Adolescent Development of Cortical and White Matter Structure in the NCANDA Sample: Role of Sex, Ethnicity, Puberty, and Alcohol Drinking

Association of Neuromelanin-Sensitive MRI Signal With Lifetime Substance Use in Young Women

OBJECTIVE

Midbrain dopamine function plays a key role in translational models of substance use disorders. Whether midbrain dopamine function is associated with substance use frequency and severity or reward function in 20-24 year-olds remains a critical gap in knowledge. The authors collected neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a validated index of lifetime dopamine function in the substantia nigra/ventral tegmentum area (SN-VTA) complex, to characterize altered dopamine function.

METHOD

Midbrain NM-MRI contrast-to-noise ratio (CNR) was acquired in 135 20-24 year-olds (105 women and 30 men). A composite measure of cumulative substance use was derived from factor analysis of lifetime alcohol intoxications, lifetime cannabis use, use of nicotine in heaviest month, number of classes of drugs used, and ever meeting DSM-5 criteria for a SUD. Trait reward function was assessed by self-report.

RESULTS

Cumulative substance use was significantly positively associated with NM-MRI CNR in a large area of the bilateral SN-VTA complex, an effect which was driven by women (who comprised most of the sample) and by voxels with greater NM-MRI CNR, including the ventral tegmentum area. NM-MRI CNR was not associated with individual differences in trait reward function.

CONCLUSIONS

History of substance use is associated with greater NM signal in NM-rich areas of the midbrain, especially in women. Future longitudinal studies with repeated NM-MRI assessments, especially in younger cohorts and while including more men, are warranted to evaluate whether aberrant dopamine function predates, follows, or is modulated by substance use.

More similarity than difference: comparison of within- and between-sex variance in early adolescent brain structure

Background

Adolescent neuroimaging studies of sex differences in the human brain predominantly examine mean differences between males and females. This focus on between-groups differences without probing relative distributions and similarities may contribute to both conflation and overestimation of sex differences and sexual dimorphism in the developing human brain.

Methods

We aimed to characterize the variance in brain macro- and micro-structure in early adolescence as it pertains to sex at birth using a large sample of 9-11 year-olds from the Adolescent Brain Cognitive Development (ABCD) Study (N=7,723). Specifically, for global and regional estimates of gray and white matter volume, cortical thickness, and white matter microstructure (i.e., fractional anisotropy and mean diffusivity), we examined: within- and between-sex variance, overlap between male and female distributions, inhomogeneity of variance via the Fligner-Killeen test, and an analysis of similarities (ANOSIM). For completeness, we examined these sex differences using both uncorrected (raw) brain estimates and residualized brain estimates after using mixed-effects modeling to account for age, pubertal development, socioeconomic status, race, ethnicity, MRI scanner manufacturer, and total brain volume, where applicable.

Results

The overlap between male and female distributions was universally greater than the difference (overlap coefficient range: 0.585 - 0.985) and the ratio of within-sex and between-sex differences was similar (ANOSIM R range: -0.001 - 0.117). All cortical and subcortical volumes showed significant inhomogeneity of variance, whereas a minority of brain regions showed significant sex differences in variance for cortical thickness, white matter volume, fractional anisotropy, and mean diffusivity. Inhomogeneity of variance was reduced after accounting for other sources of variance. Overlap coefficients were larger and ANOSIM R values were smaller for residualized outcomes, indicating greater within- and smaller between-sex differences once accounting for other covariates.

Conclusions

Reported sex differences in early adolescent human brain structure may be driven by disparities in variance, rather than binary, sex-based phenotypes. Contrary to the popular view of the brain as sexually dimorphic, we found more similarity than difference between sexes in all global and regional measurements of brain structure examined. This study builds upon previous findings illustrating the importance of considering variance when examining sex differences in brain structure.

Multi-dimensional predictors of first drinking initiation and regular drinking onset in adolescence: A prospective longitudinal study

Early adolescent drinking onset is linked to myriad negative consequences. Using the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) baseline to year 8 data, this study (1) leveraged best subsets selection and Cox Proportional Hazards regressions to identify the most robust predictors of adolescent first and regular drinking onset, and (2) examined the clinical utility of drinking onset in forecasting later binge drinking and withdrawal effects. Baseline predictors included youth psychodevelopmental characteristics, cognition, brain structure, family, peer, and neighborhood domains. Participants (N=538) were alcohol-naïve at baseline. The strongest predictors of first and regular drinking onset were positive alcohol expectancies (Hazard Ratios [HRs]=1.67-1.87), easy home alcohol access (HRs=1.62-1.67), more parental solicitation (e.g., inquiring about activities; HRs=1.72-1.76), and less parental control and knowledge (HRs=.72-.73). Robust linear regressions showed earlier first and regular drinking onset predicted earlier transition into binge and regular binge drinking (βs=0.57-0.95). Zero-inflated Poisson regressions revealed that delayed first and regular drinking increased the likelihood (Incidence Rate Ratios [IRR]=1.62 and IRR=1.29, respectively) of never experiencing withdrawal. Findings identified behavioral and environmental factors predicting temporal paths to youthful drinking, dissociated first from regular drinking initiation, and revealed adverse sequelae of younger drinking initiation, supporting efforts to delay drinking onset.

