Developmental Cognitive Neuroscience

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

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

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.

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.

Globally, 60% of the population has experienced at least one type of adversity (e.g., emotional abuse, bullying) across infancy, childhood, and adolescence. Such experiences have been linked to an increased risk for mental health disorders. Changes in brain structure following experiences of childhood adversity have been hypothesised to be a mechanistic pathway explaining later mental health issues. However, to understand how changes in brain structure might mediate the effects of adversity, it is essential to identify which underlying neuronal processes may be affected by different types of adverse experiences. A key open question is whether grey or white matter is more vulnerable to adversity, as these two structures reflect distinct neurobiological mechanisms. This study investigated whether differences in trajectories of grey and white matter development during adolescence can be explained by exposure to different types of adversity. We applied the Adverse Adolescent Experiences Framework (Pollmann et al., 2025) categorising adversity into four levels: Intrapersonal (e.g., accidents), Caregiver (e.g., emotional neglect), Peer (e.g., bullying), and Community (e.g., neighbourhood safety). Exposure to each of the four factors was estimated through principal components analyses. We analysed two large longitudinal datasets: the Adolescent Brain Cognitive Development study (~12,000 adolescents measured at ages 10, 12, and 14) and the IMAGEN study (~1,400 adolescents measured at ages 14, 19, and 22). Using latent growth curve models, we captured individual differences in brain development by estimating baseline levels (intercepts) and rates of change (slopes) for total grey matter volume and mean white matter fractional anisotropy. In both cohorts, we found significant interindividual variability in baseline levels and rates of change for both grey matter volume and fractional anisotropy. Caregiver, Peer, and Community adversities were negatively associated only with the intercepts of grey matter volume and white matter fractional anisotropy. Importantly, associations differed between grey and white matter. In ABCD, Peer and Community adversities were more strongly associated with grey matter volume intercepts. In contrast, in IMAGEN, Caregiver, Peer and Community adversities were more strongly linked to white matter fractional anisotropy intercepts. This suggests that adversity has unique associations with grey and white matter, rather than exerting a uniform influence on brain structure. By demonstrating that different environments generate distinct biological associations with brain maturation, this work underscores the need to consider both grey and white matter when assessing the neurodevelopmental pathways to outcomes across the lifespan.

Speech consists of regularities at different timescales. Already during infancy, neural electrophysiological activity aligns to these rhythms. The degree to which infants exhibit neural tracking of speech can be linked to their language development. In this study, we examined how the neural tracking of sung speech develops across age, from infancy to early childhood, and across different frequency bands (i.e., at the stress, syllabic, and phonemic rates), and whether neural tracking at each frequency and age predicts childrens language outcomes. We included 2565 children of the longitudinal YOUth cohort. Children listened to Dutch sung nursery rhymes while EEG was recorded at three measurement waves. After preprocessing the data, we included 955 children at 5 months, 1048 children at 10 months, and 795 children at 2-4 years. The final sample consisted of 750 children who also completed a receptive vocabulary test at 2-4 years. Children from 5 months onwards showed significant neural tracking of stressed syllables, syllables, and phonemes, measured with speech-brain coherence (SBC). Unexpectedly, there were no developmental changes in SBC across different frequency bands from infancy to early childhood. As expected, children with larger receptive vocabularies showed increased SBC in the stressed syllable rate. These findings suggest that stronger tracking of stressed syllables is related to individual differences in language ability.

This study explores the nonlinear developmental trajectories of brain networks in neurotypically developing infants during their first six months. Using a longitudinal dataset of 137 resting-state functional MRI scans from 74 infants, we analyzed five spatial metrics across 13 intrinsic connectivity networks, including motor, visual, subcortical, and prefrontal networks. A cubic model was specifically employed to capture distinct linear and non-linear trends in the networks developmental patterns, allowing for the identification of significant differences in cubic, quadratic, and linear slope parameters across networks. This model choice was driven by the need to examine how specific non-linear components (e.g., inflection points and acceleration rates) uniquely characterize each networks trajectory, which a generalized approach might smooth out without pinpointing such network-specific features. Notably, the subcortical network exhibited a distinct cubic growth pattern, while secondary motor and visual networks showed pronounced quadratic variations, suggesting network-specific shifts in spatial organization and connectivity. These findings highlight the unique maturation timelines and interactions between functional systems, such as early sensory-motor coordination and later cognitive integration. The results underscore the importance of network-specific growth patterns, providing deeper insights into how infant brain networks evolve and interact to support emerging cognitive and behavioral functions.

