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.

Normative brain growth charts in early life hold great promise for furthering basic and clinical science. We leverage the rapid, substantial development of visual cortex function that is indexed by visual-evoked potentials (VEP) in electroencephalography to create longitudinal normative growth curves of task-related brain function with 1374 observations contributed by 802 infants (57 to 579 days old) from South Africa, Brazil, and the United States. Site-specific models were cross-validated and showed excellent fits to other sites samples, demonstrating functional growth curves generalize across contexts robustly. Deviations from the normative growth models associated with early environmental and behavioral measures such as prenatal exposures and postnatal cognition. These findings demonstrate the utility of using functional growth charts to understand and potentially act on individual neurodevelopmental trajectories. VEP brain function growth charts represent a new direction for EEG research to support healthy brain development globally.

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.

The current study examined the relations between hippocampal structure (e.g., volume and neurite density) and performance on a trace eye blink conditioning (EBC) task in young children. Our first aim assessed whether individual differences in hippocampal volume were associated with trace EBC performance, using both percent Conditioned Responses (% CR) and CR onset latency or the average latency (ms) at which the child started their blink, as measures of hippocampal-dependent associative learning. Our second aim evaluated whether individual differences in hippocampal neurite density were associated with EBC performance using the same outcome measures. Typically developing 4- to 6-year-olds (N = 31; 14 girls; Mage = 5.67; SDage = 0.89) completed T1 and diffusion-weighted MRI scans and a 15-minute trace eyeblink conditioning task outside of the scanner. % CR and CR onset latency were computed across all tone-puff and tone-alone trials. While hippocampal volume was not associated with any of our EBC measures, greater hippocampal neurite density bilaterally, was associated with later CR onset. In other words, children with greater left and right hippocampal neurite density blinked closer to the US (i.e., air puff) than children with less hippocampal neurite density, indicating that structural changes in the hippocampus assisted in the accurate timing of conditioned responses.

Malnutrition, particularly undernutrition, is a critical global health challenge, contributing to nearly half of all deaths among children under 5 and severely impacting physical and mental health, along with neural and cognitive development. Prior research by Xie et al. (2019a) linked growth faltering to altered EEG functional connectivity (FC) at 36 months and poorer cognitive outcomes at 48 months; however, no associations were found at 6 months for EEG measures or at 27 months for cognitive outcomes. Our study investigates these relationships in a sample of 12-month-old infants in Dhaka, Bangladesh, using various growth measurements (height/length-for-age, weight-for-age, weight-for-height/length, head-circumference-for-age, and mid-upper-arm-circumference-for-age z-scores) as indicators of nutritional status. Brain development was assessed through EEG, focusing on power spectral density (PSD) and FC, while cognitive development was evaluated with the Bayley Scales of Infant and Toddler Development, Fourth Edition. Our findings reveal that, at 12 months, growth faltering, indicative of undernutrition, was associated with reduced PSD, while initial correlations with increased FC did not remain significant after false discovery rate (FDR) correction. PSD was further positively linked to cognitive development, but associations with FC were not significant post-correction. Notably, EEG PSD in the theta and alpha bands mediated the relationship between malnutrition and behavioral outcomes. These results underscore the early impact of malnutrition on brain development, highlighting the importance of PSD in understanding neural development in this context. Our study emphasizes the need for early intervention and continuous monitoring to mitigate the adverse effects of malnutrition on infant brain and cognitive development. RESEARCH HIGHLIGHTS- EEG power spectral density (PSD) in the theta and alpha frequency bands at 12 months sheds light on undernutritions impact on cognitive development. - Better nutritional health, indicated by higher height/length-for-age (HAZ), leads to increased theta and alpha PSD, contributing to better cognitive outcomes. - Initial correlations between undernutrition, increased EEG functional connectivity (FC), and poorer cognitive outcomes did not remain significant after FDR correction. - Findings highlight the critical role of nutritional interventions in early childhood to support optimal neural and cognitive development.

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.

The home literacy environment (HLE) in infancy has been associated with subsequent pre-literacy skill development and HLE at pre-school age has been shown to correlate with white matter organization in tracts that subserve prereading and reading skills. Furthermore, childhood socioeconomic status (SES) has been linked with both HLE and white matter organization. It is also important to understand whether the relationships between environmental factors such as HLE and SES and white matter organization can be detected as early as infancy, as this period is characterized by rapid brain development that may make white matter pathways particularly susceptible to these early experiences. Here, we hypothesized (1) an association between HLE and white matter organization in pre-reading and reading-related tracts in infants, and (2) that this association mediates a link between SES and white matter organization. To test these hypotheses, infants (mean age: 9.2 {+/-} 2.5 months, N = 18) underwent diffusion-weighted imaging MRI during natural sleep. Fractional anisotropy (FA) was estimated from the left superior longitudinal fasciculus (SLF) and left arcuate fasciculus using the automated fiber-tract quantification method. HLE was measured with the Reading subscale of the StimQ and SES was measured with years of maternal education. Self-reported maternal reading ability was also quantified and applied to all statistical models to control for confounding genetic effects. The Reading subscale of the StimQ positively related to FA in left SLF and mediated the association between maternal education and FA in the left SLF. Taken together, these findings underscore the importance of considering HLE from the start of life and may inform novel prevention and intervention strategies targeted at low-SES families to support developing infants during a period of heightened brain plasticity.

