Developmental Cognitive Neuroscience

Adolescence is a fundamental developmental period marked by dramatic socio-affective and physiological changes, including shifts in social behavior and maturation of underlying brain architecture. In girls, this period coincides with the onset of the pubertal transition, which fundamentally influences motivated social behavior and neurodevelopment. The present study examines age- and pubertal maturation-related changes in social motivational goals and hippocampal and motivation-related cortical structural development in adolescent girls (n=154) across five timepoints. Social motivational goals showed substantial variability of each subdomain across age and pubertal development. Specifically, all social goals showed linear increases across age and pubertal stage, whereas goals centered around developing social competency increased non-linearly across age. Our neurodevelopmental findings align with established research, revealing volumetric increases of the hippocampus, and cortical thinning of the medial orbitofrontal cortex (mOFC) and rostral anterior cingulate cortex (rACC) across age and pubertal stages. Collectively, these results highlight simultaneous change in endorsement and prioritization of different social motivational goals across adolescence, and they underscore the simultaneous shifts in structural development in regions supporting social motivation and broader socio-affective development. This research highlights the importance of fostering positive social experiences during this critical developmental stage, with implications for adolescent well-being and social development.

Background: Adolescence is marked by improvements in inhibitory control along with brain maturational processes affecting function and structure of cortical circuitry. Preliminary evidence shows a developmental decrease of local neuronal inputs, suggesting a weakening of local connectivity supporting circuit refinement and mature behavior. Microstructural changes in gray matter, arising from processes such as synaptic pruning and myelination, may support this refinement, though it remains unknown how microstructural features interact with the reconfiguration of functional circuitry, or how this unfolds in vivo in normative development to support mature cognitive functioning. Methods: In this study, 175 participants ages 10-26 (93F; 17.32{+/-}4.82yo) completed an anti-saccade task, a developmentally-validated measure of inhibitory control, as well as a 3T MRI scan involving a multi-shell diffusion weighted imaging acquisition, multi-echo resting state fMRI, and structural (T1w, T2w) scans. We computed measures of neurite density (NDI) in gray matter using neurite orientation dispersion and density imaging, local functional connectivity with surface-based and volumetric regional homogeneity (ReHo), and intracortical myelin using T1w/T2w ratio. Generalized additive models examined non-linear age-related trends across a number of cortical and subcortical regions implicated in inhibitory control, as well as associations with anti-saccade performance. Results: We found that NDI significantly increased with age in all regions while ReHo decreased. Greater NDI was associated with more accurate anti-saccade performance and lower ReHo, which remained after residualizing NDI for T1w/T2w ratio, suggesting that microstructural reorganization beyond myelination may underlie functional specialization throughout adolescence. Lower ReHo, specifically in young adolescents, also resulted in better anti-saccade performance. Finally, an interaction between ReHo and NDI, rather than either measure alone, best predicted inhibitory control performance, such that the maturity of neurite density had the greatest effect when local connectivity was high, suggesting immaturity. Conclusions: Our results suggest that the joint maturation of microstructural elements and associated specialization of local functional circuitry interact to support the emergence of stable adult-level inhibitory control.

Hispanic Americans face persistent health disparities rooted in complex sociocultural and bioecodevelopmental dynamics. Identifying early neurodevelopmental trajectories that confer risk or resilience during adolescence is critical for developing targeted health equity interventions. Grounded in the NIMHD Research Framework and bioecodevelopmental theory, data from 12- to 14-year-old Hispanic adolescents in the Adolescent Brain Cognitive Development (ABCD) Study were analyzed (n=236). Partial least squares correlation (PLSC) was used to evaluate multivariate associations between sociocultural measures, spanning individual, family, and community levels, and resting-state functional connectivity (rsFC) networks. Post hoc linear mixed-effects models examined how derived sociocultural-rsFC patterns predicted measures of physical and mental health, linking bioecodevelopmental patterns to adolescent well-being. PLSC revealed dual community- and family-level neural pathways of biological embedding, diverging from traditional nested bioecodevelopmental assumptions. The community pathway linked child opportunity and neighborhood disadvantage to connectivity across Cingulo-Opercular, Default, Dorsal Attention, Visual Networks. This community-rsFC profile was associated with lower respiratory functioning, reflecting an allostatic load marker of environmental stress. The family pathway linked caregiver ethnic identity and heritage acculturation to Default, Ventral Attention, Sensorimotor-Mouth, and Visual Networks connectivity, suggesting that the family system shapes neural systems underlying social attunement and identity formation. Structural community factors and familial culture impose distinct neurobiological demands on the adolescent connectome among Hispanic youth. Findings highlight respiratory health as a biological marker of environmental adversity and underscore the necessity of structural and culturally sustaining interventions to promote health equity among Hispanic youth.

