Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

Hippocampal subregion volumes and preadolescent depression risk in the ABCD sample

The hippocampus is central in the pathophysiology of depression. Subregions of the hippocampus (head, body, tail) have been implicated in adult depression, though research examining depression and hippocampal subregions in youth has been limited. This study aimed to examine associations between preadolescent hippocampal subregions and depression risk as well as their interactions with factors associated with depression risk, including biological sex and socioeconomic status (SES). Hippocampal subregions were extracted from the Adolescent Brain and Cognitive Development Study baseline sample (N = 10,469, ages 9-10 years). Depression risk factors included maternal lifetime depression, child depressive symptoms, and child internalizing and externalizing symptoms. Maternal depression was measured through the Family History Questionnaire, and child symptoms were measured through the Child Behavioral Checklist. Results identified associations between hippocampal volumes and future increases in internalizing symptoms (N = 9738). Further, associations between hippocampal subregions and depression risk were moderated by biological sex and SES: males, but not females, with maternal depression exhibited lower hippocampal tail volumes (N = 9826), and for preadolescents with low, but not high, SES, greater hippocampal head volumes predicted increased internalizing symptoms at baseline (N = 10,294) and at the 24-month follow up (N = 7069-7086). Together, this study demonstrates the importance of hippocampal subregions within preadolescent depression risk and identifies subgroups, including preadolescent males and those with low SES, that may be at particular risk.

An interaction-centric approach for quantifying eye-to-eye reciprocal interaction

This study presents an interaction-centric framework for analytically investigating brain-to-brain dynamics during eye contact, advancing beyond the traditional spectator model. The foundation of the interactor approach is to delineate the interaction. To achieve this, simultaneous brain activity engaged in eye contact was captured using hyperscanning fMRI. The BOLD responses were first divided into eye-to-eye reciprocal interaction and eye-to-face non-reciprocal communication based on the experimental design; then the reciprocal interaction response was further differentiated into sensory-based (exogenous) and mind-based (endogenous) components to characterize agentic interaction. The proposed interactor approach not only determines interaction from dyadic brain states but also computes emergent interactive brain states arising from the interaction. To achieve these, reciprocal interactive fMRI responses were quantified into an interaction matrix, from which interaction-induced communication channels were identified using Correspondence Analysis, and information flow within those channels was measured with Mutual Information. The advantage of the interactor approach is its ability to reveal emergent dyadic brain states that a spectator approach cannot fully unravel. When applied to parent-child eye contact, this method confirmed existing developmental findings, clarified previous inconsistencies, and uncovered new insights into how reciprocal social engagement shapes brain function.

Negative life events during early adolescence are associated with neural deactivation to emotional stimuli

Negative life events (NLEs) have been shown to perturb neurodevelopment and are correlated with poor mental health outcomes in adolescence, the most common period of psychopathology onset. Emotion regulation is a critical component of psychological response to NLEs and interacts, neurobiologically and behaviorally, with working memory. This study leveraged an emotional n-back task to examine how NLEs influence emotion- and working memory-related brain activation using data from 2150 youth in the Adolescent Brain Cognitive Development (ABCD) Study. Greater incidence of NLEs was associated with less activation in the amygdala and more pronounced deactivation in other limbic and frontal brain regions previously implicated in emotion-related cognition; however, this association was present only during emotion processing conditions of the task. While NLEs were not significantly associated with task performance in the final sample, behavioural analyses including youth excluded for low task accuracy and poor neuroimaging data quality showed a significant negative association between NLEs and overall task performance. While behavioural findings across the entire sample support prior work, somewhat incongruent with prior literature, imaging results may suggest that during early adolescence the effects of negative experiences on patterns of neural activation are specific to contexts necessitating emotion processing.

Session interest model for CTR prediction based on feature co-action network

The main purpose of click-prediction models is to predict the probability of customers clicking on products and provide support for advertising decisions of businesses. However, most previous models often use deep neural networks to capture implicit interaction and can not fully retain the representational power of the original feature interactions. At the same time, one factor that most models ignore is that sequence is made up of sessions. Therefore, how to model user interest features and preserve the representational properties of feature interactions is the main challenge to improve the accuracy of CTR prediction. According to above issues, this study propose session interest model with feature co-action network (SIFAN). First, we used widely used characteristic co-action network module to tap into the interactions in customer single behavior. Then, the sequential behavior of customers is divided into session layers, and considering that various session interests may follow sequential patterns, gated recursive units are applied to predict customer clicks. Then, by analyzing the GRU with attention update gates, the correlation between conversation interest and target items is determined. According to relevant experimental results, under the same experimental conditions, the SIFAN model has significant performance advantages compared to other models.

Investigating omega-3 fatty acids' neuroprotective effects in repetitive subconcussive neural injury: Study protocol for a randomized placebo-controlled trial

Soccer (football) is the most popular sport globally, with 265 million players across all ages and sexes. Repetitive subconcussive head impacts due to heading of the soccer ball can pose threats to healthy brain development and aging. Omega-3 fatty acids, especially docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), may have neuroprotective effects, but it remains unclear what aspects of neural health benefit from DHA+EPA when faced with subconcussive head impacts. In a randomized placebo-controlled trial, 208 soccer players will complete baseline measures including demographics, blood sampling, dietary recalls, and psychological assessment. Participants will be randomly assigned to ingest DHA+EPA [3.4g/d: DHA 2.4g+EPA 1.0g] or placebo daily for 8 weeks followed by a subconcussion intervention phase. During the subconcussion intervention, participants will perform a session of 20 controlled soccer headings, with a second session 24 hours later. Blood samples, neuroimaging data, autonomic reactivity, and clinical measures (symptoms, oculomotor, cognition) will be collected pre-heading and 24-hour post-1st session, 24-hour post-2nd session, and 7-day post-2nd session. The primary hypothesis is that DHA+EPA pretreatment will promote neuronal and astrocyte resiliency to subconcussive head impacts, as assessed by blood biomarkers of brain injury, axonal microstructure measured by diffusion tensor imaging, and whole-brain resting-state connectivity. It is proposed that pretreatment will preserve autonomic function, as assessed by the cold pressor test (CPT), as well as oculomotor and cognitive function, even after head impacts. Data from this trial will help clarify the combined effect of DHA+EPA on brain molecular, cellular, and physiological health in response to subconcussive head impacts. If the hypotheses are confirmed, the findings will support a highly practical intervention for mitigating the neurodegenerative cascade triggered by head impacts. Trial registration: ClinicalTrials.gov NCT06736925.

Sources and components of fine air pollution exposure and brain morphology in preadolescents

Air pollution is an emerging novel neurotoxicant during childhood and adolescence. However, little is known regarding how fine particulate matter (PM2.5) components and its sources impact brain morphology. We investigated air pollution exposure-related differences in brain morphology using cross-sectional magnetic resonance imaging data from 10,095 children ages 9-11 years-old enrolled in the United States' Adolescent Brain Cognitive Development Study [2016-2018]. Air pollution estimates included fifteen PM2.5 constituent chemicals and metals, and six major sources of PM2.5 (e.g., crustal materials, biomass burning, traffic) identified from prior source apportionment, as well as nitrogen dioxide (NO2) and ozone (O3). After adjusting for demographic, socioeconomic, and neuroimaging covariates, we used partial least squares analyses to identify associations between simultaneous co-exposures and morphological differences in cortical thickness, surface area, and subcortical volumes. We found that greater exposure to PM2.5 and NO2 was associated with decreases in frontal and increases in inferior temporal surface area. PM2.5 component and source analyses linked cortical surface area and thickness to biomass burning (e.g., organic carbon, potassium), crustal material (e.g., calcium, silicon), and traffic (e.g., copper, iron) exposures, while smaller subcortical volumes were linked to greater potassium exposure. This is the first study to show differential effects of several air pollution sources on development of children's brains. Significant associations were found in brain structures involved in several cognitive and social processes, including lower- and higher-order sensory processing, socioemotional behaviors, and executive functioning. These findings highlight differential effects of several air pollution sources on brain structure in preadolescents across the U.S.

Characterizing the Effects of Age, Puberty, and Sex on Variability in Resting-State Functional Connectivity in Late Childhood and Early Adolescence

Understanding the relative influences of age, pubertal development, and sex assigned at birth on brain development is a key priority of developmental neuroscience given the complex interplay of these factors in the onset of psychopathology. Previous research has investigated how these factors relate to static (time-averaged) functional connectivity (FC), but little is known about their relationship with dynamic (time-varying) FC. The present study aimed to investigate the unique and overlapping roles of these factors on dynamic FC in children aged approximately 9 to 14 in the ABCD Study using a sample of 5,122 low-motion resting-state scans (from 4,136 unique participants). Time-varying correlations in the frontolimbic, default mode, and dorsal and ventral corticostriatal networks, estimated using the Dynamic Conditional Correlations (DCC) method, were used to calculate variability of within- and between-network connectivity and of graph theoretical measures of segregation and integration. We found decreased variability in global efficiency across the age range, and increased variability within the frontolimbic network driven primarily by those assigned female at birth (AFAB). AFAB youth specifically also showed increased variability in several other networks. Controlling for age, both advanced pubertal development and being AFAB were associated with decreased variability in all within- and between-network correlations and increased variability in measures of network segregation. These results potentially suggest advanced brain maturation in AFAB youth, particularly in key networks related to psychopathology, and lay the foundation for future investigations of dynamic FC.