A longitudinal study of the relationship between alcohol-related blackouts and attenuated structural brain development

PURPOSE

Alcohol-related blackouts (ARBs) are common in adolescents and emerging adults. ARBs may also be indicative of persistent, alcohol-related neurocognitive changes. This study explored ARBs as a predictor of altered structural brain development and associated cognitive correlates.

METHODS

Longitudinal growth curve modeling estimated trajectories of brain volume across 6 years in participants from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study (n = 800, 213 with lifetime ARB history). While controlling for demographics and overall alcohol use, ARB history was analyzed as a predictor of brain volume growth in regions associated with alcohol-related cognitive change. Post hoc analyses examined whether ARBs moderated relationships between brain morphology and cognition.

RESULTS

ARBs significantly predicted attenuated development of fusiform gyrus and hippocampal volume at unique timepoints compared to overall alcohol use. Alcohol use without ARBs significantly predicted attenuated fusiform and hippocampal growth at earlier and later timepoints, respectively. Despite altered development in regions associated with memory, ARBs did not significantly moderate relationships between brain volume and cognitive performance.

CONCLUSION

ARBs and overall alcohol use predicted altered brain development in the fusiform gyrus and hippocampus at different timepoints, suggesting ARBs represent a unique marker of neurocognitive risk in younger drinkers.

Alcohol and brain structure across the lifespan: A systematic review of large-scale neuroimaging studies

Alcohol exposure affects brain structure, but the extent to which its effects differ across development remains unclear. Several countries are considering changes to recommended guidelines for alcohol consumption, so high-quality evidence is needed. Many studies have been conducted among small samples, but recent efforts have been made to acquire large samples to characterize alcohol's effects on the brain on a population level. Several large-scale consortia have acquired such samples, but this evidence has not been synthesized across the lifespan. We conducted a systematic review of large-scale neuroimaging studies examining effects of alcohol exposure on brain structure at multiple developmental stages. We included studies with an alcohol-exposed sample of at least N = 100 from the following consortia: ABCD, ENIGMA, NCANDA, IMAGEN, Framingham Offspring Study, HCP and UK BioBank. Twenty-seven studies were included, examining prenatal (N = 1), adolescent (N = 9), low-to-moderate-level adult (N = 11) and heavy adult (N = 7) exposure. Prenatal exposure was associated with greater brain volume at ages 9-10, but contemporaneous alcohol consumption during adolescence and adulthood was associated with smaller volume/thickness. Both low-to-moderate consumption and heavy consumption were characterized by smaller volume and thickness in frontal, temporal and parietal regions, and reductions in insula, cingulate and subcortical structures. Adolescent consumption had similar effects, with less consistent evidence for smaller cingulate, insula and subcortical volume. In sum, prenatal exposure was associated with larger volume, while adolescent and adult alcohol exposure was associated with smaller volume and thickness, suggesting that regional patterns of effects of alcohol are similar in adolescence and adulthood.

More similarity than difference: comparison of within- and between-sex variance in early adolescent brain structure

Background

Adolescent neuroimaging studies of sex differences in the human brain predominantly examine mean differences between males and females. This focus on between-groups differences without probing relative distributions and similarities may contribute to both conflation and overestimation of sex differences and sexual dimorphism in the developing human brain.

Methods

We aimed to characterize the variance in brain macro- and micro-structure in early adolescence as it pertains to sex at birth using a large sample of 9-11 year-olds from the Adolescent Brain Cognitive Development (ABCD) Study (N=7,723). Specifically, for global and regional estimates of gray and white matter volume, cortical thickness, and white matter microstructure (i.e., fractional anisotropy and mean diffusivity), we examined: within- and between-sex variance, overlap between male and female distributions, inhomogeneity of variance via the Fligner-Killeen test, and an analysis of similarities (ANOSIM). For completeness, we examined these sex differences using both uncorrected (raw) brain estimates and residualized brain estimates after using mixed-effects modeling to account for age, pubertal development, socioeconomic status, race, ethnicity, MRI scanner manufacturer, and total brain volume, where applicable.