Background: Developmental trajectories of low-concentration neurometabolites such as the neurotransmitter {gamma}-aminobutyric acid (GABA), and the antioxidants glutathione (GSH) and ascorbate (Asc) across early infancy remain unexplored. Advances in spectral editing enabled the measurement of these key molecules together with high-concentration metabolites like N-acetylaspartate (NAA) and glutamate (Glu) in the HEALthy Brain and Child Development (HBCD) study, the largest longitudinal study of early brain development in the United States. Purpose: To determine the age-associated trajectories of 14 key neurometabolites during early infancy from a cross-sectional 1H-MRS dataset. Materials and Methods: HBCD utilizes ISTHMUS, an integrated MRS sequence that includes both an unedited short-echo-time PRESS acquisition and an advanced 4-step Hadamard-encoded sequence, HERCULES to enable measurement of both high- and low-concentration metabolites. Metabolite quantification was carried out by the HBCD Data Coordinating Center (HDCC) using an automated Osprey pipeline, with data from 201 infants ages 0 - 10 weeks adjusted age included in the tabular imaging results in HBCD data release 1.0. After excluding preterm born infants and data with poor linewidth or model quality metric, we tested for linear associations with adjusted age for each metabolite. Results: Concentration estimates of total NAA (tNAA), total creatine (tCr) and glutamate (Glu) as well as the combined sum of glutamate and glutamine (Glx) significantly increased across ages 0 - 10 weeks, while myo-inositol (mI) decreased. GABA and GSH showed age-related trends, but did not reach significance. Levels of the lipid precursor phosphorylethanolamine (PE) and Asc are higher in the first months than established adult values. Conclusion: Multiple metabolites showed significant age-related changes during early infancy. While GABA and GSH did not, future work will establish whether the trends suggested here contribute to linear or non-linear patterns across the first years of life.

IntroductionVagally mediated heart rate variability (vmHRV) reflects parasympathetic cardiac control and serves as a peripheral marker of brain-body interaction. While studies in adults link higher vmHRV to greater cortical thickness regions related autonomic regulatory, little is known about its association with longitudinal cortical maturation during puberty, a period of pronounced cortical thinning. MethodsThis longitudinal study examined whether individual differences in cortical thinning trajectories are associated with vmHRV in two independent cohorts of children and adolescents. Structural MRI were acquired in an accelerated longitudinal design over three time points, each one year apart in two cohorts (n = 44; ages 9 and 12 at baseline). Cortical thickness was estimated using FreeSurfer, and annualized regional thinning slopes were derived for 62 cortical regions. vmHRV was measured one year later at follow-up. Elastic net regression with stability selection identified robust predictors, which were entered into linear models separately for each cohort. ResultsAcross both cohorts, vmHRV was associated with distributed patterns of cortical thinning. Consistent associations emerged in medial and posterior midline regions, including the precuneus, isthmus of the cingulate cortex, and medial prefrontal and orbitofrontal areas. Associations showed heterogeneous directions across regions, contrasting with uniform adult findings. DiscussionvmHRV may be linked to network-level cortical maturation during adolescence, particularly within default mode and fronto-limbic systems. Findings extend adult work by demonstrating that brain-autonomic coupling emerges during development and is characterized by regionally differentiated trajectories of cortical thinning.