Machine learning-derived multimodal Neurobiological profiles of behavioral activation traits in adolescents

Behavioral activation (BA) traits mediate responses to positive reinforcement, and then to promote reward-seeking actions. However, few studies have investigated the neurobiological profiles of BA traits in adolescents based on multimodal neuroimaging and machine learning techniques. In this study, a total of 6626 adolescents with both valid multimodal magnetic resonance imaging (MRI) and questionnaire data were included in the Adolescent Brain Cognitive Development Study. Machine learning-based elastic net regression with 5-fold cross-validation (CV) was used to characterize the neurobiological profiles of BA traits using multimodal MRI data as predictors. Using 5-fold CV, the multi-region neurobiological profiles substantively predicted BA traits, and this finding was robust in an out-of-sample. Regarding specific regions, neurobiological profiles were enriched in the bilateral pallidum. Regarding functional networks, functional connectivity of the cingulo-opercular and the fronto-parietal networks with both the pallidum and nucleus accumbens, showed high beta weights. The relationships of the neurobiological profiles with BA traits were further supported by traditional univariate linear mixed effects models, in which many of the profiles identified as part of the neurobiological pattern showed significant univariate associations with BA traits, including the hub region pallidum. In summary, these findings revealed robust machine learning-derived neurobiological profiles of BA traits, those that comprised a key node the pallidum, which is involved in the motivational brain network. These findings suggested that the pallidum might play a vital role in developing BA traits in adolescents.

Neural correlates of device-based sleep characteristics in adolescents

Understanding the brain mechanisms underlying adolescent sleep patterns and their impact on psychophysiological development is complex. We applied sparse canonical correlation analysis (sCCA) to data from 3,222 adolescents in the Adolescent Brain Cognitive Development (ABCD) study, integrating sleep characteristics with multimodal imaging. This reveals two key sleep-brain dimensions: one linking later sleep onset and shorter duration to decreased subcortical-cortical connectivity and another associating a higher heart rate and shorter light sleep with lower brain volumes and connectivity. Hierarchical clustering identifies three biotypes: biotype 1 has delayed, shorter sleep with a higher heart rate; biotype 3 has earlier, longer sleep with a lower heart rate; and biotype 2 is intermediate. These biotypes also differ in cognitive performance and brain structure and function. Longitudinal analysis confirms these differences from ages 9 to 14, with biotype 3 showing consistent cognitive advantages. Our findings offer insights into optimizing sleep routines for better cognitive development.

Whole-brain white matter variation across childhood environments

White matter develops over the course of childhood in an experience-dependent manner. However, its role in the relationship between the early environment and later cognition is unclear, in part due to focus on changes in specific gray matter regions. This study examines white matter differences across adolescents from diverse environments, evaluating both their extent throughout the brain and their contribution to cognitive outcomes. Using data from the Adolescent Brain Cognitive Development (ABCD) study (N = 9,082, female = 4,327), we found extensive cross-sectional associations with lower white matter fractional anisotropy (FA) and streamline count in the brains of 9- and 10-y-old children exposed to a range of experiences, including prenatal risk factors, interpersonal adversity, household economic deprivation, and neighborhood adversity. Lower values of FA were associated with later difficulties with mental arithmetic and receptive language. Furthermore, white matter FA partially mediated the detrimental relationship between adversity and cognition later in adolescence. These findings advance a white matter-based account of the neural and cognitive effects of adversity, which supports leading developmental theories that place interregional connectivity prior to gray matter maturation.

A Phenome-Wide association study (PheWAS) of genetic risk for C-reactive protein in children of European Ancestry: Results from the ABCD study

BACKGROUND

C-reactive protein (CRP) is a moderately heritable marker of systemic inflammation that is associated with adverse physical and mental health outcomes. Identifying factors associated with genetic liability to elevated CRP in childhood may inform our understanding of variability in CRP that could be targeted to prevent and/or delay the onset of related health outcomes.

METHODS

We conducted a phenome-wide association study (PheWAS) of genetic risk for elevated CRP (i.e. CRP polygenic risk score [PRS]) among children genetically similar to European ancestry reference populations (median analytic n = 5,509, range = 120-5,556) from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) Study baseline assessment. Associations between CRP PRS and 2,377 psychosocial and neuroimaging phenotypes were estimated using independent mixed effects models nested by recruitment site (or scanner) and family, with ancestral genomic principal components (n = 10), age, and sex, as well as global brain metrics (when relevant) included as fixed effect covariates. Post hoc analyses examined whether: (1) covarying for measured body mass index (BMI) or removing the shared genetic architecture between CRP and BMI altered phenotypic associations, (2) sex moderated CRP PRS associations, and (3) associations were unconfounded by assortative mating or passive gene-environment correlations (using within-family analyses). Multiple testing was adjusted for using Bonferroni and false discovery rate (FDR) correction.

RESULTS

Nine phenotypes were positively associated with CRP PRS after multiple testing correction: five weight- and eating-related phenotypes (e.g. BMI, overeating), three phenotypes related to caregiver somatic problems (e.g. caregiver somatic complaints), as well as weekday video watching (all ps = 1.2 x 10-7 - 2.5 x 10-4, all pFDRs = 0.0002-0.05). No neuroimaging phenotypes were associated with CRP PRS (all ps = 0.0003-0.998; all pFDRs = 0.08-0.998) after correction for multiple testing. Eating and weight-related phenotypes remained associated with CRP PRS in within-family analyses. Covarying for BMI resulted in largely consistent results, and sex did not moderate any CRP PRS associations. Removing the shared genetic variance between CRP and BMI attenuated all relationships; associations with weekday video watching, caregiver somatic problems and caregiver report that the child is overweight remained significant while associations with waist circumference, weight, and caregiver report that child overeats did not.

DISCUSSION

Genetic liability to elevated CRP is associated with higher weight, eating, and weekday video watching during childhood as well as caregiver somatic problems. These associations were consistent with direct genetic effects (i.e., not solely due to confounding factors like passive gene-environment correlations) and were independent of measured BMI. The majority of associations with weight and eating phenotypes were attributable to shared genetic architecture between BMI and inflammation. The relationship between genetics and heightened inflammation in later life may be partially attributable to modifiable behaviors (e.g. weight and activity levels) that are expressed as early as childhood.

Longitudinal associations between greenspace exposure, structural brain development, and mental health and academic performance during early adolescence

BACKGROUND

Greenspace exposure is associated with positive mental health and academic outcomes. This preregistered longitudinal study examines whether the influence of greenspace exposure on structural brain development partially explains these associations.

METHODS

We analyzed data from the Adolescent Brain Cognitive Development (ABCD) study (N=7102), to test the relationship between greenspace exposure at age 9-10 and brain structure two years later, as well as change over time. Additionally, we tested whether brain structural development statistically mediated the associations of greenspace exposure with mental health and academic performance.

RESULTS

Greenspace exposure was associated with greater total surface area (SA) and cortical volume (CV), greater cortical thickness (CT) in temporal regions and the insula, lower thickness in the caudal middle frontal and superior frontal gyri, greater SA across several regions, and greater volume of the caudate nucleus, putamen, and nucleus accumbens. In analyses studying change in brain structure over time, higher greenspace exposure was associated with greater growth of total SA, lower average thickness reduction, and reduced total CV growth as well as changes at the regional level. We also found significant indirect effects of the association of greenspace exposure with academic performance and mental health through both total and regional cortical structure.

CONCLUSIONS

Greenspace exposure is linked to structural neurodevelopment, which is, in turn, associated with better mental health and academic achievement. Our findings underscore the importance of greenspace in supporting brain development and positive outcomes in children and adolescents.

Examining the unique contribution of parent anxiety sensitivity on adolescent neural responses during an emotion regulation task

Parent factors impact adolescent's emotion regulation, which has key implications for the development of internalizing psychopathology. A key transdiagnostic factor which may contribute to the development of youth internalizing pathology is parent anxiety sensitivity (fear of anxiety-related physiological sensations). In a sample of 146 adolescents (M/SDage = 12.08/.90 years old) and their parents (98% mothers) we tested whether parent anxiety sensitivity was related to their adolescent's brain activation, over and above the child's anxiety sensitivity. Adolescents completed an emotion regulation task in the scanner that required them to either regulate vs. react to negative vs. neutral stimuli. Parent anxiety sensitivity was associated with adolescent neural responses in bilateral orbitofrontal cortex (OFC), anterior cingulate, and paracingulate, and left dorsolateral prefrontal cortex, such that higher parent anxiety sensitivity was associated with greater activation when adolescents were allowed to embrace their emotional reaction(s) to stimuli. In the right OFC region only, higher parent anxiety sensitivity was also associated with decreased activation when adolescents were asked to regulate their emotional responses. The findings are consistent with the idea that at-risk adolescents may be modeling the heightened attention and responsivity to environmental stimuli that they observe in their parents.

Protocol to analyze deep-learning-predicted functional scores for noncoding de novo variants and their correlation with complex brain traits

Functional impact of noncoding variants can be predicted using computational approaches. Although predictive scores can be insightful, implementing the scores for a custom variant set and associating scores with complex traits require multiple phases of analysis. Here, we present a protocol for prioritizing variants by generating deep-learning-predicted functional scores and relating them with brain traits. We describe steps for score prediction, statistical comparison, phenotype correlation, and functional enrichment analysis. This protocol can be generalized to different models and phenotypes. For complete details on the use and execution of this protocol, please refer to Mondragon-Estrada et al.1.

