Developmental Cognitive Neuroscience

BackgroundAdolescence is a period of rapid neurobiological and behavioural change, yet it remains unclear how deviations from normative brain maturation relate to the development of internalising and externalising symptoms. MethodsUsing data from the Adolescent Brain Cognitive Development (ABCD) Study, we combined brain age prediction with bivariate latent growth curve (BLGC) models to test whether deviations in brain maturation - indexed by the brain age gap (BAG) - relate to mental health development across late childhood and adolescence. Brain age was estimated using T1-weighted, diffusion (dMRI), resting-state fMRI, and multimodal MRI data across four waves (ages [~]8.3-17.5). Internalising and externalising symptoms were assessed across ten waves with the self-report Brief Problem Monitor (BPM). ResultsAcross T1, dMRI, and multimodal models, deviations from age-expected brain maturation and internalising and externalising symptoms showed coordinated nonlinear development across adolescence. Adolescents whose brains increasingly diverged from age-expected maturation over time also showed increasing symptom trajectories. These associations were small to moderate in magnitude and were most consistent for internalising symptoms in females (r = .15-.23), whereas externalising symptoms showed broader but less selective nonlinear associations across modalities in both males and females (r = .15-.23). Intercept-level associations were weaker and modality-specific (r = .06-.11). Formal tests provided no evidence for robust sex differences in these associations after correction for multiple comparisons. ConclusionThese results indicate that adolescent development of mental health problems is more strongly linked to nonlinear changes in how individuals diverge from age-expected brain trajectories, rather than to fixed differences in brain age. Shifts in brain maturational tempo may therefore be a key feature underlying vulnerability to psychopathology in youth.

ObjectiveTo examine whether screen time predicts interindividual variability regarding pubertal development across adolescence. Study designThis longitudinal cohort study included 10786 participants (47.9% female) from the Adolescent Brain Cognitive Development (ABCD) study. First, associations were examined between average daily screen time (hours/day, parent-reported Screen Time Survey) at baseline (mean age = 9.91 {+/-} 0.63 years) and pubertal timing, derived from Pubertal Development Scale (PDS) scores through 4-year follow-up (mean age = 14.08 {+/-} 0.68 years) and standardized by age and sex. Second, associations were examined between screen time groups (very low: 0-1.29 h/day; low: 1.29-2.07 h/day; moderate: 2.07-2.86 h/day; high: 2.86-4.0 h/day; very high: 4.00-12.43 h/day) and age at mid-puberty, defined as the age at first parent report of Pubertal Development Scale (PDS) category at least 3. ResultsIn linear mixed models adjusting for age, sex, race/ethnicity, socioeconomic status, BMI, and physical activity, higher log-transformed screen time at baseline was associated with more advanced pubertal timing at 1-, 2- and 3- year follow-ups, with the strongest effect observed at year 2 (standardized {beta}=0.07 [95%-CI, 0.05 to 0.10]). The associations were more pronounced in girls. The group of participants with very high screen time reached mid-puberty 2.47 months earlier [adjusted effect size, 95%-CI, -3.38 to -1.56) than participants with very low screen time. ConclusionThese findings suggest that screen time in late childhood is linked with earlier pubertal development and highlight its relevance for parental guidance on preadolescents screen media use.

Premature birth occurs during a phase of intense brain maturation, making white matter (WM) particularly vulnerable to injury. Beyond major lesions, subtle and widespread microstructural alterations also contribute to later neurodevelopmental impairments. We aimed to characterize the impact of key clinical risk factors on global and tract-specific WM microstructure at term-equivalent age (TEA), using 3T-diffusion-MRI data of 111 infants born before 33 weeks of gestation. We developed a lesion-robust tractography pipeline suitable for heterogeneous neonatal anatomy and extracted diffusion tensor imaging (DTI) metrics in sensorimotor tracts: corticospinal tract (CST), superior thalamic radiation (STR), frontal aslant tract (FAT), forceps minor (FMI) and middle cerebellar peduncle (MCP). Associations with risk factors were assessed accounting for age at MRI or global WM microstructure. Tractography succeeded in most infants despite marked anatomical variability and/or overt lesions. Being a male, small for gestational age (SGA) at birth, encountering sepsis and having severe Kidokoro radiological score for WM were associated with altered global WM metrics. At the tract level, CST and STR showed the strongest susceptibility to SGA, prolonged parenteral nutrition, and Kidokoro score. In contrast, for FAT, associations with extreme prematurity, SGA and invasive ventilation were contrary to the expected direction, after adjustment for global WM microstructure. Findings were partially replicated in infants without macroscopic abnormalities, supporting the presence of WM dysmaturation even in the absence of visible injury. DTI metrics thus provide tract-specific biomarkers of early WM microstructure in preterm infants, which are sensitive to risk factors and could inform targeted prevention and intervention.