Youth adversity has been associated with alterations in hippocampal structure; however, it remains unclear whether different forms of adversity relate distinctly to its organization across the anterior-posterior and proximal-distal axes. Here, we investigated the associations of different types of adversity with multiple structural properties of the hippocampus in 5,263 early adolescents from the ABCD Study. Hippocampal macrostructure was characterized using volume, thickness, and gyrification, whereas T1w/T2w ratio served as an in vivo proxy for microstructure. Adversity was assessed at the family level using questionnaires on family environment and parenting, and at the socioeconomic level using income-to-needs ratio and neighborhood disadvantage measured by the Area Deprivation Index. Associations were examined for each adversity type separately in multi-variate analyses and for cumulative adversity exposure in univariate models. Hippocampal features were obtained using HippUnfold, an advanced automatic segmentation approach that accounts for interindividual folding variability, and were analyzed globally as well as across the hippocampal anterior-posterior and proximal-distal axes. Socioeconomic measures showed widespread associations with hippocampal macrostructure across the whole hippocampus and both anatomical axes, whereas associations with T1w/T2w ratio were limited and observed only for neighborhood disadvantage along the anterior-posterior axis. Cumulative adversity exposure was consistently associated with alterations in CA1 and subiculum across volume, thickness, and gyrification, but not T1w/T2w ratio. Together, these findings suggest that different types of adversity exhibit distinct spatial associations across complementary hippocampal macro- and microstructural features, highlighting regional variation in the susceptibility of the developing hippocampus to environmental adversity.

Importance: Pediatric obesity affects 1 in 5 US children and has been linked to brain structural differences. Most evidence is cross-sectional and models body mass index (BMI) linearly, with metrics that compress severe obesity. Objective: To examine associations between brain structure and BMI for age across the weight spectrum and Centers for Disease Control and Prevention (CDC) weight status categories, distinguishing between and within person associations, and their age and sex moderation. Design, Setting, and Participants: Longitudinal cohort study of youth aged 8 to 10 years at baseline in the US community based Adolescent Brain Cognitive Development Study (4 waves, 2016 to 2025; ages 8 to 18 years). Exposures: Extended CDC BMI-for-age z-score, grouped by wave-mean z-score: underweight (<5th percentile, n=297), healthy weight (5th to <85th, n=7,452), overweight (85th to <95th, n=1,919), and obesity ([&ge;]95th, n=1,842). Main Outcomes and Measures: Cortical thickness (12 regions) and subcortical volume (7 regions) from T1 weighted magnetic resonance imaging (MRI), defined a priori. Results: Among 11,510 participants contributing 32,212 observations (mean [SD] age, 12.6 [2.5] years; 52.2% male), higher between person BMI for age z was associated with lower frontal and temporal thickness (6 regions) and larger subcortical volume (5 regions; all q < .001), but associations were nonlinear (17 of 19 regions). Youth with obesity had lower thickness than healthy weight youth in 8 frontal and temporal regions (largest, -0.21 SD; q < .001), with dorsal frontal differences decreasing across adolescence; underweight youth had smaller subcortical volumes. Higher BMI for age z was associated with larger subcortical volume (all 7 regions) within the healthy weight category and lower cortical thickness (11 of 12 regions; fusiform: {beta} = -0.27; q < .001) within the obesity category, steeper than in healthy weight youth in 10 regions, but not in overweight or underweight youth. Within person associations did not reproduce the obesity associations, reversed from negative at age 10 to positive at age 16, and were more negative in female than male participants. Conclusions and Relevance: Youth with obesity had lower cortical thickness than healthy weight peers, but associations between brain structure and BMI for age differed between CDC weight status groups, suggesting a complex relationship between adiposity and brain structure.

Childhood adversity is robustly linked to differences in amygdala and hippocampal volume. However, findings across studies have been inconsistent and contradictory. This inconsistency stems partly from the many reasonable but arbitrary choices that researchers make when operationalizing brain regions, stress exposure, and covariates. To deal with this variability, we applied a multiverse analysis approach using adolescent data from the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study to evaluate how multiple analytic choices influence the relationships between stress and hippocampal/amygdala volume. Our primary analysis crossed three region-of-interest operationalizations (left, right, total), four intracranial volume scaling methods, and multiple sociodemographic covariates. Greater lifetime stress severity was associated with smaller amygdala volume across 72% of specifications, and with smaller hippocampal volume across 52% of specification models. Statistical significance was strongly influenced by the region of interest. Our secondary multiverse analysis tested six operationalizations of stress exposure (total/acute/chronic x count/severity). This analysis found that the laterality pattern in the primary analysis was not strongly influenced by stress operationalization. These findings demonstrate the robustness of the stress-medial temporal lobe association and identify specific analytic choices (i.e. hemisphere operationalization) that most strongly drive the variability observed in previous literature. Our study is one of the first that utilized multiverse analysis for adversity-neuroimaging research, and provides a strong framework for evaluating and interpreting inconsistent findings.

