Developmental Cognitive Neuroscience

IntroductionBody mass index (BMI) is widely used to screen for weight-related health risks during adolescence. Prior neuroimaging studies have assumed a linear relationship between BMI and brain microstructure, potentially obscuring how this association varies across the BMI distribution. Using restriction spectrum imaging (RSI) in the Adolescent Brain Cognitive Development (ABCD) Study, previous work has identified positive linear associations between BMI and weight-related metrics and the restricted normalized isotropic (RNI) signal fraction in subcortical structures, but it remains unclear whether these associations are uniform across the full BMI spectrum or driven by particular portions of the distribution. MethodsWe examined the relationship between BMI percentile and voxelwise RNI in subcortical gray matter and white matter structures using data from the ABCD Study 6.1 release, which includes four imaging timepoints spanning ages 9-18 years (22,011 observations from 10,465 unique participants). Sex-stratified generalized additive mixed-effects models with smooth terms for BMI percentile, age, and pubertal development were used to model the shape of the BMI-microstructure association across the full percentile range, controlling for genetic principal components, household income, parental education, and MRI scanner/software version. ResultsThe association between BMI percentile and RNI was nonlinear in the bilateral nucleus accumbens, caudate, pallidum, putamen, thalamus, and forceps minor. A modest, positive association was present across most of the BMI range, but the rate of change accelerated markedly above the 80th percentile. This pattern was consistent across structures and sexes, though the overall magnitude of the partial effect was higher for males across most structures, while females showed steeper rates of change in most structures above the 80th percentile. Voxelwise analyses revealed spatial heterogeneity within structures, with stronger effects concentrated in specific subregions including the posterior forceps minor, dorsal pallidum, anterior putamen, and posterior thalamus. DiscussionThe relationship between BMI and subcortical brain microstructure during adolescence is not uniform but instead accelerates at the upper end of the BMI distribution, suggesting that prior linear estimates may reflect a blended average of a modest slope across most of the range and a steep slope above the 80th percentile. These findings extend the existing literature by capturing a wider developmental window, employing voxelwise rather than ROI-averaged analyses, identifying the forceps minor as a novel region of interest, and highlighting the advantages of nonlinear modeling in revealing dynamic associations.

Adolescence is a critical period for the development of the brain, cognition, and mental health, which are shaped by a wide range of environmental factors. In the present study, we analysed the Adolescent Brain and Cognitive Development (ABCD) dataset to examine how a range of proximal (e.g., socioeconomic status, familial circumstances) and distal (e.g., neighbourhood conditions, access to healthcare and education) environmental factors are associated with changes in centile-based measures of brain structure, and whether these brain differences subsequently mediate variations in cognition and mental health. We analysed these associations both at baseline (N = 6,911; 3,605 M, 3,606 F; mean age = 9.93) and longitudinally across three timepoints (N = 1,628; 879 M, 749 F; ages 8-15). At baseline, a more advantaged proximal and distal environment was associated with larger volumes across the whole brain relative to age- and sex-matched peers, which, in turn, mediated better mental health outcomes and cognitive performance. In the longitudinal analysis, the childhood environment predicted changes in brain structure across adolescence, and these structural changes predicted changes in mental health and cognition. The childhood environment also predicted cognitive but not mental health changes across adolescence, suggesting that these associations may already be established early in adolescence. These findings provide insight into how environmental and neural factors shape adolescent mental health and cognition, with potential implications for early intervention strategies aimed at promoting positive developmental outcomes.