ImportancePrenatal cannabis exposure is increasing in prevalence, yet its associations with early brain development--particularly how the timing and frequency of exposure across gestation relate to neonatal brain structure--remain insufficiently understood. Clarifying these associations is essential for informing early risk identification and guiding perinatal care. ObjectiveTo examine associations between patterns of maternal prenatal cannabis exposure, including exposure presence, gestational timing, and frequency of exposure, and neonatal brain structure and microstructure during the first month of life. Design, Setting, and ParticipantsThis cohort study included 1,782 mother-infant dyads (221 with PCE) from the HEALthy Brain and Child Development Study. Mother-reported prenatal cannabis exposure was assessed using the validated Timeline Follow-back method. Infants underwent natural-sleep magnetic resonance imaging, including T2-weighted structural imaging and diffusion imaging, within the first month of life. Main Outcomes and MeasuresAssociations between prenatal cannabis exposure and regional T2-weighted volumes and diffusion white matter microstructure metrics examined (1) exposure presence, (2) gestational timing of exposure, and (3) frequency of exposure within exposed infants. ResultsAny prenatal cannabis exposure was associated with brain volume differences in cerebellar and subcortical limbic regions, including smaller amygdala, thalamic, and cerebellar vermis volumes and larger caudate, hippocampal, and cerebellar cortex volumes. Timing-specific analyses revealed divergent patterns: first trimester exposure was associated with smaller volumes in select regions, whereas exposure that continued into the third trimester was associated with larger volumes in overlapping structures, with additional subcortical volumetric differences observed. White matter microstructure alterations were observed only among infants with exposure that continued into the third trimester. Within the exposed subgroup, higher frequency of cannabis exposure was associated with larger cerebral white matter volumes and white matter microstructural differences in white matter regions. Conclusions and RelevanceIn infants with maternal prenatal cannabis exposure, we observed timing- and frequency-dependent differences in brain development within the first month of life. These findings underscore the importance of considering not only the presence of exposure, but also when and how much cannabis is used during pregnancy to support targeted prenatal counseling and early developmental monitoring for exposed infants. Key PointsO_ST_ABSQuestionC_ST_ABSIs prenatal cannabis exposure associated with brain development in the first month of life? FindingsIn a cohort[ABS] of 1,782 mother-infant dyads, prenatal cannabis exposure was associated with region-specific differences in neonatal brain volumes. Brain volume and diffusion white matter microstructure associations differed between exposure limited to the first trimester versus exposure that continued into the third trimester. Greater frequency of exposure across gestation was also associated with volumetric and microstructural differences. MeaningThe timing and frequency of prenatal cannabis exposure is associated with alterations in neonatal brain development, underscoring the importance of addressing cannabis use in pregnancy.

BackgroundEarly relational health (ERH) is thought to buffer the association between early life stress (ELS) and child psychopathology, but limited work has directly tested this hypothesis. ObjectiveWe evaluate mother-infant emotional connection, a facet of ERH, as a buffer of combined and individual impacts of specific ELS exposures (maternal mental health and interpartner conflict) on child psychopathology. MethodsParticipants included mother-infant dyads (n=100) followed longitudinally in the COMBO cohort, a convenience sample recruited during the COVID-19 pandemic. ERH was assessed via a remote mother-infant face-to-face interaction at ~4mo postpartum coded for emotional connection. An ELS Index was estimated using measures of maternal self-reported postpartum anxiety, depression, stress, and inter-partner conflict. Mothers rated emerging signs of child psychopathology symptoms at 2-3yrs on the Child Behavior Checklist for Ages 1[1/2]-5 (CBCL/1[1/2]-5). Main and interactive effects of ELS and ERH on emerging signs of child psychopathology were tested in generalized linear models. ResultsGreater ELS Index scores were associated with a higher rate of emerging psychopathology symptoms (aRR=1.32, p<.001), but this association was moderated by a significant interaction between the ELS Index and emotional connection (aRR=0.99, p=.03), such that at higher levels of emotional connection, the association of ELS with child psychopathology symptoms was weaker (aRR=1.16, p<.001). ConclusionParent-infant emotional connection may buffer the impact of ELS exposure in infancy on child emerging symptoms of psychopathology in toddlerhood, supporting efforts to invest in pediatric interventions that target ERH.