Structural connectomics provides a means of characterising white matter (WM) network organisation using diffusion MRI (dMRI), but reconstructing neonatal structural connectomes remains challenging due to the immature and heterogeneous nature of the developing brain. Although recent neonatal studies have increasingly adopted approaches beyond conventional diffusion tensor imaging (DTI), there remains scope to incorporate more advanced tractography and streamline post-processing approaches within neonatal pipelines. Here, we propose a neonatal structural connectome pipeline integrating surface-based anatomical constraints, ensemble tractography, hierarchical anatomical refinement of pathways (HARP) filtering, and spherical-deconvolution informed filtering (SIFT2) reweighting. We acquired 3T MRI data from 300 neonates (185 preterm, 115 term-born) to assess the impact of pipeline configuration on network organisation. Mean gestational age (GA) at birth was 29.31 (23.43-32.86) weeks in preterm infants and 39.52 (37.00-42.43) weeks in term infants. At scan, mean GA was 40.85 (36.29-49.00) weeks in preterm infants and 42.06 (38.29-48.00) weeks in term infants. Four connectome variants were generated: raw surfaced-based tractograms, HARP-filtered, SIFT2-weighted, and combined HARP+SIFT2. Pipeline performance was primarily evaluated using an existing brain age prediction model: connectome-based predictive model (CPM) and our derived connectomes to estimate GA at scan in term and preterm infants. In addition, global graph theoretical metric analyses were conducted to provide a complementary assessment of pipeline configuration differences in network organisation. In total, seven graph theoretical metrics were calculated and evaluated: global efficiency, local efficiency, transitivity, modularity, assortativity, degree variance and statistical complexity. Across all configurations, connectomes supported accurate brain age prediction, with mean absolute errors (MAE) of 0.76-0.79 weeks in term infants and 1.00-1.06 weeks in preterm infants. Prediction error and brain age gap variability were greater in preterm than term infants across configurations, with HARP+SIFT2 achieving the lowest preterm MAE (1.00 weeks) and brain age gap (BAG) variability (SD = 1.38 weeks). However, differences in prediction performance across configurations were minimal, suggesting limited influence of pipeline choice on brain age prediction. However, analysis of global network metrics demonstrated that pipeline choice significantly influenced downstream measures of network organisation, with HARP+SIFT2 being the only configuration to identify significant preterm vs. term differences across all seven metrics examined. These findings demonstrate the importance of considering tractography and streamline-processing choices when constructing neonatal structural connectomes and provide a framework for more anatomically informed investigation of early brain development.

Background: Temperamental risk, including negative reactivity (NR) and behavioral inhibition (BI), represents a robust early pathway to anxiety. Neural responsivity to unexpected sensory stimuli, indexed by the mismatch response (MMR), has been shown to moderate associations linking early temperament to later anxiety. This study extends prior work by testing whether MMR measured as early as 4 months, in a community sample, moderate the developmental pathways from NR to BI and from BI to childhood anxiety. Methods: Participants included 147 infants from the Origins of Infant Temperament study. NR and EEG were assessed at 4 months, with EEG recorded during an auditory oddball paradigm. BI was observationally measured at 14 months, and anxiety symptoms were assessed at 30 months and 4 to 6 years using the Child Behavior Checklist. Structural equation modeling with full-information maximum likelihood tested moderation effects of MMR on NR to BI and BI to anxiety pathways. Results: MMR significantly moderated both pathways. More negative MMR at 4 months were associated with the risk pathways from high NR to high BI and from high BI to high anxiety at 30 months. No significant associations were observed at more positive MMR levels. Anxiety symptoms were stable from 30 months to 4 to 6 years. Conclusions: Neural responsivity to unexpected stimuli in early infancy moderates developmental pathways from temperamental risk to childhood anxiety. Findings replicate and extend prior work to an earlier developmental window and a community sample, highlighting infancy as a critical period for identifying neurobiological markers of anxiety risk. Key words: mismatch response; negative reactivity; behavioral inhibition; infancy; anxiety Abbreviations: BI, behavioral inhibition; EEG, electroencephalography; MMR, mismatch response; NR, negative reactivity.