A cross-sectional multicentre study of multishell diffusion MRI in multiple sclerosis

BACKGROUND AND OBJECTIVES

White matter (WM) microstructural properties from advanced multishell diffusion MRI (dMRI) have been linked to clinical disability in multiple sclerosis (MS). This multicentre study used multishell dMRI to compute WM metrics and test for differences between people with MS (pwMS) and healthy controls (HCs).

METHODS

We included multishell dMRI data from 251 pwMS or clinically isolated syndrome (CIS) (mean age 40.7 years, 72.4 % women, 88.8 % relapsing remitting MS) at six MAGNIMS centres and 543 HCs. Eleven scalar metric maps were estimated from multishell dMRI sequences, based on diffusion tensor imaging (DTI) and restriction spectrum imaging (RSI). The maps were analysed using tract-based spatial statistics (TBSS). The diffusion output was submitted to paired sampled t-tests to test for case-control differences and linear regression models to test for associations with Expanded Disability Status Scale (EDSS) scores, while accounting for confounders. In a sub-sample from Oslo, we tested for correlations between EDSS and dMRI metrics within WM lesions.

RESULTS

Significant group differences were found in nine out of eleven dMRI metrics. Linear regression models revealed significant correlations between EDSS and fractional anisotropy (FA) fast (β=-4.54, p = 0.01) and apparent diffusion coefficient (ADC) fast (β=10.92, p = 8.7 × 10-3).

CONCLUSIONS

Diffusion MRI based on clinically feasible multishell sequences uncovers WM group differences between pwMS and HCs, but only a selection of the advanced multishell parameters were sensitive to disability, and no statistically significant correlations with disability remained after Bonferroni correction.

Sex, Neural Networks, and Behavioral Symptoms Among Adolescents With Multisite Pain

Importance

Multisite pain disproportionately affects females starting in adolescence and is associated with central nervous system dysregulation. Understanding the heterogeneity of underlying neural networks and behavioral symptoms is essential.

Objective

To characterize sex-related resting-state neural networks and co-occurring symptoms, including sleep and behavioral problems, in youth with multisite pain.

Design, Setting, and Participants

This cross-sectional analysis leverages the 2-year follow-up data from the Adolescent Brain and Cognitive Development Study. A total of 684 youth aged 11 to 12 years with multisite pain were compared with 1368 youth with no pain or with regional pain, matched by pubertal status, handedness, and race and ethnicity. Data were collected from July 2018 to February 2021 and released October 2021. Data were analyzed from June 2023 to July 2024.

Exposure

Youth-reported number of painful regions during the last month classified into multisite (≥3), regional (1-2), and no pain groups.

Main Outcomes and Measures

Sex-stratified group iterative multiple model estimation was used for sparse network estimation of regions from the salience network (SLN), sensorimotor network (SMN), and default mode network (DMN). Individual within-network and between-network densities were calculated. Symptoms were behavioral problems and sleep disturbances. Sex-stratified differences in network densities and symptoms were examined between groups. Associations between brain networks and co-occurring symptoms were explored.

Results

Of 2052 participants (1044 [50.88%] female), mean (SD) pubertal status was 2.23 (0.65) and mean (SD) age was 12.02 (0.66) years; 25 (1.22%) were Asian, 149 (7.26%) were Black, 361 (17.59%) were Hispanic, 1307 (63.69%) were White, and 210 (10.23%) were other race or ethnicity. A total of 1646 participants (80.21%) were right-handed, 100 (4.87%) were left-handed, and 306 (14.91%) were ambidextrous. Multisite pain was associated with lower within-SMN connectivity in male (F2,1005 = 61.40; η2 = 0.11; false discovery rate [FDR] P < .001) and female (F2,1041 = 13.38; η2 = 0.03; FDR P < .001) participants and was associated with greater behavioral problems in male (F2,918 = 28.12; η2 = 0.04; FDR P < .001) and female (F2,945 = 9.12; η2 = 0.02; FDR P < .001) participants compared with the subgroup with no pain. Male participants with multisite pain had heightened DMN-SMN connectivity (F2,1005 = 3.55; η2 = 0.007; FDR P = .04). Female participants with multisite pain had heightened sleep disturbances (F2,1039 = 10.64; η2 = 0.02; FDR P = .002), partially explained by reduced within-SMN connectivity (indirect effect estimate, 0.15; 95% CI, 0.03-0.34).

Conclusions and Relevance

In this cross-sectional study of 2052 adolescents, sex-related neurophysiological mechanisms were associated with multisite pain. Brain connectivity partially explained the sleep-pain association in female participants only. On replication and evidence of persistence, these findings suggest that female adolescents with pain may especially benefit from interventions targeting sleep disturbances.

Measuring the associations between brain morphometry and polygenic risk scores for substance use disorders in drug-naive adolescents

Substance use has been associated with differences in adult brain morphology; however, it is unclear whether these differences precede or are a result of substance use substance use. We investigated the impact of polygenic risk scores (PRSs) for cannabis use disorder (CUD) and general substance use and substance use disorder liability (SU/SUD) on brain morphology in drug-naïve adolescents. Baseline data were used from 1,874 European-descent participants (ages 9-11) comprising 222, 328 and 387 pairs of MZ twins, DZ twins, and Non-Twin Siblings, respectively, in the Adolescent Brain Cognitive Development Study. We fitted multivariate twin models to estimate the putative effects of CUD, SU/SUD, and brain region-specific PRSs. These models assessed their influence on six subcortical and two cortical phenotypes. PRS for CUD and SU/SUD were created based on GWAS conducted by Johnson et al. (2020) and Hatoum et al. (2023), respectively. When decomposing variance in each brain region of interest (ROI), we used the corresponding ROI-specific PRS. Brain morphometry in drug-naive subjects was unrelated to CUD PRS. The variance explained in each ROI by its corresponding PRS ranged from 0.8-4.4%. The SU/SUD PRS showed marginally significant effects (0.2-0.4%) on cortical surface area and nucleus accumbens volume, but overall effect sizes were small. Our findings indicate that differences in brain morphometry among baseline drug-naive individuals are not associated with the genetic risk for CUD but show a weak association with general addiction and substance use risk (SU/SUD), particularly in nucleus accumbens volume and total cortical surface area.

Delay discounting and nucleus accumbens functional connectivity are related to weight status in adolescents from the ABCD study

BACKGROUND

Despite the growing epidemic of paediatric obesity, questions remain regarding potential neural mechanisms for individual risk. Delay discounting is a cognitive process of comparison of valuation between immediate and delayed reward, which has been inconsistently linked to weight status. Moreover, central to the brain's reward system is the nucleus accumbens, a region structurally and functionally altered in obesity.

OBJECTIVES/METHODS

This study aimed to examine the relationships between two continuous metrics of weight status, performance on a monetary delay-discounting task and nucleus accumbens functional connectivity in 10-12-year-olds from the Adolescent Brain and Cognitive Development (ABCD) Study.

RESULTS

Using multilevel longitudinal linear modelling, we found greater discounting was associated with higher BMI Z-scores (BMIz) and waist-to-height ratio Z-scores (WHtRz) (N = 3819). Moreover, we observed functional connectivity of the nucleus accumbens to the cingulo-opercular, dorsal attention, fronto-parietal, salience and ventral attention networks were predictive of BMIz (N = 1817). Nucleus accumbens functional connectivity was not found to mediate the association between delay-discounting behaviour and BMIz.

CONCLUSIONS

Delay discounting and nucleus accumbens functional connectivity are independently related to weight status in a large sample of early adolescents. A better understanding of the relationship between reward and overeating behaviours may better inform obesity interventions.

Gestational Age and Cognitive Development in Childhood

Importance

Preterm and early-term births are known risk factors for cognitive impairment, but studies that comprehensively include genetics, prenatal risk, and child-specific factors in high-risk populations are lacking.

Objective

To investigate the long-term cognitive outcomes of children born at various gestational ages, including very preterm (28-31 weeks), moderately preterm (32-33 weeks), late preterm (34-36 weeks), and early term (37-38 weeks), compared with full-term (≥39 weeks), accounting for genetics and other risk factors.

Design, Setting, and Participants

In this prospective, multicenter, longitudinal cross-sectional study, children aged 9 to 10 years were recruited from the Adolescent Brain and Cognitive Development Study between January 1, 2016, and December 31, 2018. Children underwent cognitive assessments using the National Institutes of Health Toolbox, Little Man Task, and Rey Auditory Verbal Learning Test. Polygenic scores for cognitive performance (cogPGS) were generated using results of a genome-wide association study from the genetic variants related to cognitive performance, educational attainment, and mathematical ability. Data analysis was performed from March to June 2024.

Exposure

Preterm (very preterm, moderately preterm, late preterm) and early-term birth status, with full-term birth status as the reference group.

Main Outcomes and Measures

The primary outcome of interest was the composite cognitive score, while secondary outcomes included individual cognitive domain scores. Hierarchical regression models were used to examine associations between gestational age and cognitive outcomes, adjusting for socioeconomic status (SES), cogPGS, prenatal risks, and child-specific factors.