Sleep problems and sensory over-responsivity (SOR) are common, co-occurring, and early-emerging features of Autism Spectrum Disorder (ASD). Yet, the early neural mechanisms underlying this relationship remain unclear. Here, we used resting-state fMRI data from the Infant Brain Imaging Study (IBIS) to examine how brain connectivity at 6 months may relate to parent-reported measures of sleep-onset problems and SOR in infants at varying familial likelihood for ASD. The right anterior insula was used in seed-based analyses to investigate Salience Network (SN) connectivity to cortical and cerebellar regions of interest previously implicated in sleep disruption, sensory processing challenges, and ASD. Infants at high (HL) and low (LL) likelihood for ASD displayed divergent patterns of SN connectivity with sensorimotor cortex, as well as cerebellar regions involved in sensorimotor processing and higher-order functions. Furthermore, stronger SN connectivity with sensorimotor cortices and cerebellar regions was associated with worse sleep-onset problems and SOR in HL infants. In contrast, stronger SN-cerebellar connectivity was related to fewer sleep-onset problems and SOR in LL infants. Our findings indicate that altered SN connectivity may result in over-attribution of attention to sensory stimuli and highlight aberrant sensory prediction learning, which may underlie worse sleep problems and higher SOR in HL infants.

BackgroundVolumetric assessment of the fetus, placenta and amniotic fluid is clinically valuable, but MRI volumetry is rarely performed in clinical practice because of the required labour-intensive manual segmentation of motion-corrupted 2-dimensional (2-D) stacks. Existing deep-learning approaches typically segment single structures in 2-D motion-corrupted stacks, are, however limited in accuracy by slice misalignment. No current method provides a reliable automated solution for whole-uterus volumetry in 3-D reconstructed MRI. Furthermore, normative ranges for computation of centiles are currently missing. ObjectiveTo develop an automated pipeline for whole-uterus volumetry in 3-D T2-weighted fetal MRI and to generate normative growth models for fetal, placental and amniotic fluid volumes in healthy pregnancies with confirmed delivery at term. Materials and methodsDeformable slice-to-volume 3-D reconstruction was applied to motion-corrupted T2-weighted (T2W) stacks from 0.55T-3T MRI, and a 3-D UNet was trained to segment fetus, placenta and amniotic fluid on the resulting reconstructed 3-D images. A reporting tool generates centiles, z-scores and structured HTML outputs. Automated segmentation was performed in 357 healthy control datasets from 16-41 weeks gestational age (GA) range with confirmed delivery at term. After visual checks of segmeted labels and minor refinements, GA-based quadratic normative volumetry models were derived and correlations with maternal and fetal characteristics assessed. The utility of the pipeline for clinical research was further evaluated using 95 longitudinal scans from 42 fetuses and 86 preterm ([&le;] 32 weeks at delivery) pregnancies. ResultsAutomated segmentation produced accurate 3-D labels, with only small local corrections (< 1% volume difference) required in the control cohort(< 25% of the datasets). Fetal and placental volumes increased across gestation, while amniotic fluid volume peaked mid-pregnancy and declined toward term. Volumes and centiles correlated with maternal size and birth weight. Longitudinal scans showed individual fetal and placental trajectories closely following the normative curves, with greater variability in amniotic fluid. Preterm pregnancies showed significantly lower fetal, placental and amniotic fluid volumes and centiles than the controls with confirmed delivery at term. ConclusionThis study introduces an automated whole-uterus volumetry pipeline and corresponding normative 3-D MRI growth models. The method provides robust, standardised volumetric assessment of fetal, placental and amniotic fluid development and offers a practical tool for evaluating growth patterns in both normal and high-risk pregnancies.