Adolescence and early adulthood are marked by rapid neurobehavioral development in reward and decision-making processes, coinciding with the initiation and escalation of alcohol use. While adolescent and young adulthood alcohol initiation is not atypical, adult trajectories diverge: some individuals reduce or discontinue use, whereas others escalate to more frequent or problematic patterns leading to substance use disorders. Corticostriatal circuits, including the ventral striatum (nucleus accumbens; NAcc) and dorsal striatum (caudate and putamen), support reward processing, goal-directed behavior, and habit formation, and are thought to contribute to distinct stages of alcohol use. Yet, how the normative maturation of these circuits relates to alcohol initiation and the transition to habitual consumption remains unclear. We used data from the National Consortium on Alcohol and NeuroDevelopment in Adolescence and Adulthood (NCANDA-A) cohort (822 participants, baseline ages 12 - 22 years old, 1 - 9 visits per participant, 4,356 total visits), a large multisite longitudinal neuroimaging sample spanning adolescence to young adulthood. We observed that rsfMRI functional connectivity (FC) patterns varied systematically across striatal subdivisions: NAcc FC followed an inverted U-shaped trajectory, peaking during adolescence; while caudate and putamen FC showed monotonic decreases with age. Adolescent peak NAcc connectivity was associated with alcohol use initiation, while a lack of normative decrease in putamen connectivity was linked to more frequent alcohol use in adulthood. Together, results suggest that the maturation of reward processing circuitry may support alcohol initiation, while a lack of habit system specialization may contribute to continued alcohol use, with potential implications for the timing of interventions aimed at limiting at-risk drinking.

Down syndrome (DS) is the most common genetic cause of intellectual disability, yet age-related cortical maturation patterns that contribute to developmental delays remain poorly understood. We analyzed longitudinal resting-state EEG and developmental data from 86 children with DS and 154 typically developing (TD) children between 12 and 81 months of age. Linear mixed-effect models tested age-related trajectories of aperiodic and periodic spectral features, and manifold learning was used to characterize multivariate EEG profiles associated with age and developmental ability. Children with DS showed altered maturation across multiple EEG features. Aperiodic exponent decreased with age in DS, but not TD children, indicating possible altered maturation of cortical excitability. While TD children showed expected age-related increases in theta-alpha peak frequency and amplitude, children with DS exhibited limited alpha maturation and greater persistence of theta-only and theta+alpha peak profiles. We next asked whether multivariate EEG organization reflected chronological maturation or individual differences in developmental ability. A spectral dimension associated with chronological age in TD children was not similarly age-associated in DS. Instead, a second spectral dimension was associated with verbal developmental quotient in children with DS, independent of chronological age and nonverbal developmental ability. This language-associated profile included features considered atypical relative to TD maturation, including increased aperiodic activity and continued presence of theta activity. These findings suggest that in DS there is an altered relationship between cortical spectral organization, chronological age, and language development, extending beyond a uniform delay in typical maturation.

Decades of developmental memory research has mainly reported linear and protracted changes in both human hippocampal function and connectivity between the hippocampus and cortex. While foundational, very few studies have interrogated the reliability of hippocampal signals across age, and how this coincides with (or diverges from) age-related changes in connectivity to broader cortical networks supporting multiple memory systems. Here, utilizing movie-watching fMRI data in children 3 to 12 years and adults, we assessed hippocampal response stability using an inter-subject functional correlation (ISFC) approach, and then measured functional connectivity between the hippocampus and the Posterior Medial (PM) - Anterior Temporal (AT) cortical memory networks proposed to support episodic-like (PM) and semantic-like (AT) memory respectively. Results showed that hippocampal responses are stable in the youngest children, but bifurcate in 7 year olds, with half the subjects correlating most highly with younger and half with older age groups. Likewise, we found that while functional connectivity within the AT network is stable across development, connections between the anterior hippocampus and this network did not reach adult levels until around 7 years. Thus, while brain networks supporting semantic memory may be in place early, interactions with the hippocampus may not develop until after middle childhood, with an inflection point around 7 years of age.