Adolescence is marked by coordinated endocrine and brain maturation, yet how blood circulating steroid hormones relate to neurochemical change in the brain remains largely unknown. We combined longitudinal data from a novel fast whole-brain, high-resolution three-dimensional proton magnetic resonance spectroscopic imaging technique with repeated measurements of sexual hormones and adrenal steroids in the serum of 42 healthy adolescents (13-15 years; 24 females) totalizing 100 scan-visits. Longitudinal voxel-wise models separated within-individual changes from stable between-individual differences and controlled the false discovery rate across whole-brain tests. In the whole sample, increasing age was associated with higher N-acetylaspartate plus N-acetylaspartylglutamate within individuals, whereas age was positively associated with higher glutamate plus glutamine between individuals. We then observed a hormone-metabolite coupling that differed by sex and steroids. In males, within-individual increases in testosterone tracked frontal increases in glutamate plus glutamine and disseminated increases in total N-acetylaspartate. In females, higher mean estradiol between individuals was associated with higher frontal choline-containing compounds. Within-individual changes in cortisone were associated with myo-inositol and choline-containing compounds in a widespread sex-interaction effect, with positive coupling in males and negative in females. The cortisone/cortisol ratio showed a similar sex-interaction for choline-containing compounds. These findings reveal spatially distributed, sex-dependent links between steroid maturation and adolescent brain neurochemical composition and underscore the importance of differentiating within- and between-individual associations. These observational data extend predominantly structural descriptions of pubertal brain development by identifying distinct coupling of gonadal hormones with neuronal-metabolic markers and glucocorticoid interconversion with glia-weighted metabolites.

Attention is foundational to learning, yet the extent to which features of the instructional environment differentially shape attentional engagement is not well understood. Here we leveraged mobile EEG and video-coded behavioral observation to examine attentional engagement in 6 to 10 years old children with and without a diagnosis of ADHD across instructional conditions varying in delivery modality (video watching, online, in-person) and management of learning (teacher-led versus student-led). EEG measures, including alpha-band (8-12Hz) oscillations, spectral slope and offset, and behavioral measures of active engagement (AE%), passive engagement (PE%), fidgeting, off-task behavior, were examined as a function of instructional context. Attentional engagement, as indicated by higher AE%, lower alpha power, flatter spectral slope and lower offset, was greatest in student-led learning, followed by teacher-led in person learning, synchronous online learning, and asynchronous learning, respectively. Child by instructional context interactions revealed that patterns of attentional engagement were largely consistent regardless of diagnosis, with group effects observed for motor behaviors (PE%, fidgeting) but not for measures of visual attention. Similarly, age showed only main effects, whereby older children showed higher passive engagement, lower fidgeting and off-task behavior, flatter spectral slope, and lower offset. The results underscore: (i) the importance of considering environmental context, such as instructional modality and management of learning, when examining mechanisms of attention and individual differences therein, and (ii) the value of recording multiple behavioral and neural measures, as not all indices commonly assumed to reflect attention capture the same underlying processes.

A central premise of developmental neuroscience is that mature behaviour emerges through reciprocal interactions between infants spontaneous actions, neural activity, and environmental experience. Yet, much human neuroimaging research relies on highly controlled, repetitive paradigms designed to minimize behavioural variability, obscuring the very brain-behaviour dynamics that drive developmental change. Here, we introduce a naturalistic functional near-infrared spectroscopy (fNIRS) paradigm that exploits, rather than suppresses, natural variability in infants behaviour to investigate cortical changes associated with behavioural development. Continuous video coding of spontaneous infant behaviour was combined with finite impulse response (FIR) modelling to estimate behaviour-specific hemodynamic responses associated with reach-to-grasp, hand-to-mouth, and vocalization behaviours while accounting for temporally overlapping hemodynamic responses by treating extraneous behaviours as nuisance regressors. From 6 to 13 months of age, reach-to-grasp and vocalizations increased in frequency, while all three behaviours shortened in duration. Critically, developmental changes in cortical activation were behaviour-specific. During reach-to-grasp movements, bilateral posterior parietal activity decreased with age. In contrast, during hand-to-mouth and vocalizations, somatomotor and premotor activity increased with age. Cortical activity was also related to individual variation in the frequency and duration of these behaviours, indicating that cortical recruitment remained coupled to behavioural variation independent of age. These findings reveal behaviour-specific patterns of cortical reorganisation during infant development and establish a methodological framework for linking spontaneous behaviour to cortical activity in freely behaving infants. More broadly, this approach enables direct investigation of cortical development as it unfolds through naturalistic interactions among behaviour, neural activity, and experience. Significance StatementContinuous self-generated interactions with the environment play a critical role in driving infant brain development, yet neuroimaging research often examines infants while sleeping or in highly constrained and repetitive tasks. Here, we show that spontaneous infant behaviour can instead be leveraged to provide the temporal variability needed to resolve behaviour-specific cortical responses in freely behaving infants. By combining continuous behavioural coding with data-driven finite impulse response (FIR) modelling of overlapping hemodynamic responses, we identified behaviour-specific developmental differences in cortical recruitment without tightly constraining the infants behaviour. This novel approach expands developmental neuroimaging beyond sleeping or trial-based paradigms and demonstrates how naturally occurring behavioural variability can become a useful feature of fNIRS experimental design. More broadly, it generates new opportunities to directly test theories of neurobehavioural development in more ecologically valid settings.