Results

The overlap between male and female distributions was universally greater than the difference (overlap coefficient range: 0.585 - 0.985) and the ratio of within-sex and between-sex differences was similar (ANOSIM R range: -0.001 - 0.117). All cortical and subcortical volumes showed significant inhomogeneity of variance, whereas a minority of brain regions showed significant sex differences in variance for cortical thickness, white matter volume, fractional anisotropy, and mean diffusivity. Inhomogeneity of variance was reduced after accounting for other sources of variance. Overlap coefficients were larger and ANOSIM R values were smaller for residualized outcomes, indicating greater within- and smaller between-sex differences once accounting for other covariates.

Conclusions

Reported sex differences in early adolescent human brain structure may be driven by disparities in variance, rather than binary, sex-based phenotypes. Contrary to the popular view of the brain as sexually dimorphic, we found more similarity than difference between sexes in all global and regional measurements of brain structure examined. This study builds upon previous findings illustrating the importance of considering variance when examining sex differences in brain structure.

Sex Differences in Alcohol Use: Is It All About Hormones?

Risky alcohol use and alcohol use disorders (AUD) are a rising problem in women, yet a major disparity in our understanding of what drives alcohol consumption in women remains. Historically biomedical research has focused on male subjects; however, recent increases in reporting of females, have highlighted major differences between the sexes. Here we review the current literature of the effect of gonadal steroid hormones (estrogens, androgens, and progestins), neurosteriods, and neurobiological factors on alcohol use in clinical and preclinical studies of both sexes. Further, we briefly discuss how fundamental sex differences in genetics, metabolism, neuroimmune, and stress responses may influence sex differences in alcohol intake. Comparing the sexes could aid in the discovery of novel therapeutics to treat AUD, and implementation of current treatment options in women.

Adjustment of Regional Cortical Thickness Measures for Global Cortical Thickness Obscures Deficits Across the Schizophrenia Spectrum: A Cautionary Note About Normative Modeling of Brain Imaging Data

Recent neuroimaging studies and publicly disseminated analytic tools suggest that regional morphometric analyses covary for global thickness. We empirically demonstrated that this statistical approach severely underestimates regional thickness dysmorphology in psychiatric disorders. Study 1 included 90 healthy control participants, 51 participants at clinical high risk for psychosis, and 78 participants with early-illness schizophrenia. Study 2 included 56 healthy control participants, 83 participants with nonaffective psychosis, and 30 participants with affective psychosis. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with and without global thickness covariation. Global and regional thickness were strongly correlated across groups. Global thickness was lower in the schizophrenia spectrum groups than the other groups. Regional thickness deficits in schizophrenia spectrum groups were attenuated or eliminated with global thickness covariation. Eliminating the variation that regional thickness shares with global thickness eliminated disease-related effects. This statistical approach results in erroneous conclusions that regional thickness is normal in disorders like schizophrenia or clinical high risk syndrome.

Volumetric segmentation in the context of posterior fossa-related pathologies: a systematic review

BACKGROUND

Segmentation tools continue to advance, evolving from manual contouring to deep learning. Researchers have utilized segmentation to study a myriad of posterior fossa-related conditions, such as Chiari malformation, trigeminal neuralgia, post-operative pediatric cerebellar mutism syndrome, and Crouzon syndrome. Herein, we present a summary of the current literature on segmentation of the posterior fossa. The review highlights the various segmentation techniques, and their respective strengths and weaknesses, employed along with objectives and outcomes of the various studies reported in the literature.

METHODS

A literature search was conducted in PubMed, Embase, Cochrane, and Web of Science up to November 2023 for articles on segmentation techniques of posterior fossa. The two senior authors searched through databases based on the keywords of the article separately and then enrolled joint articles that met the inclusion and exclusion criteria.

RESULTS

The initial search identified 2205 articles. After applying inclusion and exclusion criteria, 77 articles were selected for full-text review after screening of titles/abstracts. 52 articles were ultimately included in the review. Segmentation techniques included manual, semi-automated, and fully automated (atlas-based, convolutional neural networks). The most common pathology investigated was Chiari malformation.

CONCLUSIONS

Various forms of segmentation techniques have been used to assess posterior fossa volumes/pathologies and each has its advantages and disadvantages. We discuss these nuances and summarize the current state of literature in the context of posterior fossa-associated pathologies.

Associations Between Family History of Alcohol and/or Substance Use Problems and Frontal Cortical Development From 9 to 13 Years of Age: A Longitudinal Analysis of the ABCD Study

Background

Previous investigations that have examined associations between family history (FH) of alcohol/substance use and adolescent brain development have been primarily cross-sectional. Here, leveraging a large population-based sample of youths, we characterized frontal cortical trajectories among 9- to 13-year-olds with (FH+) versus without (FH-) an FH and examined sex as a potential moderator.