Acquiring reading proficiency, unlike spoken language, requires the brain to engage several specialized neural systems to map visual symbols (letters) to their corresponding phonological sounds (audiovisual integration), laying the foundation for fluent reading. This study investigates the neural and behavioral trajectory of developing audiovisual (AV) integration during the first year of learning to read. Thirty-two healthy Hebrew-speaking first-grade children were assessed at 3 time points across the school year: beginning, middle, and end of first grade. Participants underwent behavioral testing and brain fMRI scans while performing a block-design fMRI task involving AV matching or non-matching letters and sounds. Together with improvement in behavioral test scores related to general abilities, working memory, cognitive flexibility, and phonemic abilities, a Drift Diffusion Modeling (DDM) analysis of the accuracy and reaction time across sessions suggested faster and more efficient responses as the year progressed. fMRI results showed a significant increase in activation, from the beginning to the end of the first grade, in the left superior temporal gyrus (STG), frontal cortices and parietotemporal cortices, with a shift towards left-lateralization in the fusiform gyrus at the end of the year. These findings point towards the second half of the first grade as the time window for neural specialization and lateralization to phonological and orthographic information. A significant positive correlation between the fusiform gyrus activation and naming objects and colors scores across all sessions links this neural specialization to cognitive flexibility behavioral skills. Key pointsO_LISignificant increase, predominantly between the middle and end of the first grade, in activation in fusiform, left superior temporal, frontal, and parietotemporal cortices across the first grade. C_LIO_LISignificant left lateralization in the fusiform gyrus at the end of first grade. C_LIO_LIPositive correlation between naming skills and a bilateral fusiform gyrus activation throughout the first grade. C_LI

Objective. The autonomic nervous system, which regulates cardiac rhythm, undergoes pronounced maturation across adolescence. How cardiac rhythm develops over this period, however, and whether individual differences in its development forecast mental and physical illness, remain open questions. We used three waves of Fitbit data from the Adolescent Brain Cognitive Development (ABCD) Study to characterize the developmental trajectory of the cardiac rhythm and to test whether variation in that trajectory predicts onset of psychopathology and cardiometabolic disease. Methods. 8,301 adolescents contributed 242,811 valid Fitbit wear days across Waves 2 (Mage=12), 4 (Mage=14), and 6 (Mage=16). Cosinor mixed-effects models yielded three rhythm parameters per session: mesor (24-hour mean), amplitude (diurnal swing), and acrophase (peak timing). We first characterized age- and sex-specific trajectories, cross-wave stability, and factors shaping the rhythm. We then used parallel-process latent growth models to test whether within-person changes in rhythm tracked symptom trajectories, and hierarchical logistic models to test whether rhythm parameters predicted the first clinical onset of psychopathology and of obesity and hypertension. Results. The cardiac rhythm changed substantially across adolescence: mesor decreased, amplitude flattened, and acrophase shifted later. Within-person change in the rhythm tracked change in blood pressure, BMI, and trajectories of depression and ADHD symptoms. Higher mesor predicted incident onset of all five outcomes controlling for demographics, baseline symptoms, and behavior (ORs 1.36-1.54); amplitude, acrophase, and rhythm instability conferred additional risk. Conclusions. The 24-hour cardiac rhythm is a passively measurable substrate of adolescent autonomic development that indexes transdiagnostic risk for psychiatric and cardiometabolic illness.