Introduction: The Pubertal Development Scale (PDS) is widely used for puberty assessment, yet its psychometric properties and norms are limited to research data. This study examined the psychometric properties of parent- and self-report PDS and established continuous norms in nationally representative samples. Methods: We analyzed two deidentified survey samples: a parent-report sample of children aged 6-18 (N=2000, Mage=11.37, 47.2% female, 74.9% White), and a youth self-report sample aged 12-18 (N=754, Mage=14.33, 49.6% female, 75.3% White). Both samples were representative of the U.S. population on key demographics, and the self-report sample consisted entirely of children whose parents also participated in the parent sample, thus creating parent-child dyads. Internal consistency was evaluated using Cronbach's alpha and McDonald's Omega. Cross-informant agreement was assessed with Intraclass Correlation Coefficient (ICC; two-way model, absolute agreement, single unit) and Bland-Altman plots. Age-dependent norms of each sex were established with Generalized Additive Models for Location, Scale, and Shape (GAMLSS), with 5th-95th percentile curves and reference tables provided. Results: Parent- and self-report PDS demonstrated acceptable-to-good internal consistency (Cronbach's alpha: 0.78-0.89; McDonald's omega: 0.79-0.90). Among the 754 parent-youth dyads, excellent cross-informant agreement was observed for both sexes (ICC(2,1)=0.88). Parents' and children's PDS total scores did not differ significantly for boys; for girls, parents rated pubertal development on average 0.13 points lower than children's self-report. Regardless of informants, PDS scores increased nonlinearly with age and exhibited sex-specific developmental patterns. Girls showed earlier pubertal onset, faster progression, and greater convergence toward pubertal completion by late adolescence. Discussion: The PDS demonstrated strong psychometrics in national samples, supporting its utility in the general pediatric population. The national norms provide empirical benchmarks for PDS score interpretation, strengthening its value as a broad estimation of pubertal status and a pre-screening tool for identifying early or delayed puberty.

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.

BackgroundSubstance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. MethodsWe conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes--alcohol, nicotine, cannabis, and any substance use--using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochrans Q and I2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. ResultsIn the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol [~] 1 x 10-7, any [~] 1 x 10-7, cannabis [~] 5 x 10-8, nicotine [~] 1 x 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 x 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. ConclusionsSurvival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

Objective: To investigate overall and neighborhood socioeconomic deprivation moderated associations between glycemic control and brain structure in youth. Research Design and Methods: This was a cross-sectional study of 705 healthy 11-12-year-olds across 21 study sites in the United States. Data was obtained from the Adolescent Brain and Cognitive Development (ABCD) Study(R). Glycemic control was assessed using hemoglobin A1c (HbA1c), brain structure was evaluated via MRI, and neighborhood deprivation was measured with the Area Deprivation Index (ADI). Mixed effects models were used to examine relationships between HbA1c, brain structure and ADI controlling for sociodemographic covariates. Stratified analysis was performed by tertiles of ADI. Results: Higher HbA1c was associated with lower mean cortical thickness (CT) and smaller total cortical gray matter volume (GMV). One percent increase in HbA1c corresponded to a 0.024 mm reduction in mean CT and a 9,611 mm3 reduction in total cortical GMV. Regionally, higher HbA1c was associated with thinner cortex and smaller gray matter volumes primarily in the frontal, cingulate and occipital areas. There was a significant interaction of HbA1c and ADI on total GMV, which was driven by significant negative associations of HbA1c with total GMV in the high ADI group, and medium ADI group, but not the low ADI group. Conclusions: Mild elevations in HbA1c, even within the non-diabetic range, are linked to early brain structural changes, particularly in youth from neighborhoods with greater socioeconomic deprivation. These results highlight the interplay between metabolic health and neighborhood deprivation on shaping brain development in youth.

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.

Brain networks that support episodic memory development in the first years of life remain poorly understood. Protracted growth of regions such as the hippocampus have been suggested as a causal role in episodic memory development, but development of these memory brain networks and their role in episodic memory development is not yet fully elucidated. In this study, subcortical memory network regions (hippocampus, thalamus, amygdala) were segmented from MRI images in 835 visits spanning 0-4 years of age across 322 participants in the Baby Connectome Project. Hippocampal segmentations were further subdivided into head, body, and tail subregions manually for 426 visits, which were used to train models that automatically segmented hippocampal subregions for the remaining visits. 58 participants returned for an early school-age follow-up, including two episodic memory tasks. Volumetric growth trajectories differed across regions and across subregions within the hippocampus, with the head of the hippocampus showing steep growth that plateaued months later than the body or tail of the hippocampus. In the right hemispheres hippocampal head, age- and sex- adjusted volumes positively predicted future early school-age episodic memory performance. After accounting for total brain volume, the right thalamus also predicted memory performance. Total sleep duration at the follow-up visit accounted for performance variance above and beyond brain volume correlations. Altogether, results suggest that trajectories of growth and relationships between volume and episodic memory performance are region and subregion specific, and provide evidence for the important role of sleep in associations between brain networks and early episodic memory development. SignificanceThe hippocampus is a critical structure in episodic memory, yet precise longitudinal developmental trajectories of this structure have yet to be elucidated. This study provides detailed, subregion specific hippocampal trajectories, and demonstrates that variation in these trajectories is associated with variation in later episodic memory performance. This insight fills a current gap in the literature delineating how brain development and episodic memory behaviors are related in the first five years of life. Considering this is the same age range during which adults begin to have long-term memories available from childhood, this gap represents an important opportunity to understand how changes in the brain support the development of basic episodic memory skills.