Comprehending how forces are applied to an object during manipulation can help provide important insights into the quality of behavior in daily tasks. We have developed the Bead Maze Hand Function test to objectively measure the quality of hand function in children. This test aims to measure how well an individual performs the activity by integrating measures of time and force control. The main objective of this study was to examine associations between a common clinical measure, the Box and Block Score (BBS), and variables on the Bead Maze Hand Function test that were either time-based or force-based. The sample was composed of neurotypical developing adolescent participants (N=23). We found that the time (duration) on the double curve wire (most complex) was the best predictor of BBT. Furthermore, we found that force-based variables were weak predictors of the clinical, time-based BBS. These findings support the integration of time and force-based metrics to holistically quantify the quality of motor behavior. Linking these metrics into a unified score may serve as a better way to analyze adolescent motor behavior and predict future motor or neurodegenerative conditions.

ObjectiveAlthough mental health and healthy lifestyle interventions are associated with functional outcomes in adolescence, the extent to which particular lifestyle factors explain relationships between mental health and outcome are unclear. Here we examined mediating effects of lifestyle factors on relationships between mental health and two functional outcomes measured 2-3 years later as well as the moderating effect of environmental risk factors on mediation strength in early adolescence. MethodsThis study analyzed data from 3 waves of the Adolescent Brain Cognitive Development Study (ages 10-11, 11-12, and 12-13). Mediating effects of sleep quality, screen time, physical activity and Mediterranean diet on the relationships between depression, anxiety, psychotic-like experience (PLE) distress, and total problems with two subsequent functional outcomes (academic functioning and social problems) were examined. Secondary analyses included environmental factors as moderators. ResultsSleep quality mediated 18.5%, 36.3%, 8.3%, and 3.4% of the relationships between depression, anxiety, PLE distress and total problems with academic functioning, respectively. Screen time was the second strongest mediating factor. For social problems, only sleep quality showed > 3% mediation (19.6% - 23.3%). Mediating effects of sleep and screen time on academic functioning decreased as financial adversity increased. Conversely, mediating effects of sleep quality on social problems increased with worsening family conflict, financial adversity, and school environment. ConclusionsThese results suggest that healthy lifestyle factors (in particular sleep quality) may partially explain the associations between mental health and functioning in adolescents and suggest that these effects are modulated by environmental factors. These results may have important implications for future intervention studies.

ObjectiveThe objectives of this study were to: (1) quantify toddlers total physical activity (TPA) and guideline adherence using a machine learning method; and (2) explore socio-ecological predictors (e.g., sex, childcare) of TPA. MethodsToddlers (n=103, 21.4 {+/-} 6.9 months, 52% female) from the Hamilton, Canada region completed a gross motor assessment (Peabody Developmental Motor Scales 2nd ed; PDMS-2) and wore an ActiGraph wGT3X-BT accelerometer on the right hip for 4-8 days. Parents completed demographics and physical activity surveys. TPA was estimated using a validated machine learning model and reported using descriptive statistics. Multiple linear regression explored potential predictors of TPA: age, sex, household income, older sibling, BMI-for-age z-score, gross motor z-score, childcare arrangement, parent physical activity, and temperature, controlling for accelerometer wear time. ResultsToddlers had an average of 200.3 {+/-} 44.0 minutes of daily TPA. Most (72%) met the PA guideline of 180 min/day when averaged across days, while only 27% met the guideline on all days. The regression model was significant and explained 57% of the variation in TPA (F13,79 = 8.09, p < 0.0001). Controlling for wear time, the only significant positive predictors were age and PDMS-2 z-score. ConclusionAlmost three quarters of toddlers met the TPA guidelines. Older toddlers and toddlers with more advanced gross motor skills for their age participated in more daily TPA. Future research should continue to apply machine learning methods in more diverse samples and could build on modifiable predictors (e.g., motor skill) to design interventions to improve toddlers PA levels.