Background: Late preterm (LP) children (34 0/7 - 36 6/7 weeks of gestation) are at risk for neurocognitive challenges, yet the neuroanatomic and functional disruptions underlying these developmental differences remain poorly understood. Purpose or Hypothesis: Investigate (1) regional differences in cortical surface area and thalamic nuclei volume and (2) structural variations that may explain heterogeneity in neurocognitive functioning in LP versus full term (FT) school-aged children, using two complementary approaches: a vertex-wise analysis of cortical surface area and a region-of-interest volumetric analysis of thalamic nuclei. Study Type: Secondary analysis of a prospective observational cohort study. Population or Subjects: 48 LP and 72 FT children aged 6-13 years. Field Strength/Sequence: 3T; Sagittal T1-weighted MP-RAGE and axial T2-weighted 3D SPACE. Assessment: FreeSurfer 7.4.1 was used to parcellate cortical regions (Destrieux atlas) and segment thalamic nuclei (25 nuclei). Neurocognitive functioning was assessed across four domains: hyperactivity/inattention (Pediatric Behavior Scale), processing speed (WISC-IV), working memory (WISC-III), and visual-spatial perception (Benton JLO). Statistical Tests: Independent samples t-tests for group comparisons; vertex-wise GLMs for cortical surface analyses with false discovery rate (FDR) correction; and multiple linear regression for thalamic nuclei analyses with FDR-corrected q < 0.05. Results: Vertex-wise analyses revealed regional differences in cortical surface area between LP and FT children in both hemispheres, along with associations between surface area in several cortical regions and hyperactivity/inattention, working memory, and visual-spatial perception. In contrast, using an ROI approach, thalamic nuclei volumes did not differ between groups and were not associated with any neurocognitive domains. Conclusion: LP birth may be associated with subtle, region-specific bidirectional left and right hemispheric cortical surface area differences rather than widespread structural alterations in middle childhood, with regional macrostructural measures associated with individual differences in neurocognitive functioning.

Introduction: The developing neural circuitry supporting adolescent risk-taking is vulnerable to metals, yet few studies have examined how early-life metal mixture exposure affects neural mechanisms underlying risk-taking. We used novel dentine biomarkers to identify critical windows of early-life metal mixture exposure associated with neurocognitive correlates of risky decision-making in early adolescence. Methods: Participants (ages 8-14, 45% female) were recruited from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) longitudinal birth cohort in Mexico City. Weekly concentrations of barium (Ba), copper (Cu), lithium (Li), magnesium (Mg), manganese (Mn), lead (Pb), tin (Sn), strontium (Sr), and zinc (Zn) were measured in children's deciduous teeth from 19 weeks pre-birth to 43 weeks postnatally. Neural activity during risky decision-making and reward processing was assessed using a functional magnetic resonance imaging gambling paradigm. Risk-taking tendency, risk sensitivity, and reward sensitivity were estimated from participants' decisions. We used lagged weighted quantile sum regression to examine time-varying associations between metal mixture exposure and neurocognitive outcomes, adjusting for child age, child sex, and socioeconomic status. Results: Higher metal mixture exposure during the early to late postnatal period was associated with increased risk-taking tendency and risk sensitivity. Exposure during the prenatal and late postnatal periods was associated with increased reward sensitivity and reduced activation in the angular gyrus/inferior parietal lobule during risky decision-making. Exposure during the late postnatal period was associated with increased activation in the insula/rolandic operculum during reward processing. Postnatal associations for risk-related and reward-related neural activation were primarily driven by Sr and Mg respectively, while postnatal associations for risk-taking tendency, risk sensitivity, and reward sensitivity were driven by multiple metals in the mixture. Conclusions: Early-life metal mixture exposure is differentially associated with neurocognitive correlates of risky decision-making in adolescence, depending on exposure timing.

