to higher broad psychopathology. Second, lower corticolimbic diffusivity, executive control volume and surface area, and cortical thickness across all three networks as well as higher corticostriatal and corticolimbic volumes were related to higher anxiety but lower externalizing. For the first mode, higher psychopathology scores predicted more school-related impairment one year later. For the second mode, higher brain and higher psychopathology scores predicted less school-related impairment one year later. Identifying how specific neural measures align with psychopathology domains, as well as how both forecast reallilworld functioning, advances the conceptualization of adolescent mental health. This approach clarifies which levels of analysis provide distinct versus shared information about youth functioning and highlights potential mechanisms that may inform future targets for change.

The relationship between cortical morphology and intelligence during adolescence has been widely studied, with existing literature reporting varying degrees of association across different modeling approaches. This study provides a comprehensive comparison of model performance in investigating the association between crystallized intelligence and cortical surface area using data from 11,351 subjects in the Adolescent Brain Cognitive Development (ABCD) study. We evaluate ten widely used models ranging from linear regression to graph convolutional networks across three covariate adjustment formulations: full (no adjustment), partial (age and sex adjusted), and total surface area (TSA) partial (age, sex, and TSA adjusted). Using bootstrap resampling with 50 iterations, we estimate the fraction of variance explained (FVE) for each model. Our results suggest that more complex models do not lead to higher FVE, with LASSO having the highest FVE of 15.9% (full formulation), Ridge at 10.5% (partial formulation), and Principal Component Regression (PCR) with 102 PCs at 2.5% (TSA partial formulation). Our results also reveal that the relationship between cortical surface area and crystallized intelligence is predominantly driven by global factors age, sex, and TSA, rather than by localized cortical surface area.

ObjectiveTo examine associations of BMI-related polygenic scores (PGSs) with BMI-for-age z-score (BMIz), height-for-age z-score (HAZ), and weight; assess sex-specific effects; and test PGS-by-diet interactions in youth experiencing the double burden of malnutrition. MethodsIn this cross-sectional study of Filipino youth aged 6-19 years, we analyzed genome-wide genotype, anthropometric, and dietary data from two 24-hour recalls. Four ancestry-standardized BMI PGSs were evaluated using linear regression adjusted for age, sex, and ancestry principal components, with platform-specific estimates combined by fixed-effects meta-analysis. ResultsAll four PGSs were positively associated with BMIz ({beta} range: 0.119 - 0.320). The strongest association was observed for the multi-ancestry score PGS005202 ({beta} = 0.320; P = 2.39 x 10-9; {Delta}R2 = 4.98%). No PGS was associated with HAZ. PGS005202 and PGS005279 were associated with higher weight independent of HAZ. A significant PGS000716-by-sex interaction was observed for BMIz (q = 0.034), with an association in boys ({beta} = 0.253; P = 0.002) but not in girls ({beta} = -0.007; P = 0.93). No PGS-by-diet interaction remained significant after multiple-testing correction. ConclusionsBMI-related PGSs were associated with adiposity-related traits, but not linear growth, in Filipino youth. Findings support sex-stratified analyses and further evaluation of ancestry-inclusive PGSs in similar pediatric settings.

The first year of formal schooling is a year of foundational reading and math learning, and individual differences emerging within this single year predict academic achievement decades later. Yet, how brain changes throughout this critical year relate to individual differences in reading and math learning remains uncharacterized. In this pre-registered study (https://osf.io/97ybe), we acquired monthly both behavioral assessments of reading- and math-learning, and diffusion-weighted MRI scans to measure white matter microstructure, across the first-grade year. Behavioral learning trajectories follow either a sigmoid for reading or an inverted-U for math. Month-to-month microstructural changes in the right middle longitudinal fasciculus predicted corresponding changes in math performance, but not in reading. Findings highlight white matter microstructure as a dynamic substrate of early math learning, and reveal a more general principle: rapid changes in white-matter microstructure during the foundational learning window may be associated with distinct academic domains. Funding: R01 HD114489