Results

Among 5946 children included in the study (mean [SD] age, 9.9 [0.6] years; 3083 [51.8%] male), 55 (0.9%) were born very preterm, 110 (1.8%) were born moderately preterm, 454 (7.6%) were born late preterm, 261 (4.4%) were born early term, and 5066 (85.2%) were born full term. The cogPGS was positively associated with the composite cognitive score (β = 0.14; 95% CI, 0.12-0.17; P < .001) in the overall cohort. Compared with full-term children, those born moderately preterm had lower composite cognitive scores (β = -0.39; 95% CI, -0.55 to -0.22; P < .001) and lower scores in vocabulary (β = -0.36; 95% CI, -0.53 to -0.19; P < .001), working memory (β = -0.27; 95% CI, -0.45 to -0.09; P = .003), episodic memory (β = -0.32; 95% CI, -0.50 to -0.14; P < .001), and both short-delay recall (β = -0.36; 95% CI, -0.54 to -0.18; P < .001) and long-delay recall (β = -0.29; 95% CI, -0.48 to -0.11; P = .002). These associations were independent of SES, cogPGS, and other risk factors. Importantly, the lowest cognitive scores appeared among children born at 32 weeks or less. In contrast, late-preterm and early-term children performed similarly to full-term peers.

Conclusions and Relevance

In this cross-sectional study of children aged 9 to 10 years, moderately preterm birth was associated with long-term cognitive problems independent of SES, genetics, and other risk factors. These findings underscore the need for continued follow-up of all preterm children, with particular focus on those born before 34 weeks' gestational age, because they may face greater developmental challenges over time.

Reduced recruitment of inhibitory control regions in very young children with ADHD during a modified Kiddie Continuous Performance Task: A fMRI study

Attention-Deficit/Hyperactivity Disorder (ADHD) symptom profiles are known to undergo changes throughout development, rendering the neurobiological assessment of ADHD challenging across different developmental stages. Particularly in young children (ages 4- to 7-years), measuring inhibitory control network activity in the brain has been a formidable task due to the lack of child-friendly functional Magnetic Resonance Imaging (fMRI) paradigms. This study aims to address these difficulties by focusing on measuring inhibitory control in very young children within the MRI environment. A total of 56 children diagnosed with ADHD and 78 typically developing (TD) 4-7-year-old children were successfully examined using a modified version of the Kiddie-Continuous Performance Test (K-CPT) during BOLD fMRI to assess inhibitory control. We also evaluated their performance on the standardized K-CPT outside the MRI scanner. Our findings suggest that the modified K-CPT effectively elicited robust and expected brain activity related to inhibitory control in both groups who were successfully scanned. Comparisons between the two groups revealed differences in brain activity, primarily observed in inferior frontal gyrus, anterior insula, dorsal striatum, medial pre-supplementary motor area (pre-SMA), and cingulate cortex (p < .005, corrected). Notably, for both groups increased activity in the right anterior insula was associated with improved response time (RT) and reduced RT variability on the K-CPT administered outside the MRI environment, although this did not survive statistical correction for multiple comparisons. The study also revealed continuing challenges for scanning this population-an additional 51 TD children and 78 children with ADHD were scanned, but failed to provide useable data due to movement. In summary, for a subsample of children, we successfully overcame some of the challenges of measuring inhibitory control in very young children within the MRI environment by using a modified K-CPT during BOLD fMRI, but further challenges remain for scanning in this population. The findings shed light on the neurobiological correlates of inhibitory control in ADHD and TD children, provide valuable insights for understanding ADHD across development, and potentially inform ADHD diagnosis and intervention strategies. The research also highlights remaining challenges with task fMRI in very young clinical samples.

Neural and Behavioral Correlates of Binge Eating in 9- to 10-Year-Old Children

OBJECTIVE

This observational study compared children with and without binge eating (BE) on biobehavioral measures of reward responsiveness, inhibitory control, and emotion processes, while accounting for the impact of weight.

METHOD

Children aged 9 to 10 years completed the baseline wave of the Adolescent Brain Cognitive Development Study (316 with BE; 7,681 without BE [no-BE]). The prevalence of binge-eating disorder in the BE group was 17.0%; clinically significant internalizing and externalizing symptoms were endorsed by 8.5% and 4.5% of the sample, respectively. The monetary incentive delay (MID) task, stop signal task (SST), and emotional N-Back (EN-Back) task were administered during neuroimaging. Analyses assessed effects of group (BE vs no-BE) on task performance and corresponding neural signal in regions of interest (ROIs). Weight status was evaluated as a covariate and as a moderator of effects.

RESULTS

Adjusting for weight status, the BE group (vs no-BE) group showed lower activation during anticipation of reward, specifically large reward (vs no reward), in the composite ROI consisting of the dorsal striatum, nucleus accumbens, orbital frontal gyrus, amygdala, and insula. Groups did not differ significantly in other behavioral or neural outcomes. No interactions between group and weight status were observed.

CONCLUSION

Blunted anticipatory responses to monetary reward were associated with binge eating during peri-adolescence and may play a role in binge eating pathophysiology. Results challenge prior findings in BE that may be confounded by weight, and highlight the importance of future prospective research across binge-eating disorder stage of illness.

PLAIN LANGUAGE SUMMARY

Binge eating disorder, the most common eating disorder, is associated with several negative psychosocial consequences. This study used data from the Adolescent Brain Cognitive Development (ABCD) Study and compared children (ages 9-10) with and without binge eating on neurobiological and behavioral measures of reward responsiveness, inhibitory control, and emotion processes. Children with binge eating showed lower neural activation during anticipation of reward, specifically large reward, compared to youth without binge eating. These findings suggest that blunted anticipatory response during peri-adolescence may play a role in binge eating pathophysiology.

Bayesian Longitudinal Network Regression With Application to Brain Connectome Genetics

The increasing availability of large-scale brain imaging genetics studies enables more comprehensive exploration of the genetic underpinnings of brain functional organizations. However, fundamental analytical challenges arise when considering the complex network topology of brain functional connectivity, influenced by genetic contributions and sample relatedness, particularly in longitudinal studies. In this paper, we propose a novel method named Bayesian Longitudinal Network-Variant Regression (BLNR), which models the association between genetic variants and longitudinal brain functional connectivity. BLNR fills the gap in existing longitudinal genome-wide association studies that primarily focus on univariate or multivariate phenotypes. Our approach jointly models the biological architecture of brain functional connectivity and the associated genetic mixed-effect components within a Bayesian framework. By employing plausible prior settings and posterior inference, BLNR enables the identification of significant genetic signals and their associated brain sub-network components, providing robust inference. We demonstrate the superiority of our model through extensive simulations and apply it to the Adolescent Brain Cognitive Development (ABCD) study. This application highlights BLNR's ability to estimate the genetic effects on changes in brain network configurations during neurodevelopment, demonstrating its potential to extend to other similar problems involving sample relatedness and network-variate outcomes.

Risk Assessment of Maladaptive Behaviors in Adolescents: Nutrition, Screen Time, Prenatal Exposure, Childhood Adversities - Adolescent Brain Cognitive Development Study

PURPOSE

We aimed to identify significant contributing factors to the risk of maladaptive behaviors, such as alcohol use disorder or obesity, in children. To achieve this, we utilized the extensive adolescent brain cognitive development data set, which encompasses a wide range of environmental, social, and nutritional factors.

METHODS

We divided our sample into equal sets (test, validation; n = 3,415 each). On exploratory factor analysis, six factor domains were identified as most significant (fat/sugar intake, screen time, and prenatal alcohol exposure, parental aggressiveness, hyperactivity, family violence, parental education, and family income) and used to stratify the children into low- (n = 975), medium- (n = 967), high- (n = 977) risk groups. Regression models were used to analyze the relationship between identified risk groups, and differences in reward sensitivity, and behavioral problems at 2-year follow-up.

RESULTS

The functional magnetic resonance imaging analyses showed reduced activation in several brain regions during reward or loss anticipation in high/medium-risk (vs. low-risk) children on a monetary incentive delay task. High-risk children exhibited heightened middle frontal cortex activity when receiving large rewards. They also displayed increased impulsive and motivated reward-seeking behaviors, along with behavioral problems. These findings replicated in our validation set, and a negative correlation between middle frontal cortexthickness and impulsivity behavior was observed in high-risk children.

DISCUSSION

Our findings show altered reward function and increased impulsiveness in high-risk adolescents. This study has implications for early risk identification and the development of prevention strategies for maladaptive behaviors in children, particularly those at high risk.

TractCloud-FOV: Deep Learning-Based Robust Tractography Parcellation in Diffusion MRI With Incomplete Field of View

Tractography parcellation classifies streamlines reconstructed from diffusion MRI into anatomically defined fiber tracts for clinical and research applications. However, clinical scans often have incomplete fields of view (FOV) where brain regions are partially imaged, leading to partial, or truncated fiber tracts. To address this challenge, we introduce TractCloud-FOV, a deep learning framework that robustly parcellates tractography under conditions of incomplete FOV. We propose a novel training strategy, FOV-Cut Augmentation (FOV-CA), in which we synthetically cut tractograms to simulate a spectrum of real-world inferior FOV cutoff scenarios. This data augmentation approach enriches the training set with realistic truncated streamlines, enabling the model to achieve superior generalization. We evaluate the proposed TractCloud-FOV on both synthetically cut tractography and two real-life datasets with incomplete FOV. TractCloud-FOV significantly outperforms several state-of-the-art methods on all testing datasets in terms of streamline classification accuracy, generalization ability, tract anatomical depiction, and computational efficiency. Overall, TractCloud-FOV achieves efficient and consistent tractography parcellation in diffusion MRI with incomplete FOV.