Early life stress (ELS) is associated with altered social cognition, but the neurodevelopmental mechanisms of this association remain understudied. In the present longitudinal study spanning 20-years, eighty-nine young adults performed the Reading the Mind in the Eyes Test (RMET) with a matched control condition during fMRI. Two ELS indices were inspected separately: a prospective cumulative risk score based on caregiver wellbeing during pregnancy and first year of life, and a retrospective self-report of adverse experiences by the participants in late adolescence. Neural outcomes were characterized by univariate activation, representational similarity analysis (RSA), and inter-subject RSA. Inter-subject RSA tested two pairwise approaches to intersubject similarity in ELS: absolute pairwise difference, and pairwise average. Prospective ELS was associated with better RMET performance, and one region survived correction across 360 cortical regions tested in RSA and IS-RSA: left anterior inferior frontal sulcus. The IS-RSA effect was pairwise average: low-exposure participants shared a more typical neural representational geometry, while high-exposure participants demonstrated increasing neural representational idiosyncrasy. Additionally, higher prospective ELS was associated with weaker RMET-versus-control separation within the same region. Retrospective ELS yielded no behavioral nor neural associations. The present study offers novel findings relating to neural representations of mentalizing using the RMET, alongside their neurodevelopmental susceptibility to ELS. The present study additionally highlights implications relating to the differentiation of mentalizing from lexical-semantic and semantic-control demands for future research.

Background Child growth is usually summarized by an average trajectory, an approach that can hide clinically meaningful heterogeneity between children. This study aims to identify various growth phenotypes in Vietnamese children. Methods This study analyzed retrospective longitudinal anthropometric data from annual school health check of children in Hanoi, Hochiminh, and Haiphong, Vietnam from 2018 to 2025. Children with at least 4 visits spanning at least 3 years were included (8,612 boys and 6,107 girls). Height for age trajectory was summarized with functional principal component scores and combined with SITAR derived random effects for growth size, pubertal timing, and tempo, then clustered with sex specific Gaussian mixture models. We evaluated phenotype associations with prepubertal BMI category, cluster stability, and whether phenotype improved prediction of late adolescent height beyond baseline prepubertal variables. Results Ten growth phenotypes in boys and twelve in girls were identified. Phenotype membership was associated with prepubertal BMI category in both sexes. A tall, accelerated growth phenotype in boys (4.2% of boys) had the highest prepubertal obesity prevalence (53.5%) and strongest obesity association in external validation. The girls' phenotype solution was more sensitive to visit based eligibility criteria than the boys' solution. Adding phenotype to a baseline model improved prediction of late adolescent height in both sexes, more strongly in boys. Conclusions Combining functional and SITAR based clustering identified clinically distinguishable growth phenotypes in Vietnamese children linked to prepubertal BMI and late adolescent height. Sex specific validation is needed before these phenotypes inform clinical application.