BackgroundPer- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental pollutants that are posited to be neurotoxic to the developing brain; however, the impact of prenatal exposure to PFAS -- particularly to newer, short-chain PFAS -- on brain development across childhood is unclear. MethodsConcentrations of 9 PFAS were quantified in cord blood plasma of 459 infants who later participated in structural and diffusion magnetic resonance imaging (MRI) at ages 4.5, 6, 7.5, and 10.5 years, providing estimates of regional cortical thickness and surface area, subcortical volumes, and fractional anisotropy (FA) of key white matter tracts. Longitudinal mixed effect models estimated associations of PFAS with age 4.5 brain metrics and their developmental trajectories across childhood. ResultsHigher concentrations of long-chain PFAS (PFNA, PFHxS, PFDA) in cord blood were associated with lower surface area of the right paracentral lobule at age 4.5. PFHpA was associated with faster surface area growth in the left rostral anterior cingulate and slower growth in the right caudal middle frontal gyrus from 4.5 to 10.5 years. The short-chain compound PFBS was linked with greater FA in 17 of 27 white matter tracts at 4.5 years; those associations attenuated with age. Finally, PFOA was associated with lower FA in 6 tracts at 4.5 years. ConclusionsPrenatal exposure to PFAS was associated with altered development of frontal and paracentral regions and of white matter microstructure. These findings highlight the need for further research examining the long-term effects of prenatal exposure to PFAS on childrens neurodevelopment.

Brain-age estimates from grey matter structure provide a promising tool to examine the neurobiology of mental health. However, whether existing models generalise to longitudinal adolescent data remains unclear. The CentileBrain Global-BrainAGE Lifespan Model, was applied to N=138 participants (74 females, 64 males) from the Longitudinal Adolescent Brain Study. Participants completed 2-14 MRI scans between the ages of 12-17 years (752 datapoints). Model fit, prediction accuracy and longitudinal consistency were examined. Results showed moderate-to-good longitudinal consistency and reliability, consistent with high-performing cross-sectional age-to-brain-age correlations in youth cohorts. However, the model systematically overestimated brain-age changes relative to chronological changes, and prediction accuracy was unstable, with the mean absolute error increasing with age. Despite sex-specific brain-age calculations, on average, females showed older brain-ages compared with males. Further, younger adolescents were underpredicted, while older adolescents were overpredicted, indicating that standard model adjustments and assumptions may not be applicable.

Newborns recognise familiar language patterns experienced in utero and discriminate them from unfamiliar ones. It is as yet unclear which neural mechanisms are responsible for such early language-specific behavior. Here we focus on neural speech tracking and test whether it shows language-specific attunement in newborns and one-to-two month olds. Infants listened to infant-directed stories in their native language (Czech) and an unfamiliar language (Russian) while their EEG was recorded. First, we examined whether neural speech tracking differed between infants predominantly exposed to Czech and infants exposed primarily to other languages. Second, we assessed developmental changes by combining these data with a previously collected cohort of newborns, yielding a continuous sample spanning 1-62 days of age. Neural speech tracking was assessed in stimulus-derived delta and theta frequency bands in terms of oscillatory power and accuracy of EEG-to-speech envelope reconstruction using the backward multivariate temporal response functions. Czech-exposed infants had stronger cortical tracking of Czech speech than infants exposed to other languages. Within the Czech-exposed group, native Czech elicited stronger neural tracking than unfamiliar Russian, particularly in the delta band, indicating early language-specific tuning to the prosodic-word structure. Across the combined Czech-exposed sample, this native-language advantage gradually decreased with age, suggesting that neural speech tracking of the slow rhythms undergoes rapid reorganization during the first two months of life. These findings demonstrate that language-specific neural speech tracking is detectable from the earliest weeks of life and is jointly shaped by early, perinatal language experience as well as cognitive maturation.

Infants actively shape their experience through self-generated movement. They need to move their head efficiently to explore and interact with their environment and to hold their head still to sustain attention. Controlled laboratory studies have documented the importance of head movements in orienting and stabilizing infant visual attention, but little is known about how head control develops as infants go about daily life, the setting in which development actually unfolds. We analyzed 383 hours of egocentric video collected from 88 infants aged 3 weeks to 29 months using head-mounted cameras in infants homes. Using a visual-odometry algorithm, we quantified rotational magnitude, the size of head movements; and rotational efficiency, the directional coherence of head movements. Head-rotation magnitude increased across the first year, and rotational efficiency improved throughout development.