Motivation: Quantitative assessment of neonatal internal capsule (IC) maturation remains largely reliant on qual- itative visual evaluation, limiting objectivity and scalability. Approach: We developed a fully automated 3D deep learning framework for anatomically detailed segmentation of IC subregions and PLIC myelin-related signal from structural T2-weighted MRI, trained on both high-resolution 7T and conventional 3T neonatal datasets. Volumetric and intensity-based metrics were derived, and developmental trajectories were modelled using postmenstrual age (PMA) and postnatal age (PNA), with normative modelling used to quantify individual deviations. Results: The pipeline achieved high segmentation accuracy across field strengths (Dice > 0.95, relative volume difference < 5%). IC metrics showed robust age-related changes, with volumetric measures increasing and intensity- based measures decreasing with PMA. PNA effects indicated prematurity-related modulation at equivalent maturational age. These patterns generalized to 3T, where normative modelling revealed significant deviations in preterm infants, particularly for myelin-related intensity measures. Conclusion: Structural T2-weighted MRI, combined with anatomically informed segmentation, enables quantitative and biologically meaningful assessment of neonatal IC maturation. This provides a scalable framework for studying early white matter development and supports potential clinical translation.

IntroductionWhile global topological properties of brain networks reach relative maturity early in development, functional reconfigurations at the regional level continue throughout adolescence to support cognitive maturation. However, regional age and sex-specific developmental patterns of functional reconfiguration remain incompletely understood. MethodsWe analyzed resting-state fMRI data from 528 participants aged 5-21 years from the Human Connectome Project in Development. Three regional graph-theory metrics (betweenness centrality, hub score, and local efficiency) were computed for each individuals functional network. Cognition was measured using NIH toolbox. Parallel factor analysis was employed to decompose an individual x region x metric array into factors representing distinct developmental properties in the full sample and separately for males and females. Brain-cognition associations were examined in developmental subgroups (<13, 13-18, >18 years). ResultsThree factors emerged, characterizing visual, multimodal integration, and higher-order factors. Across development, metrics capturing network integration (betweenness centrality and hubness) showed general stability, while metrics capturing segregation (local efficiency) presented distinct peaks, particularly in the visual factor. Females showed earlier peaks and declines in higher-order factor, while males exhibited greater variability and protracted maturation in multimodal and higher-order factors. Brain-cognition associations were modest with early childhood and crystallized cognition composites showed small negative correlations with hub score in entire sample (r=-0.212) and local efficiency in males aged <13 years (r=-0.215). ConclusionFindings highlight nonlinear, sex-specific functional reconfiguration at region-level during childhood and adolescence, underscoring the importance of sex-stratified analyses in developmental and providing a crucial foundation for future investigations of developmental disorders.

The types of faces that infants see impact their developing ability to engage with and individuate people from familiar and unfamiliar social groups, a phenomenon known as perceptual narrowing. However, the neural mechanisms that underlie infants processing of different faces as a function of experience remain poorly understood. To address this gap, the present study analyzes electroencephalography data collected while 3-month-olds (N=24), 6-month-olds (N=26), and 9-month-olds (N=18) viewed female and male faces of a familiar or unfamiliar social group. Infants neural responses to faces differed by group familiarity from 3 months of age, with increased responses to the more familiar face types in early components (P1, N290), and to the more unfamiliar face types in later components (P400, Nc). Face sex and group familiarity interacted to shape N290 and P400 amplitudes at 3- and 9-months. Specifically, N290 amplitudes were greater in response to female faces of a familiar group at 3 months, and to male faces of a familiar group at 9 months. In contrast, P400 amplitudes were greater in response to male faces of an unfamiliar group at 3 months old, and greatest in response to both female faces of a familiar group and to male faces of an unfamiliar group at 9 months. Source reconstruction of the Nc revealed greater reconstructed current density in response to faces of an unfamiliar social group across all ages. These findings contribute to a growing body of knowledge examining how perceptual experiences shape infants understanding of their social world.