ImportanceIndividuals exposed to perinatal risk factors are at increased risk for cardiovascular and neurodevelopmental disorders. Heart rate variability, an index of autonomic nervous system function, is widely used to assess long-term health risk in these populations, yet findings remain inconsistent. ObjectiveTo quantify heart rate variability differences between individuals with perinatal risk factors (including preterm birth, intrauterine growth restriction, and low birth weight) and healthy full-term controls, and to examine sources of heterogeneity. Data sourcesPubMed, EMBASE, Web of Science, Scopus, and APA PsycArticles were searched through April 2025, supplemented by ClinicalTrials.gov and reference screening. Study selection: Peer-reviewed studies reporting heart rate variability in perinatal risk populations versus healthy controls after hospital discharge. Of 7,781 screened articles, 27 met inclusion criteria. Data extraction and synthesisThis review followed PRISMA 2020 guidelines and was registered on PROSPERO (CRD42024527673). One reviewer extracted data using a standardized form, with verification by a second reviewer. A total of 176 effect sizes were extracted. Multilevel random-effects models accounted for dependency within studies. Main outcome(s) and measure(s)The primary outcome was heart rate variability difference between groups, expressed as Cohens d. ResultsAcross 27 studies (1,890 participants) and 176 effect sizes, the overall effect was modest and marginally significant (d = -0.24; 95% CI: -0.50 to 0.02; p = 0.07), with substantial heterogeneity (I{superscript 2} = 87.7%). Effect sizes differed significantly by perinatal condition (p < 0.001). Congenital heart disease (d = -1.07) and genetic syndromes (d = - 1.02) showed large heart rate variability reductions, while growth-related conditions showed moderate effects (d = -0.44). Heart rate variability differences attenuated with age ({beta} = +0.027 per year; p = 0.04), with strongest effects in early development (d = -0.85) and apparent normalization during adolescence. Conclusions and relevanceAutonomic consequences of perinatal adversity are condition-specific and developmentally dynamic. Structural and genetic conditions show pronounced deficits, while other conditions show substantial developmental heterogeneity. These findings underscore the importance of age- and condition-specific assessment and longitudinal follow-up. Key PointsO_ST_ABSQuestionC_ST_ABSDo individuals with perinatal risk factors show altered heart rate variability (HRV) compared to healthy controls, and what factors explain between-study heterogeneity? FindingsIn this meta-analysis of 27 studies, perinatal risk groups showed modestly reduced HRV compared to controls, with effects varying significantly by condition. Congenital heart disease and genetic syndromes showed large HRV reductions. Growth-related conditions showed moderate reductions. HRV differences were largest in early development and attenuated significantly with age. MeaningAutonomic consequences of perinatal adversity are condition-specific and developmentally dynamic, warranting age- and condition-specific clinical assessment.

Exposure is considered the most active element of cognitive behavioral therapy (CBT) for pediatric anxiety, and its efficacy is theorized to depend on cognitive control and its supporting neural substrates (e.g., central executive [CEN], salience [SN], and default mode networks [DMN]). However, little work has identified how CBT, or exposure specifically, modulates intrinsic connectivity of these networks. Progress may be limited by heterogeneity in network connectivity in anxiety, which may obscure treatment-related effects in group-averaged analyses. This randomized clinical trial (RCT) leverages person-specific network modeling to test how exposure-focused CBT (EF-CBT) influences resting-state connectivity of cognitive control networks in pediatric anxiety, relative to an active control (relaxation mentorship training; RMT). Youth aged 7-18 years with an anxiety disorder (N = 104) or low/no anxiety (L/NA; N = 37) completed resting-state fMRI scans before being randomized to EF-CBT or RMT. Resting-state connectivity was reassessed following treatment (or commensurate time L/NA youth) in 113 participants. Changes in within-CEN, CEN-SN, and CEN-DMN density were examined using Group Iterative Multiple Model Estimation, which yields sparse, person-specific networks capturing both shared and individual connectivity structure. At baseline, anxious youth exhibited lower density within-CEN, between CEN-SN, and between CEN-DMN than L/NA youth. Treatment effects differed by intervention: EF-CBT selectively increased (i.e., normalized) CEN-SN density, whereas RMT increased within-CEN density. These findings demonstrate dissociable effects of exposure and relaxation on cognitive control network organization in pediatric anxiety. Exposure-focused CBT uniquely strengthens coordination between control and salience systems, consistent with a mechanism supporting top-down control of threat-related signals during exposure. Network-based measures of cognitive control may help identify mechanistic targets for optimizing and personalizing treatment. Clinical Trial NumberNCT02810171.