Methods

We used data from 9710 participants in the Adolescent Brain Cognitive Development (ABCD) Study (release 4.0). FH+ was defined as having ≥1 biological parents and/or ≥2 biological grandparents with a history of alcohol/substance use problems (n = 2433). Our primary outcome was frontal cortical structural measures obtained at baseline (ages 9-11) and year 2 follow-up (ages 11-13). We used linear mixed-effects models to examine the extent to which FH status qualified frontal cortical development over the age span studied. Finally, we ran additional interactions with sex to test whether observed associations between FH and cortical development differed significantly between sexes.

Results

For FH+ (vs. FH-) youths, we observed increased cortical thinning from 9 to 13 years across the frontal cortex as a whole. When we probed for sex differences, we observed significant declines in frontal cortical thickness among boys but not girls from ages 9 to 13 years. No associations were observed between FH and frontal cortical surface area or volume.

Conclusions

Having a FH+ is associated with more rapid thinning of the frontal cortex across ages 9 to 13, with this effect driven primarily by male participants. Future studies will need to test whether the observed pattern of accelerated thinning predicts future substance use outcomes.

Simulator Driving Abilities, Executive Functions, and Adaptive Behavior Among Adolescents With Complex Attention Deficit Hyperactivity Disorder

OBJECTIVE

To examines the driving skills, executive functions, and adaptive behavior of adolescents diagnosed with Attention-deficit/hyperactivity disorder (ADHD) combined with emotional difficulties and/or learning disabilities (complex ADHD), compared to adolescents without ADHD.

METHOD

A cross-sectional study including 30 adolescents with complex ADHD and 33 adolescents without ADHD aged 15 to 18 years. Driving skills on a simulator, executive functions, and adaptive behavior were evaluated.

RESULTS

Adolescents without ADHD demonstrated significantly higher total scores on the driving simulator, indicating better driving performance compared to adolescents with complex ADHD. In the complex ADHD group, after controlling for different Conners Comprehensive Behavior Rating Scale-Self Report scales, driving simulator scores were partially correlated with executive functions.

CONCLUSION

These findings emphasize the unique needs of adolescents with complex ADHD. Given the significance of driving in today's society, it is crucial to consider the development of intervention programs to support this population's driving skills.

Fronto-temporal cortical grey matter thickness and surface area in the at-risk mental state and recent-onset schizophrenia: a magnetic resonance imaging study

BACKGROUND

Studies to date examining cortical thickness and surface area in young individuals At Risk Mental State (ARMS) of developing psychosis have revealed inconsistent findings, either reporting increased, decreased or no differences compared to mentally healthy individuals. The inconsistencies may be attributed to small sample sizes, varying age ranges, different ARMS identification criteria, lack of control for recreational substance use and antipsychotic pharmacotherapy, as well as different methods for deriving morphological brain measures.

METHODS

A surfaced-based approach was employed to calculate fronto-temporal cortical grey matter thickness and surface area derived from magnetic resonance imaging (MRI) data collected from 44 young antipsychotic-naïve ARMS individuals, 19 young people with recent onset schizophrenia, and 36 age-matched healthy volunteers. We conducted group comparisons of the morphological measures and explored their association with symptom severity, global and socio-occupational function levels, and the degree of alcohol and cannabis use in the ARMS group.

RESULTS

Grey matter thickness and surface areas in ARMS individuals did not significantly differ from their age-matched healthy counterparts. However, reduced left-frontal grey matter thickness was correlated with greater symptom severity and lower function levels; the latter being also correlated with smaller left-frontal surface areas. ARMS individuals with more severe symptoms showed greater similarities to the recent onset schizophrenia group. The morphological measures in ARMS did not correlate with the lifetime level of alcohol or cannabis use.

CONCLUSIONS

Our findings suggest that a decline in function levels and worsening mental state are associated with morphological changes in the left frontal cortex in ARMS but to a lesser extent than those seen in recent onset schizophrenia. Alcohol and cannabis use did not confound these findings. However, the cross-sectional nature of our study limits our ability to draw conclusions about the potential progressive nature of these morphological changes in ARMS.

Brain structural covariance network features are robust markers of early heavy alcohol use

BACKGROUND AND AIMS

Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies.

DESIGN AND SETTING

Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years).

CASES

Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected.

MEASUREMENTS

Graph theory metrics of segregation and integration were used to summarize SCN.

FINDINGS

Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar.

CONCLUSION

Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

Loss of free will in the Iranian criminal justice system: Interdisciplinary analysis of law and neuroscience

Today, with the development of neuroscience and the discovery of new secrets of the brain, the social sciences, including law, have made significant progress with the help of new findings in this science. One of the significant applications of neuroscience in modern criminal law is the explanation of the neurological dimensions of human free will, which in addition to creating a profound and scientific approach to the definition of this important element of criminal responsibility, can help ascertain the loss of free will causes. To this end, the present study is an attempt to answer this question in the context of the Iranian criminal justice system: What are the core causes of the loss of free will from the perspective of neurolaw? The paper strives to take an appropriate step toward the development of criminal justice. In this study, we found that mental disorders, coercion, drunkenness, somnambulism, and error are the core causes that can be assessed in particular ways using EEG and fMRI techniques, however, each with limitations.