Background Children in low- and middle-income countries (LMICs) face an elevated risk of developmental delay, yet scalable neuroimaging tools to study early brain development in these contexts remain limited. Children who are HIV-exposed but uninfected (CHEU) represent a growing population with evidence of language and motor delays and altered brain development compared with children who are HIV-unexposed (CHU). Ultra-low-field (ULF) MRI offers a more affordable alternative to conventional high-field (HF) MRI, but its application in early childhood remains underexplored. Methods We compared brain volumes derived from ULF (64mT) and HF (3T) MRI in South African CHEU and CHU as part of the DolPHIN-2 PLUS study. Volumetric segmentation was performed using FreeSurfer v7.4.1 and SynthSeg on the Flywheel platform. Agreement between modalities was assessed using Pearsons and Lins concordance correlation coefficients across global and subcortical regions. Associations between ULF-derived brain volumes and developmental outcomes, measured by the Bayley Scales of Infant Development, Third Edition, were evaluated using partial correlations adjusted for sex and age. Results Forty-five children (9 CHEU, 36 CHU; mean age 45.6 months) had paired ULF and HF scans of usable quality. Strong correlations were observed between ULF and HF volumes for global white and grey matter regions (r > 0.92) and larger subcortical grey matter structures such as the thalamus, caudate, and putamen (r = 0.86-0.89). Moderate-to-weak correlations were evident in smaller structures (hippocampus, pallidum, amygdala). ULF underestimated most grey matter volumes, and overestimated total white matter volume relative to HF. ULF-derived global and subcortical volumes were associated with receptive and expressive communication (r = 0.34-0.59, all p < 0.05). Conclusions ULF MRI produces brain volume estimates comparable to HF MRI and captures meaningful associations with early language development. These findings support ULF MRI as a feasible and scalable tool for studying neurodevelopment in vulnerable paediatric populations in LMICs.

I ntroduction: Prospective memory (PM) deficits in children with attention-deficit/hyperactivity disorder (ADHD) significantly impact academic and daily functioning. Through two experiments, this study investigated how cognitive load and encoding strategies modulate PM performance. Methods: Experiment 1 included 43 children (21 ADHD, 22 typically developing) who completed an n-back task under high and low cognitive load. Experiment 2 included 44 children with ADHD who were randomly assigned to either a standard encoding group or an implementation intention encoding group, also completing the n-back task under both load conditions. Results: Experiment 1 showed that children with ADHD had significantly lower PM accuracy than typically developing peers. Signal detection analysis revealed that this deficit stemmed from a more conservative response bias rather than impaired perceptual sensitivity. Unexpectedly, PM accuracy and perceptual sensitivity were higher under high cognitive load than low load for both groups. Experiment 2 demonstrated that implementation intention encoding significantly enhanced PM accuracy and perceptual sensitivity in children with ADHD, with stable effects across load conditions and no interference with ongoing task performance. Discussion: These findings indicate that PM deficits in children with ADHD reflect a conservative response strategy rather than an inability to detect target cues. Implementation intention encoding provides an effective, load-independent cognitive strategy for enhancing PM performance. These results offer novel insights into the cognitive mechanisms underlying PM deficits in ADHD and provide evidence-based guidance for targeted interventions.

Across species, adolescence is a time of heightened reward sensitivity and enhanced impulsivity and risk-taking. In adults, these behavioral features are linked with a tendency to approach and interact with reward-associated cues - a behavior known as sign tracking - which is thought to reflect the transfer of incentive salience from reward to cue. Counterintuitively, adolescents are less likely to exhibit sign tracking, compared with adults, and more likely to exhibit goal tracking, or approach to the site of reward. To investigate a possible neural basis for this age difference, we recorded the activity of individual neurons in the nucleus accumbens (NAc) of male and female rats during Pavlovian conditioning in adolescence and adulthood. In a separate group, we used a fluorescent indicator (GRABDA) to measure dopamine release at the same ages. We found that cue-evoked NAc activity increased over the course of training in adolescents and then further in adulthood. The majority of adolescents were goal trackers or intermediates, for whom reward-evoked activity peaked during adolescence and declines in adulthood, correlating with increased prevalence and intensity of sign tracking. Meanwhile, cue-evoked dopamine release was markedly higher in sign trackers than in goal trackers at all time points. These results suggest that the progression from adolescence to adulthood may be accompanied by changes in the engagement of the mesolimbic dopamine system and/or the responsivity of NAc neural signaling to dopamine, contributing to limited sensitivity to reward cues, coupled with heightened sensitivity to primary rewards, in adolescent animals. Significance StatementAdolescence is a time of enhanced reward sensitivity, impulsivity, and risk-taking, making adolescents vulnerable to drug use and other risky behaviors. In adults, attraction to reward-associated cues - which can be modeled in animals using a behavior called sign tracking - plays an important role in risky behaviors. Surprisingly, we find that adolescents exhibit less sign tracking compared with adults. Here, we investigate the neural circuits underlying this age difference by monitoring neural activity and dopamine release in the nucleus accumbens (NAc), a key brain area for reward-seeking behavior, in the same animals as adolescents and as adults. We find that the majority of adolescents show a reduced neural sensitivity to reward cues, but a heightened neural response to the reward itself.