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.

Early-life stress elevates the risk of developing neuropsychiatric disorders. However, the mechanism underlying this vulnerability, and how they contribute to sex differences in these disorders, remain to be understood. Here, we use multivariate brain-based predictive models to examine how the number, positive or negative appraisal, and impact of adolescent stressful life events reported either by the youth or their caregivers are reflected in neuroanatomy (cortical thickness, surface area, cortical and subcortical gray matter volume, and T1 intensity measures). We used data from the Adolescent Brain Cognitive Development (ABCD) study at 2-year (N = 6,301, age 11-12), 4-year (N = 5,000, age 13-14) and 6-year (N = 3,226, age 15-16) follow-up time points to examine the sex-independent and sex-specific neural correlates of stressful life events. Our analyses showed mostly non-significant associations between stressful life events and neuroanatomy. However, we did find that the number of positively appraised stressful life events reported by the caregivers at the 4-year follow-up was significantly associated with cortical thickness, independent of sex, and with surface area in females only. Across three developmental timepoints, seven neuroanatomical measures, two reporting perspectives, and both sex-independent and sex-specific analyses, we show that the number, appraisal, and impact of stressful life events are largely not reflected in adolescent neuroanatomy.

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

Previous research has demonstrated that children exhibit superior - as compared to adults - consolidation of newly acquired motor sequences across post-learning periods of wakefulness. Given that consolidation is thought to be supported by the reactivation of learning-related patterns of brain activity during the rest periods following active task practice, we hypothesized that the childhood advantage in offline consolidation may be linked to greater reactivation during post-learning wakefulness. Twenty-two children (7-11 years) and 23 adults (18-30 years) completed two sessions of a motor sequence learning task, separated by a 5-hour wake interval. Multivoxel analyses of task-related and resting-state functional magnetic resonance imaging data were employed to assess the persistence of learning-related patterns of neural activity into post-task rest epochs, reflective of reactivation processes. Behavioral results demonstrated the previously reported childhood advantage in offline consolidation over a post-learning wake interval. Imaging results revealed that children exhibited greater persistence of task-related hippocampal - but not putaminal - activity into post-learning rest as compared to adults. These findings suggest that the childhood advantage in awake motor memory consolidation may be supported, at least partially, by enhanced reactivation of task-dependent hippocampal activity patterns during offline epochs.

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.