Working memory (WM), a core executive function that supports learning and reasoning, undergoes rapid development during early childhood years. Neural activation patterns underlying WM have been extensively studied in both adults and children, revealing increasing involvement of the frontoparietal network (FPN) with age and coordinated interactions with the default mode network (DMN). However, relatively little is known about how these network interactions develop in children, particularly within the visuospatial domain. The present study investigated the influence of age and task performance on effective connectivity within the FPN and its interactions with DMN hubs during a visuospatial WM task in early childhood. Functional MRI data were collected during a visual n-back task with two WM load levels (0-back and 2-back) in 120 typically developing children aged 5-8 years. Dynamic Causal Modeling (DCM) with parametric empirical Bayes was used to estimate effective connectivity among eight regions of interest spanning the FPN and DMN. Behaviorally, age-related gains were steepest under high-load for accuracy, and under low-load for reaction time, suggesting WM capacity is a demand-sensitive marker of development at this age. At the network level, high-load robustly engaged the FPN, whereas low-load was associated with relatively greater engagement of DMN and episodic memory-related regions. Baseline effective connectivity was dominated by parietal-to-frontal drive and strong self-inhibition in the anterior cingulate cortex. Age-related effects on this architecture were sparse, involving asymmetric interhemispheric frontal coupling and reduced parieto-cingulate coupling, whereas accuracy-related effects were larger in magnitude, particularly at self-connections. More accurate children showed greater excitability in frontal and parietal FPN nodes alongside increased self-inhibition in the precuneus, a DMN hub, consistent with a neural efficiency account in which better performance reflects more selective, rather than more global, network engagement. Task load further shaped connectivity in distinct ways: low-load elicited widespread inter-regional modulation, whereas high-load predominantly modulated self-connections, with age and accuracy effects on this modulation dissociating by load. These findings suggest that, in primary school children, current task performance was associated with more pronounced differences in frontoparietal effective connectivity than was age, and that WM-related network engagement becomes increasingly selective and load-dependent across this developmental window.

Objective: To provide national norms, percentiles, and results of factor analyses for the ADHD symptoms and performance items on the parent-report and self-report versions of the Vanderbilt Assessment Scale (VAS) for youth ages 6 to 17. We hypothesized that symptom items would demonstrate separate inattention and hyperactivity/impulsivity factors, performance items would demonstrate interpretable latent dimensions, measurement invariance would be supported across age and sex, and symptom ratings would vary systematically by age and sex. Method: In a nationally stratified survey conducted in July 2025-March 2026, 2,230 parents of youth aged 6-17 years and 996 adolescents aged 12-17 years completed Vanderbilt Assessment Scale items. Both versions asked about the frequency of 18 ADHD symptoms and performance in 8 domains. To evaluate the psychometric properties and age-related normative curves of the VAS across parent- and youth-report forms, we conducted exploratory factor analysis, confirmatory factor analysis, and measurement invariance testing. We also generated age and sex-specific norms. Results: Factor analyses produced the expected two symptom factors and two performance factors. Developmental and sex-specific patterns of ratings of inattention and hyperactivity/impulsivity symptoms indicated that after increasing slightly during the preadolescent years, parent ratings of inattention symptoms declined and remained stable. In contrast, ratings of hyperactivity/impulsivity declined steadily with age. Normative data were generated using GAMLSS estimated centiles from fitted probability distributions. Conclusions: This study provides norms for the parent-report and adolescent self-report VAS. Findings underscore the importance of using sex- and age-based norms to better inform estimates of severity and diagnostic decision making.

We evaluated whether participant-separated within-cohort discrimination was retained when electroencephalography (EEG) classifiers for attention-deficit/hyperactivity disorder (ADHD) were applied to a different population and recording task. This exploratory reanalysis included 121 children performing a visual task and 79 adults recorded during eyes-open rest after basic channel screening. Both cohorts used Cz/F4, 128 Hz, and the first fifteen non-overlapping 2-second epochs per participant. Fixed logistic regression and random forest classifiers used spectral, amplitude-derived, and combined features. Internal evaluation used five repetitions of five-fold participant-grouped cross-validation; bidirectional transfer fitted transformations and classifiers only on the source cohort. Adult spectral balanced accuracy (BA) was 0.9519-0.9546, compared with 0.5504-0.5664 in children. Adult spectral logistic regression exceeded all 999 internal label permutations (Monte Carlo p=0.001; within-family Holm-adjusted p=0.002). Paired spectral-minus-amplitude conditional intervals excluded zero in adults but spanned zero in children. Cross-cohort spectral BA was 0.3584-0.4675, with area under the receiver operating characteristic curve (AUC) of 0.0309-0.3857 in the unchanged score direction. Increasing pediatric source-epoch budgets moved random-forest AUC toward 0.5, whereas logistic-regression AUC remained below 0.1. Strong adult internal discrimination thus coexisted with reverse cross-cohort ranking. These findings characterize the evaluated pipelines, not clinical diagnostic utility or a unique mechanism: age, task, and acquisition differences were not separated, target results had previously been inspected, and conditional intervals excluded model-refitting uncertainty.