There is growing interest in identifying brain function underlying adolescent cognition, personality, and psychopathology. One promising approach is Precision Functional Mapping (PFM) of MRI functional connectivity, a data-intensive method for characterizing individualized brain networks. Foundational studies suggest that PFM can detect stable, task-responsive, and clinically relevant networks. Studies demonstrate that both functional connectivity reliability and network stability improve with increasing data quantity, although benchmark estimates vary across populations, preprocessing pipelines, and MRI acquisition approaches. Accordingly, it is important to understand how PFM performs in adolescent populations and with multi-echo fMRI acquisition. In a case study of eight youth (ages 10-17), we applied PFM to 80-minutes of combined resting-state and task-based fMRI. The resulting networks were highly modular, consistent with adult templates, and without evidence of structural registration artifacts. Functional connectivity reliability compared favorably to prior single-echo studies, with multivariate similarity and ICC estimates showing early stabilization around 10-15 minutes despite continued improvement with additional data. Trait-like stability increased gradually with acquisition time and a Bayesian algorithm (MS-HBM) demonstrated higher stability than Infomap. Across algorithms, stability was greatest in sensory networks (somatomotor, auditory, visual). Furthermore, when evaluating task-based responses to threat and attention paradigms, only the auditory network consistently benefited from individualized mapping over group template networks. These findings suggest that, with constrained scanning time, PFM is especially effective for characterizing sensory and perceptual networks in adolescents. Bridging the methodological divide between deeply sampled individual cases and large-scale developmental studies will require further innovation and validation.

Introduction: While growing evidence suggests that music training supports child development, few long-term randomized controlled trials (RCTs) have rigorously tested these claims. Moreover, it remains unclear whether the benefits are confined to music-specific domains or extend to higher-order cognitive functions such as inhibitory control (IC), a core executive function associated with long-term outcomes in academic achievement, career success, socio-emotional health, and physical well-being. This paper presents the protocol for the Extracurricular Activity and Child Early Learning and Development (EXCEL) trial, an RCT designed to assess the feasibility of a long-term music training program focusing on the brain and behavioral correlates of IC. Methods: A total of 126 children, aged 6 to 8 years and residing in neighborhoods with limited resources in Los Angeles, were individually randomized to either a music (intervention) or theatre (active control) after-school program. Both programs were delivered over 24 months by established community arts organizations. Eligibility criteria included: average intellectual functioning, no major medical or psychiatric conditions, and MRI eligibility. Children with prior formal music training exceeding six months or severe hearing impairment were excluded. Before the intervention began, all participants completed baseline behavioral and neuroimaging assessments. The primary trial aim was to assess the effects of extended music training, relative to theatre training, on changes in measures of IC (i.e., Go/No-Go task and delayed gratification) and related neural functional activation. A secondary interim aim of the trial was to evaluate the feasibility of conducting a long-term RCT of music education in a first cohort, measured by participant retention, adherence to the program, willingness to continue at the 12-month mark, and fidelity. Progress: Recruitment, screening, baseline testing, randomization, and program enrollment began in August 2022, and after-school programming began in October 2022. The randomized interventions and all data for the first cohort (N = 42) have been collected. Intervention and active control programs for a second cohort are ongoing and will end in Fall 2026. Discussion: This paper reports the EXCEL trial protocol and provides feasibility estimates for implementing a long-term randomized controlled trial of music training in real-world, community-based settings with children. While similar neuroimaging RCTs are currently underway in Europe, the EXCEL trial is among the first in the United States to integrate longitudinal neuroimaging with arts intervention. Findings will inform the viability of scaling such programs and contribute to our understanding of how sustained music engagement may influence the development of inhibitory control circuitry in childhood.

BrainAge models hold promise as a clinical biomarker for developmental brain health, especially in childhood when there is the potential for early intervention. To distinguish between normative developmental variance and pathological divergence, BrainAge models should reflect the dynamic and diverse neurodevelopmental processes that occur in distinct developmental windows across childhood. We utilized multi-modal neuroimaging data from three pediatric cohorts covering ages 4 to 13 years (n = 1005, 2126 scans), split into Train and Test datasets. Twelve sex-stratified BrainAge models were built stratified by type and different combinations of neuroimaging features. Model types were "Full-Span" models covering the full age range, and "Phase-Specific" models split into early- and late-childhood. We first compared BrainAge estimates in the Test dataset amongst our candidate models, then benchmarked the best-performing model against published pre-trained models and DNA-based biological age measures. Our findings show that a BrainAge model that was phase-specific and consisted of both structural and functional features (cortical thickness, subcortical volumes, and functional network integration measures) showed good prediction of age and best distinguished between healthy and symptomatic subgroups. We present a proof-of-concept for developmental models supporting building BrainAge models of higher temporal resolution that align to different childhood developmental phases.