Systematic bias in surface area asymmetry measurements from automatic cortical parcellations

Anatomical asymmetry is a hallmark of the human brain and may reflect hemispheric differences in its functional organization. Widely used software like FreeSurfer can automate neuroanatomical measurements and facilitate studies of hemispheric asymmetry. However, patterns of surface area lateralization measured using FreeSurfer are curiously consistent across diverse samples. Here, we demonstrate systematic biases in these measurements obtained from the default processing pipeline. We compared surface area asymmetry measured from reconstructions of original brains vs. the same scans after flipping their left-right orientation. The default pipeline returned implausible asymmetry patterns between the original and flipped brains: Many structures were always left- or right-lateralized. Notably, these biases occur prominently in key speech and language regions. In contrast, manual labeling and curvature-based parcellations of key structures both yielded the expected reversals of left/right lateralization in flipped brains. We determined that these biases result from discrepancies in how regional labels are defined in the left vs. right hemisphere in the default cortical parcellation atlases. These biases are carried into individual parcellations because the FreeSurfer parcellation algorithm prioritizes vertex correspondence to the template atlas relative to individual neuroanatomical variation. We further demonstrate several straightforward, bias-free approaches to measuring surface area asymmetry, including using symmetric registration templates and parcellation atlases, vertex-wise analyses, and within-subject curvature-based parcellations. These results highlight theoretical concerns about using only the default processing stream to make inferences about population-level brain asymmetry and underscore the need for validating bias-free neuroanatomical measurements, particularly when studying regions where structural lateralization may underlie functional lateralization.

Brain asymmetry and its association with inattention and heritability during neurodevelopment

The relationship between brain asymmetry and inattention, and their heritability is not well understood. Utilizing advanced neuroimaging, we examined brain asymmetry with data from the Adolescent Brain Cognitive Development (ABCD; n = 8943; 9-10 y) and the Human Connectome Project (HCP) cohorts (n = 1033; 5-100 y). Data-driven metrics from resting-state fMRI and morphometrics revealed reproducible and stable brain asymmetry patterns across the lifespan. In children, high levels of inattention were highly heritable (61%) and linked to reduced leftward asymmetry of functional connectivity in the dorsal posterior superior temporal sulcus (dpSTS), a region interconnected with a left-lateralized language network. However, reduced dpSTS asymmetry had low heritability (16%) and was associated with lower cognitive performance suggesting that non-genetic factors, such as those mediating cognitive performance, might underlie its association with dpSTS asymmetry. Interventions that enhance cognition might help optimize brain function and reduce inattention.

Resting-State Sensory-Motor Connectivity between Hand and Mouth as a Neural Marker of Socioeconomic Disadvantage, Psychosocial Stress, Cognitive Difficulties, Impulsivity, Depression, and Substance Use in Children

Background

The sensory-motor network is essential for integrating sensory input with motor function and higher-order cognition. Resting-state functional connectivity (rsFC) within this network undergoes significant developmental changes, and disruptions in these connections have been linked to behavioral and psychiatric outcomes. However, the relationship between sensory-motor connectivity, early-life adversity, and later health behaviors remains understudied.

Objective

This study examines the associations between rsFC within the sensory-motor network (mouth and hand regions) and key social, psychological, and behavioral factors, including baseline and past socioeconomic status (SES), trauma exposure, family conflict, impulsivity, major depressive disorder (MDD), and future substance use.

Methods

Data were drawn from the Adolescent Brain Cognitive Development (ABCD) Study, a national sample of U.S. children. Resting-state fMRI data were used to assess functional connectivity within the sensory-motor network. Bivariate analyses examined associations between rsFC in the sensory-motor mouth and hand regions and baseline SES, past SES, childhood trauma exposure, family conflict, impulsivity, and MDD. Longitudinal analyses assessed whether baseline rsFC predicted future substance use.

Results

Greater rsFC between the sensory-motor mouth and hand regions was significantly associated with lower SES, higher trauma exposure, and greater family conflict. Increased connectivity was also correlated with older age and more advanced puberty status. Higher rsFC between the sensory-motor mouth and hand regions was linked to greater impulsivity, lower cognitive function, an increased likelihood of MDD, and future marijuana use.

Conclusion

These findings suggest that sensory-motor connectivity is sensitive to socioeconomic and psychosocial stressors, with potential long-term implications for mental health and substance use risk. The results highlight the importance of early-life environmental factors in shaping neurodevelopmental trajectories and emphasize the need for targeted interventions to mitigate the effects of adversity on brain function and behavior. Future research should further explore the role of sensory-motor network alterations in behavioral health outcomes as a function of environmental stressors.

Genetics impact risk of Alzheimer's disease through mechanisms modulating structural brain morphology in late life

BACKGROUND

Alzheimer's disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively.

METHODS

We used bidirectional two-sample Mendelian randomisation to estimate the effects between genetic liability to AD and global and regional cortical thickness, estimated total intracranial volume, volume of subcortical structures and total white matter in 37 680 participants aged 8-81 years across 5 independent cohorts (Adolescent Brain Cognitive Development, Generation R, IMAGEN, Avon Longitudinal Study of Parents and Children and UK Biobank). We also examined the effects of global and regional cortical thickness and subcortical volumes from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium on AD risk in up to 37 741 participants.

RESULTS

Our findings show that AD risk alleles have an age-dependent effect on a range of cortical and subcortical brain measures that starts in mid-life, in non-clinical populations. Evidence for such effects across childhood and young adulthood is weak. Some of the identified structures are not typically implicated in AD, such as those in the striatum (eg, thalamus), with consistent effects from childhood to late adulthood. There was little evidence to suggest brain morphology alters AD risk.

CONCLUSIONS

Genetic liability to AD is likely to affect risk of AD primarily through mechanisms affecting indicators of brain morphology in later life, rather than structural brain reserve. Future studies with repeated measures are required for a better understanding and certainty of the mechanisms at play.

A generalized epilepsy network derived from brain abnormalities and deep brain stimulation

Idiopathic generalized epilepsy (IGE) is a brain network disease, but the location of this network and its relevance for treatment remain unclear. We combine the locations of brain abnormalities in IGE (131 coordinates from 21 studies) with the human connectome to identify an IGE network. We validate this network by showing alignment with structural brain abnormalities previously identified in IGE and brain areas activated by generalized epileptiform discharges in simultaneous electroencephalogram-functional magnetic resonance imaging. The topography of the IGE network aligns with brain networks involved in motor control and loss of consciousness consistent with generalized seizure semiology. To investigate therapeutic relevance, we analyze data from 21 patients with IGE treated with deep brain stimulation (DBS) for generalized seizures. Seizure frequency reduced a median 90% after DBS and stimulation sites intersect an IGE network peak in the centromedian nucleus of the thalamus. Together, this study helps unify prior findings in IGE and identify a brain network target that can be tested in clinical trials of brain stimulation to control generalized seizures.

Considerations When Accounting for Race and Ethnicity in Studies of Poverty and Neurodevelopment

OBJECTIVE

Poverty and systemic racism within rare intertwined. Children of marginalized racial and ethnic identities experience higher levels of poverty and adverse psychiatric outcomes. Thus, in models of poverty and neurodevelopment, race and ethnicity, as proxies for exposure to systemic disadvantage, are regularly considered confounders. Recently, however, some researchers have claimed that using race and ethnicity as confounders is statistically dubious, and potentially socially damaging. Instead, they argue for the use of variables measuring other social determinants of health (SDoH). We explore this approach herein.

METHOD

Data are from 7,836 children 10 years of age in the Adolescent Brain Cognitive Development Study (ABCD Study). We fit mixed regression models for the association of household poverty measures with psychiatric symptoms, magnetic resonance imaging (MRI)-derived cortical measures, and cognition with and without (1) race and ethnicity adjustment, (2) poverty-by-race and ethnicity interaction terms, and (3) alternative SDoH variables. Propensity-based weights were used to calibrate the sample to key US demographics.

RESULTS

For psychiatric and cognitive outcomes, poverty-outcome relationships differed across racial and ethnic groups (interaction of poverty by race and ethnicity, p < .05). For MRI-derived outcomes, adjusting for race and ethnicity changed the estimate of the impact of poverty. Alternative SDoH adjustment could not fully account for the impact of race and ethnicity on the associations explored.

CONCLUSION

Poverty and both race and ethnicity combine to influence neurodevelopment. Results suggest that the effects of poverty are generally inconsistent across race and ethnicity, which supports prior research demonstrating the nonequivalence of SDoH indicators by race and ethnicity. Studies exploring these relationships should assess the interaction between poverty and race and ethnicity and/or should stratify when appropriate. Replacing race and ethnicity with alternative SDoH may induce bias.