Longitudinal relationships between lifestyle risk factors and neurodevelopment in early adolescence

OBJECTIVE

The goal of this study is to investigate the cross-sectional and longitudinal relationships between clustered lifestyle risk factors (sleep, physical activity, body mass index [BMI], and screen time) and neurodevelopment over the early adolescent period.

METHOD

Data from the ABCD Study Data Release 3.0 consisted of 11,878 participants (aged 9-10 years) at baseline and 6,571 participants (aged 11-12 years) at 2-year follow-up. The interrelationships between lifestyle risk factors and brain structure were analyzed using bivariate multiple indicator latent change score models. Using confirmatory factor analysis, a single lifestyle risk factor domain (measured by sleep, physical activity, BMI, and screen time) was shown to fit the data well. Using exploratory and confirmatory factor analysis, seven brain structure domains were extracted and labeled as temporal-parietal, frontotemporal, occipital, orbitofrontal, temporal, cingulate, parietal, and cuneus domains. All bivariate latent change score models accounted for age, sex at birth, race/ethnicity, parental education, and marital status.

RESULTS

Higher lifestyle risk was associated with smaller brain volume at baseline. Higher baseline lifestyle risk was also associated with a greater rate of change (i.e., greater decreases) in brain volume for the temporal-parietal, frontotemporal, orbitofrontal, parietal, and cuneus domains. Effects were not reciprocal; baseline brain volume did not predict changes in lifestyle behaviors over time.

CONCLUSION

These findings are important for understanding the biological mechanisms underpinning health risk factors and can be used to target interventions and improve brain health during this critical developmental phase. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Associations between alcohol use and sex-specific maturation of subcortical gray matter morphometry from adolescence to adulthood: Replication across two longitudinal samples

Subcortical brain morphometry matures across adolescence and young adulthood, a time when many youth engage in escalating levels of alcohol use. Initial cross-sectional studies have shown alcohol use is associated with altered subcortical morphometry. However, longitudinal evidence of sex-specific neuromaturation and associations with alcohol use remains limited. This project used generalized additive mixed models to examine sex-specific development of subcortical volumes and associations with recent alcohol use, using 7 longitudinal waves (n = 804, 51% female, ages 12-21 at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA). A second, independent, longitudinal dataset, with up to four waves of data (n = 467, 43% female, ages 10-18 at baseline), was used to assess replicability. Significant, replicable non-linear normative volumetric changes with age were evident in the caudate, putamen, thalamus, pallidum, amygdala and hippocampus. Significant, replicable negative associations between subcortical volume and alcohol use were found in the hippocampus in all youth, and the caudate and thalamus in female but not male youth, with significant interactions present in the caudate, thalamus and putamen. Findings suggest a structural vulnerability to alcohol use, or a predisposition to drink alcohol based on brain structure, with female youth potentially showing heightened risk, compared to male youth.

White matter microstructural integrity continues to develop from adolescence to young adulthood in mice and humans: Same phenotype, different mechanism

As direct evaluation of a mouse model of human neurodevelopment, adolescent and young adult mice and humans underwent MR diffusion tensor imaging to quantify age-related differences in microstructural integrity of brain white matter fibers. Fractional anisotropy (FA) was greater in older than younger mice and humans. Despite the cross-species commonality, the underlying developmental mechanism differed: whereas evidence for greater axonal extension contributed to higher FA in older mice, evidence for continuing myelination contributed to higher FA in human adolescent development. These differences occurred in the context of species distinctions in overall brain growth: whereas the continued growth of the brain and skull in the murine model can accommodate volume expansion into adulthood, human white matter volume and myelination continue growth into adulthood within a fixed intracranial volume. Appreciation of the similarities and differences in developmental mechanism can enhance the utility of animal models of brain white matter structure, function, and response to exogenous manipulation.

Cortical thickness is inversely associated with transcranial magnetic stimulation-evoked N45 potential among young adults whose heavy drinking began in adolescence

BACKGROUND

Adolescence is a particularly vulnerable stage of development in terms of the deleterious effects of alcohol. Both lower gray matter (GM) volume and greater GABAergic activity have been associated with chronic alcohol consumption during adolescence. However, the association between these measures has not been investigated.

METHODS

In this exploratory study, we compared 26 young adults with a 10year history of heavy alcohol consumption with 21 controls who used little or no alcohol. Simultaneous transcranial magnetic stimulation and electroencephalography were used to assess transcranial magnetic stimulation-evoked N45 potentials, reflecting a balance between GABAergic inhibition and N-methyl-D-aspartate (NMDA) receptor-mediated glutaminergic excitation in the brain. GM thickness was measured from magnetic resonance images and GM and N45 potentials were then correlated.