Background: Body-focused repetitive behaviours (BFRBs), including hair pulling, skin picking and nail biting, are common but under-recognised behaviours that often emerge during adolescence. Their prevalence, associated distress, and relationship with mental health and social factors remain poorly characterised. Methods: 5,437 adolescents aged 11-18 years reported engagement in BFRBs, associated distress, and functional interference as part of the 2025 OxWell Student Survey. Participants. Problematic BFRBs were defined as at least one BFRB with moderate or high distress. Associations with gender, neurodivergence, bullying, and internalising symptoms were examined using multivariable logistic regression. Results: Overall, 58.5% of participants reported at least one BFRB. Nail biting was most common (43.6%), followed by skin picking (31.3%) and hair pulling (14.5%). Among those with BFRBs, 22.2% reported moderate-to-high distress, and 3.3% of the total sample reported the highest level of distress. Co-occurrence was common: more than half of those with BFRBs reported multiple behaviours. BFRBs were more common and more distressing in girls and trans/gender-diverse participants than in boys. Problematic BFRBs showed strong associations with internalising symptoms (6.3% in the normal range vs 34.2% in the clinical range) and bullying (9.6% with no bullying vs 27.1% with >weekly bullying). Internalising symptoms were the strongest predictor in multivariable models (OR 1.97 per 10-point increase), alongside independent contributions from gender and frequent bullying. Conclusions: BFRBs are common in adolescents, frequently co-occur, and are strongly associated with emotional distress and social adversity. Recognition of distress, rather than behaviour alone, may be important for identifying unmet need and guiding intervention.

Adolescence is characterized by heightened reward sensitivity and risky decision-making. Prevailing neurodevelopmental frameworks typically attribute these behavioral trends to a maturational imbalance between rapidly developing motivational brain regions, and slower-maturing prefrontal cognitive control circuitry. However, these models largely overlook the cerebellum--a structure that demonstrates protracted development across adolescence and reciprocal connectivity with both striatum and prefrontal cortex. Computational models also highlight the cerebellums central role in reinforcement learning and error-based model updating, making it a potentially critical region for understanding adolescent reward processing. To evaluate this, we conducted a systematic literature search and coordinate-based meta-analysis of functional magnetic resonance imaging (fMRI) studies examining reward anticipation and receipt in healthy adolescents (19 studies; 55 cerebellar peaks). Results demonstrate a striking functional dissociation. During reward anticipation, adolescent cerebellar activation mirrors adult topographies--demonstrating widely distributed activation patterns across the cerebellar lobules and Vermis, localized to cerebellar regions that are functionally connected with salience, somatomotor, and frontoparietal cortico-cerebellar networks. Conversely, while reward receipt also elicits widespread cerebellar activation in adolescents, this stands in contrast to highly focal feedback-locked reward activity seen only in the Vermis in adult studies. We interpret these findings through the lens of cerebellar reinforcement learning. We argue that widespread reward outcome-locked BOLD activity in adolescents may reflect broader parallel fiber recruitment, supporting the active maintenance of short-timescale eligibility traces required for credit assignment while internal forward models are being constructed during development. Ultimately--rather than a biological epiphenomenon--it is hypothesized that this active cerebellar computation during adolescence may contribute to the developmental shaping of prefrontal networks necessary for normative regulation of motivation and decision-making in adulthood.