Amygdala subregion volumes and apportionment in preadolescents - Associations with age, sex, and body mass index

The amygdala, a key limbic structure, is critical to emotional, social, and appetitive behaviors that develop throughout adolescence. Composed of a heterogeneous group of nuclei, questions remain about potential differences in the maturation of its subregions during development. In 3953 9- and 10-year-olds from the Adolescent Brain Cognitive Development℠ Study, the CIT168 Atlas was used to segment nine amygdala subregions. Linear mixed-effects models were used to examine the effects of age, sex, pubertal stage, and body mass index z-score (BMIz) on subregion volumes and their relative apportionment within the amygdala. Distinct associations were observed between age, sex, and BMIz with whole amygdala volume, subregion volumes, and subregion apportionment. Pubertal stage was not related to amygdala subregion volumes. Age was associated with near-global expansion of amygdala subregions during this developmental period. Female sex was linked to smaller volumes in most amygdala subregions, with larger relative apportionment in the dorsal subregions and smaller apportionment in the basolateral ventral paralaminar subregion. Higher BMIz was associated with smaller volumes in large basolateral subregions, with increased relative apportionment in smaller subregions. These findings provide a foundational context for understanding how developmental variables influence amygdala structure, with implications for understanding future risk for brain disorders.

Time Persistence of the FMRI Resting-State Functional Brain Networks

Time persistence is a fundamental property of many complex physical and biological systems; thus understanding the phenomenon in the brain is of high importance. Time persistence has been explored at the level of stand-alone neural time-series, but since the brain functions as an interconnected network, it is essential to examine time persistence at the network level. Changes in resting-state networks have been previously investigated using both dynamic (i.e., examining connectivity states) and static functional connectivity (i.e., test-retest reliability), but no systematic investigation of the time persistence as a network was conducted, particularly across different timescales (i.e., seconds, minutes, dozens of seconds, days) and different brain subnetworks. Additionally, individual differences in network time persistence have not been explored. Here, we devised a new framework to estimate network time persistence at both the link (i.e., connection) and node levels. In a comprehensive series analysis of three functional MRI resting-state datasets including both sexes, we established that (1) the resting-state functional brain network becomes gradually less similar to itself for the gaps up to 23 min within the run and even less similar for the gap between the days; (2) network time persistence varies across functional networks, while the sensory networks are more persistent than nonsensory networks; (3) participants show stable individual characteristic persistence, which has a genetic component; and (4) individual characteristic persistence could be linked to behavioral performance. Overall, our detailed characterization of network time persistence sheds light on the potential role of time persistence in brain functioning and cognition.

Amygdala Subregion Volumes and Apportionment in Preadolescents - Associations with Age, Sex, and Body Mass Index

The amygdala, a key limbic structure, is critical to emotional, social, and appetitive behaviors that develop throughout adolescence. Composed of a heterogeneous group of nuclei, questions remain about potential differences in the maturation of its subregions during development. In 3,953 9- and 10-year-olds from the Adolescent Brain Cognitive Development Study, the CIT168 Amygdala Atlas was used to segment nine amygdala subregions. Linear mixed-effects models were used to examine the effects of age, sex, pubertal stage, and body mass index z-score (BMIz) on subregion volumes and their relative apportionment within the amygdala. Distinct associations were observed between age, sex, and BMIz and whole amygdala volume, subregion volumes, and subregion apportionment. Pubertal stage was not related to amygdala subregion volumes. Age was associated with near-global expansion of amygdala subregions during this developmental period. Female sex was linked to smaller volumes in most amygdala subregions, with larger relative apportionment in the dorsal subregions and smaller apportionment in the basolateral ventral paralaminar subregion. Higher BMIz was associated with smaller volumes in large basolateral subregions, with increased relative apportionment in smaller subregions. These findings provide a foundational context for understanding how developmental variables influence amygdala structure, with implications for understanding future risk for brain disorders.

Reliable multimodal brain signatures predict mental health outcomes in children

BACKGROUND

Inter-individual brain differences likely precede the emergence of mood and anxiety disorders, however, the specific brain alterations remain unclear. While many studies focus on a single imaging modality in isolation, recent advances in multimodal image analysis allow for a more comprehensive understanding of the complex neurobiology that underlies mental health.

METHODS

In a large population-based cohort of children from the Adolescent Brain Cognitive Development (ABCD) study (N > 10K), we applied data-driven linked independent component analysis to identify linked variations in cortical structure and white matter microstructure that together predict longitudinal behavioural and mental health symptoms. Brain differences were examined in a sub-sample of twins depending on the presence of at-risk behaviours.

RESULTS

Two multimodal brain signatures at age 9-10y predicted longitudinal mental health symptoms from 9-12y, with small effect sizes. Cortical variations in association, limbic and default mode regions linked with peripheral white matter microstructure together predicted higher depression and anxiety symptoms across two independent split-halves. The brain signature differed amongst depression and anxiety symptom trajectories and related to emotion-regulation network functional connectivity. Linked variations of subcortical structures and projection tract microstructure variably predicted behavioural inhibition, sensation seeking, and psychosis symptom severity over time in male participants. These brain patterns were significantly different between pairs of twins discordant for self-injurious behaviour.

CONCLUSIONS

Our results demonstrate reliable, multimodal brain patterns in childhood, before mood and anxiety disorders tend to emerge, that lay the foundation for long-term mental health outcomes and offer targets for early identification of children at-risk.

Enhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS

Large-scale GWAS studies have uncovered hundreds of genomic loci linked to facial and brain shape variation, but only tens associated with cranial vault shape, a largely overlooked aspect of the craniofacial complex. Surrounding the neocortex, the cranial vault plays a central role during craniofacial development and understanding its genetics are pivotal for understanding craniofacial conditions. Experimental biology and prior genetic studies have generated a wealth of knowledge that presents opportunities to aid further genetic discovery efforts. Here, we use the conditional FDR method to leverage GWAS data of facial shape, brain shape, and bone mineral density to enhance SNP discovery for cranial vault shape. This approach identified 120 independent genomic loci at 1% FDR, nearly tripling the number discovered through unconditioned analysis and implicating crucial craniofacial transcription factors and signaling pathways. These results significantly advance our genetic understanding of cranial vault shape and craniofacial development more broadly.

The role of socioeconomic status in shaping associations between sensory association cortex and prefrontal structure and implications for executive function

Socioeconomic status (SES) is associated with widespread differences in structure of temporal, parietal, occipital, and frontal cortices. Development of sensory processing regions-in particular visual association cortex (VAC) and auditory association cortex (AAC)-may scaffold development of the prefrontal cortex (PFC). Experiences that correlate with SES like cognitive stimulation and language may influence VAC and AAC development, in turn allowing the PFC to resolve conflicts between similar stimuli. SES-related differences in these regions may partly explain differences in executive function (EF) skills. Here, we use structural equation modeling of longitudinal data from the Adolescent Brain and Cognitive Development study to test the hypothesis that SES-related differences in AAC and VAC are associated with differences in structure of the PFC and development of the PFC over time, which in turn are associated with development of EF. We found partial support for this model, demonstrating that SES-related differences in PFC structure are mediated by differences in sensory cortex structure, and that SES-related differences in sensory cortex structure mediate the association between SES and EF. These findings highlight the role sensory processing regions play in SES-related differences in PFC development. Future studies should explore proximal environmental factors driving SES-related differences to inform interventions.

Longer scans boost prediction and cut costs in brain-wide association studies

A pervasive dilemma in brain-wide association studies (BWAS) is whether to prioritize functional MRI (fMRI) scan time or sample size. We derive a theoretical model showing that individual-level phenotypic prediction accuracy increases with sample size and total scan duration (sample size × scan time per participant). The model explains empirical prediction accuracies extremely well across 76 phenotypes from nine resting-fMRI and task-fMRI datasets (R2 = 0.89), spanning a wide range of scanners, acquisitions, racial groups, disorders and ages. For scans ≤20 mins, prediction accuracy increases linearly with the logarithm of total scan duration, suggesting interchangeability of sample size and scan time. However, sample size is ultimately more important than scan time in determining prediction accuracy. Nevertheless, when accounting for overhead costs associated with each participant (e.g., recruitment costs), to boost prediction accuracy, longer scans can yield substantial cost savings over larger sample size. To achieve high prediction performance, 10-min scans are highly cost inefficient. In most scenarios, the optimal scan time is ≥20 mins. On average, 30-min scans are the most cost-effective, yielding 22% cost savings over 10-min scans. Overshooting is cheaper than undershooting the optimal scan time, so we recommend aiming for ≥30 mins. Compared with resting-state whole-brain BWAS, the most cost-effective scan time is shorter for task-fMRI and longer for subcortical-cortical BWAS. Standard power calculations maximize sample size at the expense of scan time. Our study demonstrates that optimizing both sample size and scan time can boost prediction power while cutting costs. Our empirically informed reference is available for future study planning: WEB_APPLICATION_LINK.

Neural mechanisms underlying synchronization of movement to musical cues in Parkinson disease and aging

Introduction

External and internal musical cues provide therapeutic techniques for gait rehabilitation in aging and neurological disorders. For people with Parkinson disease (PwPD), mental singing is a type of internal cue that can regularize gait timing. No studies to date have directly measured brain activity during external and internal musical cues as used in gait rehabilitation. Evidence suggests the neural mechanisms of external vs. internal cued movement differ. External cues are thought to drive movement via recruitment of cerebello-thalamo-cortical (CTC) pathways, while internal cues are thought to rely more on striato-pallido-thalamocortical (SPT) pathways.

Methods

We investigated the neural mechanisms that underlie acute responses to external cues (listening to music) and internal cues (mental singing). Using fMRI, we imaged PwPD and age-matched healthy controls (HC) while performing finger tapping during musical cueing tasks.