Youth alcohol use is a significant global health concern. Despite the widespread nature of alcohol use-related problems, the longitudinal effects of alcohol on brain structure in youth remain unclear. This review aimed to systematically synthesise the findings from the longitudinal structural magnetic resonance imaging (sMRI) literature on how alcohol use is associated with changes in brain structure in youth. Following PRISMA guidelines, five databases were searched, and studies of youth alcohol use that measured brain structure using sMRI at more than one time-point were included. A label-based meta-analysis (i.e., ratio of number of significant effects for a specific brain region to total number of analyses for that brain region) approach was employed to synthesise the findings. Sixteen studies were included. There was preliminary evidence that youth alcohol use is associated with reduced cortical volume (particularly in temporal regions) and attenuated increases in white matter volume over time. The role of pre-existing structural differences, and other moderating factors remains unclear due to limited research. Future longitudinal studies are needed to clarify the clinical significance of neurodevelopmental changes associated with youth alcohol use. Significance statementThis systematic review synthesises evidence from 16 longitudinal neuroimaging studies on youth alcohol use and brain structure. Preliminary findings suggest adolescent drinking may be associated with reduced grey and white matter volume over time, with heavier consumption amplifying these effects. While methodological limitations prevent definitive conclusions, these potential neurodevelopmental disruptions during a critical brain maturation window could influence cognitive and behavioural outcomes. The review highlights the need for rigorous future research to further clarify the impact of alcohol on developmental brain trajectories, which could support targeted prevention approaches for adolescent brain health.

Epigenetic clocks and scores have been investigated as potential biomarkers of later-life health outcomes following early-life exposures. In pediatric settings, DNA methylation (DNAm) is often measured in saliva; however, most clocks and scores have been trained in adult blood. Therefore, we assessed the performance, correlation, longitudinal stability, and association with early-life adversity (ELA) for established epigenetic measures in matched pediatric blood and saliva samples. Leveraging the Kids2Health cohort of 291 children (3-12 years, 56% exposed to ELA), we assessed DNAm (Illumina EPICv2) from matched blood and saliva. We calculated 22 commonly used epigenetic measures (chronological and biological clocks, scores for body mass index [BMI], C-reactive protein [CRP], cognition, maternal smoking, telomere length) and compared them with corresponding measured phenotypes (chronological age, BMI, CRP, IQ, telomere length). Overall, performance of epigenetic clocks and scores in children varied widely. Nine epigenetic measures were significantly and equally correlated with their corresponding phenotype across tissues. Six measures were highly correlated between blood and saliva (r[&ge;]0.7). All age acceleration estimates showed low to moderate cross-tissue correlations (r=0.20-0.68). Epigenetic scores indicating lower cognitive ability and elevated inflammation were associated with ELA and low SES in both tissues. We additionally provide epigenome-wide blood-saliva correlations across 815,069 CpGs. The results indicate limited generalizability of adult-trained epigenetic clocks and scores to pediatric blood and saliva, even when accounting for cell type composition. We advise caution for cross-tissue and cross-age-range applications of epigenetic measures in research and clinical settings and provide a resource to optimize epigenetic biomarkers in children.

ObjectivesTo assess if maternal stress is higher in pregnancies with congenital heart disease (CHD) compared to low-risk pregnancies and if maternal stress is associated with placental microstructure and function. To explore if CHD alters the relationship between maternal stress and placental measures. MethodsIn this prospective observational study, 27 participants carrying a fetus with CHD and 42 participants with typical low-risk pregnancies underwent 1-2 combined diffusion{square}T2* relaxation placental MRIs from 20 weeks gestation (GA) and completed the Edinburgh Postnatal Depression Scale and State Trait Anxiety Inventory [43 male fetuses, median (IQR) GA at assessment 30.86 weeks (27.43-34.00), interval between assessments 6.00 weeks (4.86-7.14)]. 98 complete placental MRI and maternal stress datasets were available. Generalized Estimating Equations were used for analyses. ResultsHigher trait anxiety was associated with higher placental apparent diffusion coefficient (p=0.023) adjusting for CHD, sex, GA at assessment, GA at assessment2, state anxiety, depressive symptoms and previous mental health treatment. Maternal state anxiety (p=0.005) and depressive symptoms (p=0.046) were higher in pregnancies with CHD adjusting for GA at assessment and previous mental health treatment. CHD did not alter these relationships (p>0.119). ConclusionsMaternal proneness to anxiety, measured with the trait anxiety inventory, is associated with increased diffusivity in the placenta, which may reflect altered microstructural maturation. Mothers with fetal CHD show more depressive symptoms and feelings of anxiety and may benefit from screening for elevated maternal stress. The findings contribute to a growing body of research regarding the influence of prenatal stress on placental development. HighlightsO_LIMaternal stress and placental MRI data acquired in pregnancies with and without CHD C_LIO_LIMaternal trait anxiety is associated with increased placental diffusivity C_LIO_LIMaternal state anxiety and depressive symptoms are higher in fetal CHD C_LIO_LIState anxiety and depressive symptoms not associated with placental MRI measures C_LIO_LICHD did not moderate relationships between placental MRI measures and stress C_LI