Objective: ADHD has been associated with obesity indicators, including BMI, across the lifespan. A possible mechanism linking ADHD and BMI is binge eating. Previous research has found associations between ADHD, binge eating and BMI. However, the role of genetic and environmental influences on these associations remains unclear. Method: We utilized data from the Twins Early Development Study (TEDS), comprising 3,675 monozygotic and 7,063 dizygotic twin pairs. ADHD symptoms in childhood and adolescence were assessed using parent-reported questionnaires. Adult ADHD symptoms were measured using both self-report and parent-report questionnaires. Phenotypic mediation models examined whether binge eating mediated the association between ADHD and BMI, without controlling for genetic confounding. Subsequently, the etiological architecture underlying the associations among the three traits across childhood, adolescence, and adulthood were investigated by incorporating genetic and environmental influences into the models. Results: Binge eating significantly mediated the association between ADHD symptoms and BMI in both adolescence and adulthood. However, these mediation effects were no longer present once genetic and environmental influences were incorporated into the models. The best-fitting model in childhood, adolescence and adulthood was Cholesky decomposition models, where covariance between traits was explained by shared aetiology. Conclusions: This twin study reveals shared liability across ADHD, binge eating, and BMI. The mediating role of binge eating in the relationship between ADHD symptoms and BMI was largely confounded by shared genetic influences. Intervention strategies could focus more on common underlying behavioural and self-regulatory mechanisms across these traits, as well as placing more emphasis on symptom patterns within families.

Understanding the dynamics of brain-behaviour relationships during adolescence is critical for elucidating the neurodevelopmental basis of mental health. Leveraging two large-scale longitudinal cohorts--the Adolescent Brain Cognitive Development (ABCD) and IMAGEN studies, comprising over 10,000 participants aged 10 to 22 years with six waves of multimodal neuroimaging and behavioural data, we applied multi-view sparse canonical correlation analysis to investigate evolving associations between structural MRI, resting-state functional connectivity, and multi-domain behavioural measures. Our findings reveal four fundamental patterns of developmental reorganisation in brain-psychopathology relationships. First, symptom profiles evolved from predominantly externalising features (aggression, attention problems) at ages 10-12 toward global psychopathology by age 14, then transitioned toward internalising features (e.g., anxiety, depression) by ages 19-22, reflecting fundamental shifts in vulnerability from behavioural dysregulation to affective disturbance. Second, cortical thickness exhibited negative associations with externalising symptom profiles throughout development. During early adolescence (ages 10-14) this was driven by broadly distributed decreases across sensorimotor, temporal, visual, and cingulate regions alongside overall mean cortical thickness. After 14, this diffuse pattern shifted towards late maturing association cortices, notably the dorsolateral prefrontal and lateral temporal cortices. Third, this was accompanied by subcortical effects that exhibited greater age-specificity: whilst cerebellar volume contributions were evident at most timepoints, basal ganglia volume influence was principally evident in early development (ages 10-12), with thalamic structures and global subcortical grey matter volume becoming dominant at age 14, marking a transition in which subcortical structures mediate psychopathology associations. Fourth, functional connectivity showed a more dynamic developmental trajectory. During early adolescence, symptom associations were driven by positive connectivity between cognitive control and sensorimotor networks, whereas late adolescence exhibited predominantly positive connectivity patterns, transitioning from dense sensorimotor-frontoparietal configurations to more specific patterns involving the central executive and default-mode networks. These findings fundamentally challenge static biomarker models, demonstrating that adolescent psychopathology reflects developmentally contingent brain-behaviour relationships rather than static neural markers. Age 14 emerges as a critical inflection point marked by convergent thalamic reconfiguration, global subcortical grey matter dominance, and symptom profile transitions. This work provides an empirical foundation for precision mental health strategies tailored to specific developmental windows, with implications for reducing psychiatric burden in youth.

Aim: To systematically evaluate evidence on the effects of post-discharge early developmental intervention programs (EI) on behavioral development, quality of life, participation, executive functioning, parent-child interaction, and use of medical services from infancy through adolescence in children born preterm. Method: Four bibliographic databases and one trial registry were systematically searched for randomized controlled trials up to April 23, 2024. Two reviewers independently screened studies and extracted data. In clinically and methodologically comparable studies, random-effects meta-analysis were performed. Risk of bias was assessed with the Cochrane RoB 2 tool, and certainty of evidence with the GRADE approach. Results: Twenty-six studies met inclusion criteria, eleven studies including 2,315 preterm born infants reported relevant outcomes, and seven contributed to meta-analyses. Most reported results showed some concerns or high risk of bias; certainty of evidence ranged from very low to moderate across outcomes. EI may offer small benefits for selective attention, behavioral problems and parent-child interaction. Little to no effect was found for special educational needs, language skills, executive functioning and the use of medical services. No included studies evaluated the effect of EI on ADHD, quality of life, or participation related to mobility or leisure activities. Interpretation: EI may improve problems typically seen in preterm children and should be offered especially to those with additional medical or social risk factors. High-quality, contemporary trials are needed to establish reliable clinical recommendations regarding EI strategies and complementary interventions throughout childhood.