RESULTS

Cortical thickness was significantly lower in several brain regions in the heavy-drinking group than the light-drinking group. The N45 amplitude was significantly larger frontally in the heavy-drinking group. Among heavy drinkers, there were several statistically significant correlations between thinner GM and larger frontal N45 amplitudes that were not detectable in the light-drinking group. The strongest correlations were detected in the frontal and parietal lobes, especially in the left superior frontal gyrus and the left supramarginal gyrus, and in both hemispheres in the superior parietal lobes.

CONCLUSIONS

These findings show that a thinner cortex and greater inhibitory neurotransmission are correlated in certain brain regions among young, long-term heavy alcohol users. Studies are needed to explore the possible causal mechanisms underlying these effects.

A Mega-analytic Study of White Matter Microstructural Differences Across 5 Cohorts of Youths With Attention-Deficit/Hyperactivity Disorder

BACKGROUND

While attention-deficit/hyperactivity disorder (ADHD) has been associated with differences in the structural connections formed by the brain's white matter tracts, studies of such differences have yielded inconsistent findings, likely reflecting small sample sizes. Thus, we conducted a mega-analysis on in vivo measures of white matter microstructure obtained through diffusion tensor imaging of more than 6000 participants from 5 cohorts.

METHODS

In a mega-analysis, linear mixed models were used to test for associations between the fractional anisotropy of 42 white matter tracts and ADHD traits and diagnosis. Contrasts were made against measures of mood, anxiety, and other externalizing problems.

RESULTS

Overall, 6993 participants (ages 6-18 years, mean age 10.62 years [SD 1.99]; 3368 girls, 3625 boys; 764 African American, 4146 non-Hispanic White, and 2083 other race/ethnicities) had measures of ADHD and other emotional/behavioral symptoms (N = 6933) and/or enough clinical data to allow a diagnosis of ADHD (n = 951) or its absence (n = 4884). Both the diagnosis and symptoms of ADHD were associated with lower fractional anisotropy of the inferior longitudinal and left uncinate fasciculi (at a false discovery rate-adjusted p < .05). Associated effect sizes were small (the strongest association with ADHD traits had an effect size of partial r = -0.14, while the largest case-control difference was associated with an effect size of d = -0.3). Similar microstructural anomalies were not present for anxiety, mood, or externalizing problems. Findings held when ADHD cases and control subjects were matched on in-scanner motion.

CONCLUSIONS

While present across cohorts, ADHD-associated microstructural differences had small effects, underscoring the limited clinical utility of this imaging modality used in isolation.

Exploring the indirect effect of loneliness in the association between problematic use of social networks and cognitive function in Lebanese adolescents

BACKGROUND

Problematic use of social networks is a widespread problem that may exert deleterious impacts on cognitive functions. Moreover, studies have added an important link between loneliness and its harmful effect on cognitive functions. Other studies have also revealed that problematic use of social networks among teenagers has a pejorative influence on their social interactions, leading to increased social isolation. Therefore, the goal of our research was to investigate the link between problematic use of social networks and cognitive function in a group of Lebanese adolescents while also taking into consideration the indirect role of loneliness in this relationship.

METHODS

This cross-sectional study, which was carried out between January and April 2022, included 379 teenagers (aged between 13 and 17 years), from all Lebanese governorates. The PROCESS SPSS Macro version 3.4, model four was used to compute three pathways. Pathway A determined the regression coefficient for the effect of problematic use of social networks on loneliness; Pathway B examined the association between loneliness and cognitive function, and Pathway C' estimated the direct effect of problematic use of social networks on cognitive function.

RESULTS

Higher negative social comparison, addictive consequences of problematic use of social networks, and loneliness were significantly associated with worse cognitive function. Loneliness mediated the association between negative social comparison and worse cognitive function, as well as between addictive consequences of problematic use of social networks and worse cognitive function. In addition, higher financial burden was significantly correlated with worse cognitive function, whereas higher physical activity was related to better cognitive function.

CONCLUSION

In sum, the current study supports that problematic use of social networks is negatively associated with adolescents' cognitive function, where loneliness seems to play a pivotal role in this equation. The results thus endorse the importance of helping Lebanese adolescents to overcome problematic use of social networks and recover from their loneliness, to achieve a better cognitive/academic performance.