BackgroundPredicted brain-age derived from structural neuroimaging is being increasingly explored as a marker of brain maturation and biological age, with mental ill-health linked to advanced biological ageing in adults. Longitudinal evidence in adolescents remains limited, and the relationship between suicidality, psychological distress, wellbeing and brain-age gap (BrainAGE; predicted brain-age minus chronological age) is poorly understood. MethodsData were drawn from 135 adolescents (54.8% female; 12-16.9 years; n=688 observations) from the Longitudinal Adolescent Brain Study. Latent profile analysis (LPA) used person-level means and standard deviations of distress (K10), wellbeing (COMPAS-W) and suicidal ideation (SIDAS). BrainAGE was estimated using the CentileBrain Global-BrainAGE pipeline from FreeSurfer-derived morphometric features. Associations between cluster membership and BrainAGE were examined using linear regression and linear mixed-effects models, adjusted for chronological age and sex. ResultsThree profiles emerged: low distress (N=110; 50% female), moderate distress with greater suicidal ideation (N=14; 64% female) and moderate distress with lower suicidal ideation (N=11; 91% female). The moderate distress with lower suicidal ideation cluster showed significantly higher BrainAGE relative to the low distress cluster (B=1.87, SE=0.76, p=.015). Whereas, the moderate distress with greater suicidal ideation cluster did not differ to the low distress cluster. Chronological age was positively associated with BrainAGE (B=0.67, SE=0.07, p<.001). ConclusionsDistinct adolescent mental health profiles may be associated with BrainAGE, depending on the levels and stability of distress and suicidality. However, the longitudinal associations were less robust across small extensions of the developmental range studied, warranting some cautious interpretation and need for replication.

BackgroundEarly life adversity (ELA) is associated with notable negative consequences across development. Experiences of deprivation may affect neurocognitive development, while experiences of threat may alter emotion processing. Deprivation and threat may also differentially influence reward processing. However, unique consequences of deprivation and threat beyond low family resources are debated. MethodsWe employed an exposure vs. control data analytic approach to isolate deprivation and threat influences from socioeconomic resources. Adolescent Brain Cognitive Development (ABCD(R)) Study youth exposed to neither deprivation nor threat (N=2408-2962) were matched to youth exposed to deprivation-only (N=638-721), threat-only (N=198-232), or threat non-exclusively (threat+: N=382-464) based on family income, parental education, race/ethnicity, sex, and age. Multivariate analyses were used to distinguish each ELA group from their respective control groups in the neurocognitive domain (resting-state connectomic maturation, cognitive task performance, and cortical grey matter thickness at two timepoints) and in the neuroaffective domain (nucleus accumbens and caudate activation to reward anticipation and amygdala and insula activation to fearful faces). ResultsIn the neurocognitive domain, similar latent variables (LVs) differentiated the deprivation and threat+ groups from their respective matched control groups. This LV corresponded to neurocognitive maturation, loading positively on cortical functional maturation and task performance, and negatively on cortical grey matter thickness. This LV was weaker in the deprivation and threat+ groups compared to controls. In the neuroaffective domain, no significant LVs were found. ConclusionBoth threat and deprivation exposure during childhood may delay neurocognitive development in early adolescence beyond their co-occurrence with low socioeconomic resources.

In the context of education, attention can be considered the gateway for learning, yet it remains unclear which neural mechanisms of attention identified under controlled laboratory conditions are most relevant when children engage in meaningful learning. Here, we addressed this question by experimentally manipulating attention while 5th- and 6th-grade students learned novel educational content from their own teacher. Working in partnership with an experienced classroom teacher, we co-developed naturalistic auditory and visual learning streams and manipulated whether students prioritized or ignored the speech. Using school-based electroencephalography and temporal response function modeling, we examined whether attention modulated early sensory or later stages of cortical speech processing. Attention selectively modulated speech processing at approximately 170 ms, with no evidence for modulation at earlier sensory stages, supporting a predominant role for late-stage attentional selection during learning. Importantly, individual differences in attentional modulation were associated with learning: students who more strongly increased neural tracking of the speech when it was task-relevant learned more effectively from spoken instruction. The same late-stage neural mechanism also distinguished students whom their teacher independently identified as stronger attenders during everyday classroom learning. Together, these findings connect late-stage attentional modulation across experimental neural dynamics, individual learning outcomes, and teacher observations of classroom behavior. More broadly, they demonstrate how studying attention within educationally meaningful contexts can help identify which neural mechanisms are most consequential for successful learning.