Humans possess an astounding ability to acquire complex movement sequences with limited practice. Motor sequence learning engages a distributed network of brain regions that show distinct learning-related changes: the prefrontal cortex (PFC) is predominantly involved early in learning, whereas the primary motor cortex (M1) becomes increasingly engaged later in learning. Because motor regions mature relatively earlier than the PFC during development, we examined how children and adults differ in the time course of neural changes underlying motor sequence learning. Using functional magnetic resonance imaging (fMRI), we compared brain activation in children (7-10 years, N = 39, 17 female) and adults (20-32 years, N = 39, 19 female) during an associative visuomotor learning task. In both age groups, response times decreased with sequence repetition, with greater reductions in adults than in children. Across age groups, early learning was associated with heightened PFC activation, whereas later learning was characterized by increased activation in left M1 and bilateral supplementary motor area. Children and adults showed comparable decreases in PFC activation and PFC-M1 connectivity with sequence repetition. In contrast, adults exhibited larger learning-related increases in activation and stability of multivariate patterns in left M1. Together, these findings indicate that although both age groups engage the PFC similarly to support increased control demands in early learning, children show less pronounced modulation of M1 activation and representational similarity, suggesting that M1s capacity to form stable, sequence-related representations may still be developing in middle childhood. Significance StatementAlthough motor sequence learning has been widely studied in adults, less is known about how brain activation changes as learning progresses during childhood. This question is particularly relevant because prefrontal cortex (PFC) and primary motor cortex (M1) both support motor learning, but mature at different rates, with PFC developing relatively later than M1. Here, we used functional MRI to compare children (7-10 years) and adults performing a motor sequence learning task. We found no age-related differences in PFC engagement early in learning; instead children showed less refinement of M1 activation and neural representations over the course of learning than adults. These findings provide new insight into how the brain supports motor learning throughout development.

Summary paragraphA hallmark of learning is the need for sensory stimuli (Ginns, 2015; McGraw et al., 2009; Reinwein, 2012; Spence, 1950) so that learning is fundamentally based on sensory input signals affecting behaviour, physiology, and neurology. If behavioural measures of learning can be causally linked to physiological and neurological variables, a broader understanding of the mechanisms related to learning in schools, learning disabilities, and learning and health issues may emerge (McGraw et al., 2009). Despite decades of research on the physiological/neurological variable of sympathetic activation, learning, and achievement (Horvers et al., 2021), any causal relation remains unclear (Cowley et al., 2014; Mason et al., 2020; Pijeira-Diaz et al., 2016; Sung et al., 2023; Yu et al., 2024) and issues with instrument validation remain (Costantini et al., 2023; Hu et al., 2024; Milstein & Gordon, 2020; Van Der Mee et al., 2021). Here we investigate the effect of sensory input on sympathetic activation by using validated instruments for skin conductance measurement (Batista et al., 2019) and whether sympathetic activation is connected to learning in a cognitive laboratory context and an ecologically valid classroom context. In both contexts, we found a physiological variable which correlated with learning and that sensory input affected this variable while student movement did not. These sensory inputs varied depending on the different instructional activities the students participated in. Together, these findings bring us one step closer to a model linking sensory input to behavioural, physiological, and neurological variables.

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.

Play is a fundamental aspect of childhood and plays a crucial role in the development of creativity, yet its neural mechanisms remain poorly understood. We tested the hypothesis that more frequent play is associated with stronger functional integration among the default mode network (DMN), executive control network (CN), and salience network (SAL), as these cortical networks have been implicated in creativity in adults. In a preregistered study of infants and toddlers (Study 1; N = 143, 10 months-3 years, 67 boys, Baby Connectome Project), parent-reported play and imitation behaviors increased sharply from 1 to 2 years, and were associated with stronger within-DMN connectivity and DMN-CN coupling, controlling for age, sex, and head motion. In middle childhood (Study 2; N = 108, ages 4-11 years, 52 boys), parent-reported play frequency declined with age, as did cross-network coupling involving SAL. However, children who engaged more frequently in play showed higher DMN-SAL and CN-SAL connectivity. Finally, in a quasi-experimental comparison (Study 3; N = 45; ages 4-12 years, 20 boys), children enrolled in a curriculum that includes guided play (Montessori) showed higher DMN-SAL and DMN-CN connectivity than peers in traditional schools, suggesting that pedagogies that center child-led exploration might enable protracted brain network integration. Across these three studies, play was consistently associated with greater integration among DMN, SAL, and CN, a pattern previously linked to creativity in adults. Our findings offer a potential mechanism linking childhood play to later creativity through its role in supporting brain integration during development. Public Significant StatementO_LIPlay is widely believed to nurture childrens creativity, yet the brain mechanisms behind this link are not well understood. C_LIO_LIAcross three studies from infancy to middle childhood, we found that more frequent play was associated with stronger integration among brain networks tied to imagination, attention, and control. C_LIO_LIThese findings suggest that play may help build the neural foundation for later creative thinking. C_LI