Associations between multi-method latent factors of puberty and brain structure in adolescent girls

Pubertal processes are associated with structural brain development, but studies have produced inconsistent findings that may relate to different measurements of puberty. Measuring both hormones and physical characteristics is important for capturing variation in neurobiological development. The current study explored associations between cortical thickness and latent factors from multi-method pubertal data in 174 early adolescent girls aged 10-13 years in the Transitions in Adolescent Girls (TAG) Study. Our multi-method approach used self-reported physical characteristics and hormone levels (dehydroepiandrosterone (DHEA), testosterone (T), and estradiol (E2) from saliva) to estimate an overall pubertal factor and for each process of adrenarche and gonadarche. There were negative associations between the overall puberty factor representing later stage and thickness in the posterior cortex, including the occipital cortices and extending laterally to the parietal lobe. However, the multi-method latent factor had weaker cortical associations when examining the adnearcheal process alone, suggesting physical characteristics and hormones capture different aspects of neurobiological development during adrenarche. Controlling for age weakened some of these associations. These findings show that associations between pubertal stage and cortical thickness differ depending on the measurement method and the pubertal process, and both should be considered in future confirmatory studies on the developing brain.

Adverse Childhood Experiences and Binge Drinking in Adolescence: the Role of Impulsivity and PTSD Symptoms

Background

The present study examines impulsivity and posttraumatic stress disorder (PTSD) symptoms as factors that may help understand the relationship between adverse childhood experiences (ACEs) and adolescent binge drinking.

Methods

Data were drawn from a subset of adolescents (N = 285) ages 12-22 from the National Consortium on Alcohol & Neurodevelopment in Adolescence (NCANDA). Impulsivity and PTSD symptoms were each predicted to moderate the relationship between ACEs and binge drinking.

Results

The positive relationship between PTSD symptoms and binge drinking was stronger when impulsivity was included. The positive relationship between ACEs and binge drinking was also strengthened when accounting for PTSD symptoms.

Conclusion

Our results provide evidence that impulsivity and PTSD symptoms may increase the risk for binge drinking during adolescence, including following ACEs. Interventions targeting PTSD symptoms and impulsivity could be valuable tools in preventing adolescent binge drinking.

Alcohol use disorder: Neuroimaging evidence for accelerated aging of brain morphology and hypothesized contribution to age-related dementia

Excessive alcohol use curtails longevity by rendering intoxicated individuals vulnerable to heightened risk from accidents, violence, and alcohol poisoning, and makes chronically heavy drinkers vulnerable to acceleration of age-related medical and psychiatric conditions that can be life threatening (Yoon, Chen, Slater, Jung, & White, 2020). Thus, studies of factors influencing age-alcohol interactions must consider the potential that the alcohol use disorder (AUD) population may not represent the oldest ages of the unaffected population and may well have accrued comorbidities associated with both AUD and aging itself. Herein, we focus on the aging of the brains of men and women with AUD, keeping AUD contextual factors in mind. Knowledge of the potential influence of the AUD-associated co-factors on the condition of brain structure may lead to identifying modifiable risk factors to avert physical declines and may reverse or arrest further AUD-related degradation of the brain. In this narrative review, we 1) describe quantitative, controlled studies of brain macrostructure and microstructure of adults with AUD, 2) consider the possibility of recovery of brain integrity through harm reduction with sustained abstinence or reduced drinking, and 3) speculate on the ramifications of accelerated aging in AUD as contributing to age-related dementia.

The role of brain structure in the association between pubertal timing and depression risk in an early adolescent sample (the ABCD Study®): A registered report

BACKGROUND

Earlier pubertal timing is associated with higher rates of depressive disorders in adolescence. Neuroimaging studies report brain structural associations with both pubertal timing and depression. However, whether brain structure mediates the relationship between pubertal timing and depression remains unclear.

METHODS

The current registered report examined associations between pubertal timing (indexed via perceived pubertal development), brain structure (cortical and subcortical metrics, and white matter microstructure) and depressive symptoms in a large sample (N = ∼5000) of adolescents (aged 9-13 years) from the Adolescent Brain Cognitive Development (ABCD) Study. We used three waves of follow-up data when the youth were aged 10-11 years, 11-12 years, and 12-13 years, respectively. We used generalised linear-mixed models (H1) and structural equation modelling (H2 & H3) to test our hypotheses.

HYPOTHESES

We hypothesised that earlier pubertal timing at Year 1 would be associated with increased depressive symptoms at Year 3 (H1), and that this relationship would be mediated by global (H2a-b) and regional (H3a-g) brain structural measures at Year 2. Global measures included reduced cortical volume, thickness, surface area and sulcal depth. Regional measures included reduced cortical thickness and volume in temporal and fronto-parietal areas, increased cortical volume in the ventral diencephalon, increased sulcal depth in the pars orbitalis, and reduced fractional anisotropy in the cortico-striatal tract and corpus callosum. These regions of interest were informed by our pilot analyses using baseline ABCD data when the youth were aged 9-10 years.

RESULTS

Earlier pubertal timing was associated with increased depressive symptoms two years later. The magnitude of effect was stronger in female youth and the association remained significant when controlling for parental depression, family income, and BMI in females but not in male youth. Our hypothesised brain structural measures did not however mediate the association between earlier pubertal timing and later depressive symptoms.