The brain age gap (BAG) -- the difference between chronological and neuroimaging-based predicted brain age -- has emerged as a sensitive biomarker of brain health. A higher BAG, reflecting an older-appearing brain, has been linked to cognitive decline, neurodegenerative disease, and mental disorders. Whether such apparent aging can be mitigated by targeted interventions remains unclear. Oestradiol (E2), a sex hormone fluctuating across the menstrual cycle and known for its neuromodulatory and cognitive effects, may represent one such target intervention. To test this, we conducted a double-blind, randomized, placebo-controlled crossover study in 28 premenopausal females. Each participant was assessed twice during the follicular phase, with at least two cycles between sessions, and received either 12 mg E2-valerate or a placebo before undergoing a T1-weighted MRI scan. BAG was estimated using a pre-trained Simple Fully Convolutional Network model. Predicted brain age was significantly younger following E2 administration compared to placebo. Exploratory analyses indicated that this effect may be moderated by resilience factors for mental health: Higher self-esteem and use of greater social support seeking was nominally associated with lower BAG, whereas females applying more expressive suppression showed more apparent brain aging. These findings suggest that even short-term increases in E2, together with resilience factors, can influence brain age estimates. Thus, E2 interventions may provide a targeted approach to support both brain and mental health. These findings underscore the urgent need for further research into the impact of E2 on mental health across the female lifespan.

IntroductionLactate plays dual roles in neuronal energy metabolism and signalling. The dorsal anterior cingulate cortex (dACC), a region with high baseline glycolytic activity implicated in psychiatric disorders, may exhibit dynamic lactate responses to graded cognitive-emotional demands. Because mitochondrial function declines with age, aging may model whether fMRS-derived lactate dynamics can detect latent neurometabolic vulnerabilities. MethodsUsing fMRS, we monitored dACC metabolite changes in 34 healthy participants (aged 21-69) during an emotional face-processing task with escalating cognitive-emotional workload. The paradigm comprised a 2-minute baseline, 10-minute task of increasing intensity, and 10-minute recovery. ResultsdACC lactate increased significantly, tracking task intensity and peaking 19.5% above baseline at maximum cognitive load (z = 2.66, p = 0.004). The response showed both linear task-related increases (z = 2.08, p = 0.02) and a quadratic inverted-U profile (z = 2.72, p = 0.004). Total creatine, total NAA and Glx (Glutamate+Glutamine) exhibited no task-dependent changes. Age influenced task-period lactate AUC (z = 2.19, p = 0.014). Participants over 40 exhibited greater peak responses (54% vs 28%), steeper upslopes (14% vs 7% per block), and larger AUC (155% vs 16%) than those under 40. Sex differences were also observed. Baseline lactate did not correlate with age. ConclusionsdACC lactate dynamics are sensitive to cognitive-emotional demand, with evidence of age-and sex-dependent modulation. The dissociation between static and dynamic measures establishes a metabolic stress-testing paradigm for detecting latent neuroenergetic vulnerabilities, supporting fMRS utility for probing mitochondrial function in health and psychiatric disorders.

BackgroundEarly low-level alcohol use predicts subsequent alcohol use and problems. Impulsivity and poor inhibitory control also predict later problematic alcohol use. However, few studies prospectively examine early sipping in combination with modeling impulsivity and inhibitory control change over time as predictors of adolescent alcohol use. MethodsData Release 6.0 from the Adolescent Brain Cognitive Development (ABCD) Study was used (n=11,866; 48% Female). A series of linear mixed-effect models examined trajectories of non-religious sipping at baseline (ages 9-10) and self-reported impulsivity (UPPS-P) and task-based inhibitory control (Flanker task) over time as predictors of past year drinks and problematic alcohol use by ages 15-16. Predictors were run as separate models and a full model with all predictors together. Models were nested within the participant and study site. Interactions with age (to measure change over time from Baseline to Year 6) were included. Corrections for multiple comparisons were employed. ResultsIn individual models, four impulsivity interactions were significant: (1) negative urgency*age ({beta}=.04, FDR-p<.001), (2) positive urgency*age ({beta}=.04, FDR-p<.001), (3) lack of planning*age ({beta}=.04, FDR-p<.001), and (4) sensation seeking*age ({beta}=.04, FDR-p<.001), suggesting that as age increases, the relationship between impulsivity and alcohol use strengthens. Sipping*age ({beta}=.02, FDR-p<.001) interactions also predicted standard drinks. Regarding problematic use, there was a significant interaction in the full model: negative urgency*age ({beta}=-.07, p=.05), indicating that this relationship is more pronounced at earlier ages. ConclusionsTrait impulsivity and sipping in late childhood relate to future alcohol use, and the relationship strengthens with age. Our results found a negative interaction between negative urgency and age on problematic use, potentially indicating negative urgency as a phenotype of vulnerability to experiencing alcohol related problems at younger ages. Findings indicate the importance of understanding facets of impulsivity in the context of adolescent alcohol use for prevention and intervention efforts.