Results

No differences were seen between PwPD and HC in any of the comparisons. Functional imaging results showed activation of sensorimotor cortex, temporal gyri, supplementary motor areas, and putamen for both cueing tasks. External cues additionally activated auditory cortex while internal cues additionally activated the cerebellum. When directly comparing cue types, external cues displayed greater activity in the primary auditory cortex and temporal gyri.

Discussion

These results suggest similar brain regions are activated during musically-cued movements for both PwPD and HC and both cue types utilize parallel pathways for processing. Both cue types may facilitate use of remaining function of areas that degenerate in PD (e.g., putamen) and potentially also activate routes through less impaired areas (e.g., cerebellum). This supports the idea that the CTC and SPT pathways work in tandem and facilitate sensorimotor activity via a complex interplay between neural circuits. These findings have implications for how external and internal cues may be administered in future therapies.

Network Localization of Pediatric Lesion-Induced Dystonia

OBJECTIVE

Dystonia is a movement disorder defined by involuntary muscle contractions leading to abnormal postures or twisting and repetitive movements. Classically dystonia has been thought of as a disorder of the basal ganglia, but newer results in idiopathic dystonia and lesion-induced dystonia in adults point to broader motor network dysfunction spanning the basal ganglia, cerebellum, premotor cortex, sensorimotor, and frontoparietal regions. It is unclear whether a similar network is shared between different etiologies of pediatric lesion-induced dystonia.

METHODS

Three cohorts of pediatric patients with lesion-induced dystonia were identified. The lesion etiologies included hypoxia, kernicterus, and stroke versus comparison subjects with acquired lesions not associated with dystonia. Multivariate lesion-symptom mapping and lesion network mapping were used to evaluate the anatomy and networks associated with dystonia.

RESULTS

Multivariate lesion-symptom mapping showed that lesions of the putamen and globus pallidus were associated with dystonia (r = 0.41, p < 0.001). Lesion network mapping using normative connectome data from healthy children demonstrated that these regional findings occurred within a common brain-wide network that involves the basal ganglia, anterior and medial cerebellum, and cortical regions that overlap the cingulo-opercular action-mode and somato-cognitive-action networks.

INTERPRETATION

We interpret these findings as novel evidence for a unified dystonia brain network that involves the somato-cognitive-action network, which is implicated in the coordination of movement. Elucidation of this network gives insight into the functional origins of dystonia and provides novel targets to investigate for therapeutic intervention. ANN NEUROL 2025.

Assessing neurocognitive maturation in early adolescence based on baby and adult functional brain landscapes

Adolescence is a period of growth in cognitive performance and functioning. Recently, data-driven measures of brain-age gap, which can index cognitive decline in older populations, have been utilized in adolescent data with mixed findings. Instead of using a data-driven approach, here we assess the maturation status of the brain functional landscape in early adolescence by directly comparing an individual's resting-state functional connectivity (rsFC) to the canonical early-life and adulthood communities. Specifically, we hypothesized that the degree to which a youth's connectome is better captured by adult networks compared to infant/toddler networks is predictive of their cognitive development. To test this hypothesis across individuals and longitudinally, we utilized the Adolescent Brain Cognitive Development (ABCD) Study at baseline (9-10 years; n = 6469) and 2-year-follow-up (Y2: 11-12 years; n = 5060). Adjusted for demographic factors, our anchored rsFC score (AFC) was associated with better task performance both across and within participants. AFC was related to age and aging across youth, and change in AFC statistically mediated the age-related change in task performance. In conclusion, we showed that a model-fitting-free index of the brain at rest that is anchored to both adult and baby connectivity landscapes predicts cognitive performance and development in youth.

Longitudinal Sex-at-Birth and Age Analyses of Cortical Structure in the ABCD Study

While the brain continues to develop during adolescence, such development may depend on sex-at-birth. However, the elucidation of such differences may be hindered by analytical decisions (e.g., covariate selection to address brain-size differences) and the typical reporting of cross-sectional data. To further evaluate adolescent cortical development, we analyzed data from the Adolescent Brain Cognitive Development Study, whose cohort of 11,000+ youth participants with biannual neuroimaging data collection can facilitate understanding neuroanatomical change during a critical developmental window. Doubly considering individual differences within the context of group-level effects, we analyzed regional changes in cortical thickness, sulcal depth, surface area, and volume between two timepoints (∼2 years apart) in 9- to 12-year-olds assigned male or female sex-at-birth. First, we conducted linear mixed-effect models to gauge how controlling for intracranial volume, whole-brain volume (WBV), or a summary metric (e.g., mean cortical thickness) influenced interpretations of age-dependent cortical change. Next, we evaluated the relative changes in thickness and surface area as a function of sex-at-birth and age. Here, we showed that WBV (thickness, sulcal depth, volume) and total cortical surface area were more optimal covariates; controlling for different covariates would have substantially altered our interpretations of overall and sex-at-birth-specific neuroanatomical development. Furthermore, we provided evidence to suggest that aggregate change in how cortical thickness is changing relative to surface area is generally comparable across those assigned male or female sex-at-birth, with corresponding change happening at slightly older ages in those assigned male sex-at-birth. Overall, these results help elucidate neuroanatomical developmental trajectories in early adolescence.

Person-centered analyses reveal that developmental adversity at moderate levels and neural threat/safety discrimination are associated with lower anxiety in early adulthood

Parsing heterogeneity in the nature of adversity exposure and neurobiological functioning may facilitate better understanding of how adversity shapes individual variation in risk for and resilience against anxiety. One putative mechanism linking adversity exposure with anxiety is disrupted threat and safety learning. Here, we applied a person-centered approach (latent profile analysis) to characterize patterns of adversity exposure at specific developmental stages and threat/safety discrimination in corticolimbic circuitry in 120 young adults. We then compared how the resultant profiles differed in anxiety symptoms. Three latent profiles emerged: (1) a group with lower lifetime adversity, higher neural activation to threat, and lower neural activation to safety; (2) a group with moderate adversity during middle childhood and adolescence, lower neural activation to threat, and higher neural activation to safety; and (3) a group with higher lifetime adversity exposure and minimal neural activation to both threat and safety. Individuals in the second profile had lower anxiety than the other profiles. These findings demonstrate how variability in within-person combinations of adversity exposure and neural threat/safety discrimination can differentially relate to anxiety, and suggest that for some individuals, moderate adversity exposure during middle childhood and adolescence could be associated with processes that foster resilience to future anxiety.

Randomized Controlled Trial of the Effects of High-Dose Ondansetron on Clinical Symptoms and Brain Connectivity in Obsessive-Compulsive and Tic Disorders

OBJECTIVE

Sensory phenomena (SP) are aversive sensations driving repetitive behaviors in obsessive-compulsive disorder (OCD) and Tourette's disorder that are not well addressed by standard treatments. SP are related to the functioning of an interoceptive-sensorimotor circuit that may be modulated by the 5-HT3 receptor antagonist ondansetron. The present study employed an experimental medicine approach to test the effects of 4 weeks of high-dose ondansetron compared to placebo on SP severity and brain connectivity in a cohort of individuals with OCD and/or Tourette's disorder.

METHODS

Of 51 participants who completed the study, 27 were assigned to receive 24 mg/day of ondansetron and 24 to receive placebo. Analyses examined changes in SP severity and, for participants with OCD, overall OCD severity from baseline to final visit. Functional MRI data were collected at both visits for analysis of intrinsic functional connectivity metrics characterizing global correlation (reflecting area "hubness") and local correlation (reflecting near-neighbor coherence).

RESULTS

There were no significant differences between ondansetron and placebo in the reduction of SP or overall OCD severity in the full sample. In a subsample of participants with OCD taking concomitant serotonin reuptake inhibitors (SRIs), ondansetron was associated with a significant decrease in overall OCD severity and global connectivity of the medial sensorimotor cortex compared with placebo. Longitudinal reductions in SP severity were related to decreases in right sensorimotor hubness in both groups, and to brainstem local coherence only in participants taking ondansetron.

CONCLUSIONS

There was no effect of high-dose ondansetron on SP. However, when used as an augmentation to SRIs, ondansetron reduced overall OCD severity, which may be related to changes in the "hubness" of the sensorimotor cortex. Ondansetron's ability to modulate brainstem connectivity may underlie its variable effectiveness in reducing SP.

Exploring the associations between the presence, characteristics, and biopsychosocial covariates of pain and lifetime depression in adolescents: A cross-sectional ABCD study analysis

INTRODUCTION

Depression and pain co-occur, even during adolescence. However, there is limited knowledge on the association between pain and lifetime depression, and which biopsychosocial measures are associated with this co-occurrence.

METHODS

Cross-sectional analysis of the Adolescent Brain and Cognitive Development (ABCD) two-year follow-up. We explored associations between the presence and characteristics of past month pain (intensity, duration, activity limitations, and number of pain sites) and lifetime depression using logistic regression. We explored associations of brain structure, physical, behavioural, emotional, social, and cognitive measures with lifetime depression and past month pain compared to having had one or neither condition using multinomial logistic regression.

RESULTS

A total of 5211 adolescents (mean age = 12.0 years) who had: (1) no lifetime mental ill-health and no pain (n = 3327); (2) pain only (n = 1407); (3) lifetime depressive disorder but no pain (n = 272); and (4) lifetime depressive disorder and pain (n = 205) were included. Pain presence was associated with lifetime depression (OR[95%CI]: 1.76 [1.45, 2.13], p < 0.001). Pain-related activity limitations (1.13 [1.06, 1.21], p < 0.001) and the number of pain sites (1.06 [1.02, 1.09], p < 0.001) were associated with lifetime depression. Various behavioural, emotional, social, and cognitive, but not brain structure or physical measures, were associated with lifetime depression and past month pain.