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.

Background: EEG provides a scalable method for elucidating neurophysiological characteristics that may distinguish mental health risk early in life, when symptoms are often non-specific, transdiagnostic, and pluripotential. Most prior studies have examined cross-sectional associations between individual EEG metrics and singular outcomes, potentially overlooking integrated patterns of neurophysiological organization. We applied data-driven clustering to infant baseline EEG to derive neurophysiological profiles and examined whether these profiles prospectively differentiated temperament and psychopathology domains in childhood. Methods: Participants were (N = 360; 46% female) from a longitudinal community cohort followed from infancy to age 7 years. Baseline EEG was collected in infancy (Mage = 7.81 months). Neurophysiological profiles were derived from spectral features (band-limited periodic power, peak frequency characteristics, and aperiodic exponent) using Bayesian model averaging of multiple clustering algorithms. Bayesian mixed-effects models tested profile differences in parent-reported temperament (surgency, negative affectivity, regulation/effortful control) across infancy and ages 3, 5, and 7 years, and child internalizing and externalizing symptoms at 5 and 7 years. Results: Consensus clustering identified four infant neurophysiological profiles characterized by: (1) elevated alpha/beta power, (2) low-frequency-dominant power, (3) globally attenuated oscillatory power, and (4) faster frequency-shifted dynamics. The profiles showed graded differentiation across childhood in effortful control (Cluster 1>2>3>4), with strong evidence for higher effortful control in Clusters 1/2 relative to Clusters 3/4 (posterior probabilities > .95). Additional differentiation was observed across surgency, negative affectivity, and psychopathology symptoms. Clusters 3/4 showed higher internalizing and externalizing symptom probabilities relative to Clusters 1/2, particularly Cluster 2, which also showed lower surgency relative to Clusters 1/3/4. Conclusions: Infant EEG-derived neurophysiological profiles prospectively differentiated temperament and psychopathology outcomes in childhood. With ongoing research, data-driven EEG profiling may provide a scalable, biologically informed framework for early mental health risk stratification prior to the consolidation of stable psychiatric diagnoses.

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

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.

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.

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.

How does the functionality of the cortex change from infancy to adulthood to support the developmental cognitive shift from learners to performers? Cortical adaptation is a simple neural mechanism which plays a key role in learning and memory encoding, but little is known about how it develops across the lifespan. Both infants and adults have been found to respond differently to repeating audio and visual stimuli, suggesting differences in cortical adaptation throughout development. However, studies typically approach these populations through different paradigms and interpret the results in terms of different cognitive models. To overcome these issues, we implemented an identical paradigm across all age groups to examine cortical adaptation and its developmental trajectory. We used functional near infra-red spectroscopy (fNIRS) to chart how different regions in the infant, child and adult brain respond to repeating audiovisual stimuli at varying inter-stimulus intervals (ISIs), using cortical adaptation as a proxy for implicit memory dynamics. We found faster recovery from adaptation in infants compared to children and adults. Specifically, there was an interaction between stimulus presentation rate and age in the right temporal, left parietal and occipital cortical areas. There was also a developmental progression in functional connectivity, with infants displaying significantly lower correlations between regions of interest than children and adults. Taken together, we suggest these findings may reflect the developmental trajectory of cortical adaptation from a learning system optimized for maximal information intake and minimal filtering of stimuli to a specialized integrative system that efficiently filters and adapts to information. HighlightsO_LICortical adaptation is a fundamental mechanism involved in memory and learning, but not much is known about how it develops throughout the lifespan. C_LIO_LIAn identical fNIRS paradigm across 3 different age groups reveals significant differences in cortical adaptation between infants, children and adults. C_LIO_LIFunctional connectivity revealed foundational connections present from infancy, growing stronger and into a specialized adaptation system with age. C_LI These findings suggest a developmental transition from a system optimized for maximal information intake to a specialized learning system, capable of filtering redundant information.

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.

Head motion during resting-state functional magnetic resonance imaging (rsfMRI) poses a major challenge for neuroimaging research, often leading to data quality concerns and participant exclusions, particularly among pediatric and clinical populations. Although necessary for ensuring reliable data, motion-related exclusions may inadvertently bias samples by disproportionately excluding certain sociodemographic groups. Using data from the Adolescent Brain Cognitive Development (ABCD) Study, we employed both frequentist and Bayesian approaches to examine how head motion-related exclusions and participant retention shape sample composition over time. At baseline (ages 9-10), Black, Hispanic, and Asian youth were significantly more likely than White youth to be excluded due to excessive head motion; these disparities were not observed at the two-year follow-up (ages 11-13). In contrast, disparities in retention persisted; Black participants were less likely to return for follow-up, even after accounting for socioeconomic factors and motion. Together, these findings highlight how both motion-related exclusions and differential retention can systematically influence the representativeness of longitudinal neuroimaging samples, with important implications for the generalizability of research in addiction neuroscience.

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.