BackgroundExternalizing behavior refers to emotional and behavioral problems or disorders characterized by conducts directed outward at an individuals environment. Polygenic scores (PGSs) indexing the individual genetic susceptibility for this behavior still explain a small proportion of the phenotypic variance. To increase this phenotypic variance explained for externalizing behavior we used a multi-PGS approach combining PGSs for several risk factors, mental health conditions and related phenotypes. In addition, we assessed the potential moderating effect of socioeconomic status (SES). MethodsThe study included a total of 4,485 children and adolescents (mean age = 10.0 years; range = 5-18, 45% females) with behavioral and genetic data available. Externalizing behavior was assessed using the Child Behavior Checklist and PGSs were constructed using PRScs software. We tested two models and compared the proportion of variance that they explained: (i) a single-PGS model with the PGS for externalizing behavior (PGSexternalizing) and (ii) a multi-PGS model combining the PGSexternalizing with other PGSs for risk factors grouped in six categories: environment, mental-health, cognition, personality, health-risk behaviors and non-mental diseases. ResultsThe multi-PGS models for the categories of environment, mental-health, cognition and health-risk behaviors improved the variance explained of externalizing behavior in 20.9%, 37.6%, 35% and 34.2%, respectively, over the single model only including PGSexternalizing. Furthermore, we observed significant interactions between SES and the multi-PGS models of environment, mental-health, cognition and health-risk behaviors (P-interaction < 0.05), indicating that in individuals with lower SES, the influence of these four multi-PGSs on externalizing behavior is stronger. ConclusionThis study provides new insights into the genetic architecture of externalizing behavior in a population-based cohort of children and adolescents and further supports the utility of incorporating multiple PGSs into predictive models to improve accuracy, increase the proportion of variance explained, and maximize the predictive utility of PGSs. Additionally, by assessing GxE, we contribute to understanding the complex relationship between SES and mental health outcomes, highlighting its impact on youth.

Children with cerebral visual impairment (CVI) presenting an atelic profile constitute a population that is largely excluded from neurovisual research, primarily due to the absence of reliable behavioural responses to standard assessment or intervention paradigms. This exclusion often leads to the assumption that a lack of observable response reflects an absence of visual processing, despite converging evidence from neuroscience indicating that neural processing may persist in the absence of overt behavioural expression. This protocol describes a clinical feasibility study designed to evaluate the feasibility, tolerability, and measurement reliability of a passive visual mirror exposure paradigm in children with CVI and an atelic profile. The visual mirror is defined as the repeated presentation of a highly predictable, coherent visual experience, intended to reduce perceptual instability and cognitive load associated with typical visual environments, without aiming to restore or train visual function. The paradigm relies on passive visual exposure delivered via a large screen, or, where appropriate and tolerated, a virtual reality headset configured in a strictly non-interactive mode, without requiring effort, task engagement, or voluntary responses from the child. The study is embedded within a precautionary ethical framework specifically adapted to behaviourally non-responsive paediatric populations, defined here as children presenting absent voluntary behavioural responses to sensory or task-based instructions. Feasibility and tolerability are assessed using predefined safety criteria and non-verbal physiological indicators, including heart rate and autonomic markers, rather than behavioural performance. This feasibility study is designed to characterise the ethical acceptability, implementability, and physiological tolerability of the protocol in this vulnerable population, and to inform future research considerations without implying any obligation or commitment to subsequent studies.