LIMITATIONS

Longitudinal analyses should validate prognostic markers for predicting co-occurring depression and pain.

CONCLUSIONS

Results support an association between the presence and characteristics of pain and lifetime depression during adolescence and could indicate the need for more integrated recognition and clinical care of youth experiencing both depression and pain.

Parental warmth buffers the negative impact of weaker fronto-striatal connectivity on early adolescents' academic achievement

In past decades, the positive role of self-control in students' academic success has attracted plenty of scholarly attention. However, fewer studies have examined the link between adolescents' neural development of the inhibitory control system and their academic achievement, especially using a longitudinal approach. Moreover, less is known about the role of parents in this link. Using large-scale longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (N = 9574; mean age = 9.94 years at baseline, SD = .63; 50% girls), the current study took an integrative biopsychosocial approach to explore the longitudinal link between early adolescents' fronto-striatal connectivity and their academic achievement, with attention to the moderating role of parental warmth. Results showed that weaker intrinsic connectivity between the frontoparietal network and the striatum was associated with early adolescents' worse academic achievement over 2 years during early adolescence. Notably, parental warmth moderated the association between fronto-striatal connectivity and academic achievement, such that weaker fronto-striatal connectivity was only predictive of worse academic achievement among early adolescents who experienced low levels of parental warmth. Taken together, the findings demonstrate weaker fronto-striatal connectivity as a risk factor for early adolescents' academic development and highlight parental warmth as a protective factor for academic development among those with weaker connectivity within the inhibitory control system.

Probing Puberty as a Source of Developmental Change in Neural Response to Emotional Faces in Early Adolescence

Pubertal development is theorized to shape the brain's response to socio-emotional information in the environment. Large-scale longitudinal studies, such as the Adolescent Brain Cognitive Development (ABCD) study, provide the opportunity to examine the association between pubertal maturation and within-person changes in neural activation to emotional stimuli over time. Leveraging ABCD data (n = 9648), the current study examines the coupling between parent-reported pubertal development and changes in youth's brain response to emotional faces in an emotional n-back task (during functional magnetic resonance imaging) across two timepoints (2 years apart). Bivariate latent change score models were fit to regions of interest canonically involved in face processing (fusiform), emotional/motivational salience (amygdala, nucleus accumbens, orbitofrontal cortex [OFC]), and social cognition (temporoparietal junction [TPJ]) to determine the associations between baseline pubertal status and neural response, and rate of change in either variable across time. Results point to both concurrent and longitudinal associations between pubertal maturation and neural activation to emotional faces in regions involved in processing emotional and social information (amygdala, TPJ, accumbens, OFC) but not basic facial processing (fusiform). These findings highlight pubertal maturation as a potential mechanism for change in neural response to emotional information during the transition from childhood to adolescence.

Multifactorial influences on childhood insomnia: Genetic, socioeconomic, brain development and psychopathology insights

Insomnia is the most prevalent sleep disturbance during childhood and can result in extensively detrimental effects. Children's insomnia involves a complex interplay of biological, neurodevelopmental, social-environmental, and behavioral variables, yet remains insufficiently addressed. This study aimed to investigate the multifactorial etiology of childhood insomnia from its genetic architecture and social-environmental variables to its neural instantiation and the relationship to mental health. This cohort study uses 4340 participants at baseline and 2717 participants at 2-year follow-up from the Adolescent Brain Cognitive Development (ABCD) Study. We assessed the joint effects of polygenic risk score (PRS) and socioeconomic status (SES) on insomnia symptoms and then investigated the underlying neurodevelopmental mechanisms. Structural equation model (SEM) was applied to investigate the directional relationships among these variables. SES and PRS affected children's insomnia symptoms independently and additively (SES: β = -0.089, P = 1.91 × 10-8; PRS: β = 0.041, P = 0.008), which was further indirectly mediated by the deviation of inferior precentral sulcus (β = 0.0027, P = 0.0071). SEM revealed that insomnia (β = 0.457, P < 0.001) and precentral development (β = -0.039, P = 0.009) significantly mediated the effect of SES_PRS (accumulated risks of PRS and SES) on psychopathology symptoms. Furthermore, baseline insomnia symptoms, SES_PRS, and precentral deviation significantly predicted individual total psychopathology syndromes (r = 0.346, P < 0.001). These findings suggest the additive effects of genetic and socioenvironmental factors on childhood insomnia via precentral development and highlight potential targets in early detection and intervention for childhood insomnia.

A neural network to create super-resolution MR from multiple 2D brain scans of pediatric patients

BACKGROUND

High-resolution (HR) 3D MR images provide detailed soft-tissue information that is useful in assessing long-term side-effects after treatment in childhood cancer survivors, such as morphological changes in brain structures. However, these images require long acquisition times, so routinely acquired follow-up images after treatment often consist of 2D low-resolution (LR) images (with thick slices in multiple planes).

PURPOSE

In this work, we present a super-resolution convolutional neural network, based on previous single-image MRI super-resolution work, that can reconstruct a HR image from 2D LR slices in multiple planes in order to facilitate the extraction of structural biomarkers from routine scans.

METHODS

A multilevel densely connected super-resolution convolutional neural network (mDCSRN) was adapted to take two perpendicular LR scans (e.g., coronal and axial) as tensors and reconstruct a 3D HR image. A training set of 90 HR T1 pediatric head scans from the Adolescent Brain Cognitive Development (ABCD) study was used, with 2D LR images simulated through a downsampling pipeline that introduces motion artifacts, blurring, and registration errors to make the LR scans more realistic to routinely acquired ones. The outputs of the model were compared against simple interpolation in two steps. First, the quality of the reconstructed HR images was assessed using the peak signal-to-noise ratio and structural similarity index compared to baseline. Second, the precision of structure segmentation (using the autocontouring software Limbus AI) in the reconstructed versus the baseline HR images was assessed using mean distance-to-agreement (mDTA) and 95% Hausdorff distance. Three datasets were used: 10 new ABCD images (dataset 1), 18 images from the Children's Brain Tumor Network (CBTN) study (dataset 2) and 6 "real-world" follow-up images of a pediatric head and neck cancer patient (dataset 3).

RESULTS

The proposed mDCSRN outperformed simple interpolation in terms of visual quality. Similarly, structure segmentations were closer to baseline images after 3D reconstruction. The mDTA improved to, on average (95% confidence interval), 0.7 (0.4-1.0) and 0.8 (0.7-0.9) mm for datasets 1 and 3 respectively, from the interpolation performance of 6.5 (3.6-9.5) and 1.2 (1.0-1.3) mm.

CONCLUSIONS

We demonstrate that deep learning methods can successfully reconstruct 3D HR images from 2D LR ones, potentially unlocking datasets for retrospective study and advancing research in the long-term effects of pediatric cancer. Our model outperforms standard interpolation, both in perceptual quality and for autocontouring. Further work is needed to validate it for additional structural analysis tasks.

Air pollution and cortical myelin T1w/T2w ratio estimates in school-age children from the ABCD and NeuroSmog studies

Air pollution affects human health and may disrupt brain maturation, including axon myelination, critical for efficient neural signaling. Here, we assess the impact of prenatal and current long-term particulate matter (PM) and nitrogen dioxide (NO2) exposure on cortical T1w/T2w ratios - a proxy for myelin content - in school-age children from the Adolescent Brain Cognitive Development (ABCD) Study (United States; N = 2021) and NeuroSmog study (Poland; N = 577), using Siemens scanners. Across both samples, we found that NO2 and PM were not significantly associated with cortical T1w/T2w except for one association of PM10 with lower T1w/T2w in the precuneus in NeuroSmog. Superficially, ABCD Study analyses including data from all scanner types (Siemens, GE, Philips; N = 3089) revealed a negative association between NO₂ exposure and T1w/T2w ratios. However, this finding could be an artifact of between-site sociodemographic differences and large scanner-type-related measurement differences. While significant associations between air pollution and cortical myelin were largely absent, these findings do not rule out the possibility that air pollution affects cortical myelin during other exposure periods/stages of neurodevelopment. Future research should examine these relationships across diverse populations and developmental periods using unified analysis methods to better understand the potential neurotoxic effects of air pollution.

Distinct distributed brain networks dissociate self-generated mental states

Human cognition relies on two modes: a perceptually-coupled mode where mental states are driven by sensory input and a perceptually-decoupled mode featuring self-generated mental content. Past work suggests that imagined states are supported by the reinstatement of activity in sensory cortex, but transmodal systems within the canonical default network are also implicated in mind-wandering, recollection, and imagining the future. We identified brain systems supporting self-generated states using precision fMRI. Participants imagined different scenarios in the scanner, then rated their mental states on several properties using multi-dimensional experience sampling. We found that thinking involving scenes evoked activity within or near the default network, while imagining speech evoked activity within or near the language network. Imagining-related regions overlapped with activity evoked by viewing scenes or listening to speech, respectively; however, this overlap was predominantly within transmodal association networks, rather than adjacent unimodal sensory networks. The results suggest that different association networks support imagined states that are high in visual or auditory vividness.