CONCLUSION

The present results demonstrate that youth, particularly females, who begin puberty ahead of their peers are at an increased risk for adolescent-onset depression. Future work should explore additional biological and socio-environmental factors that may affect this association so that we can identify targets for intervention to help these at-risk youth.

The effects of puberty and sex on adolescent white matter development: A systematic review

Adolescence, the transition between childhood and adulthood, is characterized by rapid brain development in white matter (WM) that is attributed in part to rising levels in adrenal and gonadal hormones. The extent to which pubertal hormones and related neuroendocrine processes explain sex differences in WM during this period is unclear. In this systematic review, we sought to examine whether there are consistent associations between hormonal changes and morphological and microstructural properties of WM across species and whether these effects are sex-specific. We identified 90 (75 human, 15 non-human) studies that met inclusion criteria for our analyses. While studies in human adolescents show notable heterogeneity, results broadly demonstrate that increases in gonadal hormones across pubertal development are associated with macro- and microstructural changes in WM tracts that are consistent with the sex differences found in non-human animals, particularly in the corpus callosum. We discuss limitations of the current state of the science and recommend important future directions for investigators in the field to consider in order to advance our understanding of the neuroscience of puberty and to promote forward and backward translation across model organisms.

Adolescent brain maturation and the neuropathological effects of binge drinking: A critical review

Adolescence is a transitional stage marked by continued brain development. This period is accompanied by physical and neurochemical modifications in the shape and function of the hippocampus, prefrontal cortex, and other limbic system structures. Brain maturation during adolescence, which is typically governed by intrinsic factors, can be dramatically altered by environmental influences such as drugs and alcohol. Unlike many other addictive substances, binge drinking is very common and normative among teenagers and young adults. This repeated pattern of excessive alcohol consumption in adolescents has been shown to cause behavioral changes and neurocognitive impairments that include increased anxiety, risky decision-making, and learning deficits, which could lead to the development of alcohol use disorder (AUD). This manuscript highlights factors that lead to adolescent binge drinking, discusses maturational changes that occur in an adolescent's brain, and then evaluates the effect of adolescent alcohol consumption on brain structure, function, and neurocognitive abilities in both human studies and animal models. The impact of gender/sex and COVID-19 are briefly discussed. Understanding the factors that promote the onset of adolescent binge drinking and its undesirable consequences could serve as a catalyst for developing therapeutic agents that would decrease or eradicate the damaging effects of alcohol on an adolescent brain.

Adolescent alcohol use is linked to disruptions in age-appropriate cortical thinning: an unsupervised machine learning approach

Cortical thickness changes dramatically during development and is associated with adolescent drinking. However, previous findings have been inconsistent and limited by region-of-interest approaches that are underpowered because they do not conform to the underlying spatially heterogeneous effects of alcohol. In this study, adolescents (n = 657; 12-22 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study who endorsed little to no alcohol use at baseline were assessed with structural magnetic resonance imaging and followed longitudinally at four yearly intervals. Seven unique spatial patterns of covarying cortical thickness were obtained from the baseline scans by applying an unsupervised machine learning method called non-negative matrix factorization (NMF). The cortical thickness maps of all participants' longitudinal scans were projected onto vertex-level cortical patterns to obtain participant-specific coefficients for each pattern. Linear mixed-effects models were fit to each pattern to investigate longitudinal effects of alcohol consumption on cortical thickness. We found in six NMF-derived cortical thickness patterns, the longitudinal rate of decline in no/low drinkers was similar for all age cohorts. Among moderate drinkers the decline was faster in the younger adolescent cohort and slower in the older cohort. Among heavy drinkers the decline was fastest in the younger cohort and slowest in the older cohort. The findings suggested that unsupervised machine learning successfully delineated spatially coordinated patterns of vertex-level cortical thickness variation that are unconstrained by neuroanatomical features. Age-appropriate cortical thinning is more rapid in younger adolescent drinkers and slower in older adolescent drinkers, an effect that is strongest among heavy drinkers.

Imputing Brain Measurements Across Data Sets via Graph Neural Networks

Publicly available data sets of structural MRIs might not contain specific measurements of brain Regions of Interests (ROIs) that are important for training machine learning models. For example, the curvature scores computed by Freesurfer are not released by the Adolescent Brain Cognitive Development (ABCD) Study. One can address this issue by simply reapplying Freesurfer to the data set. However, this approach is generally computationally and labor intensive (e.g., requiring quality control). An alternative is to impute the missing measurements via a deep learning approach. However, the state-of-the-art is designed to estimate randomly missing values rather than entire measurements. We therefore propose to re-frame the imputation problem as a prediction task on another (public) data set that contains the missing measurements and shares some ROI measurements with the data sets of interest. A deep learning model is then trained to predict the missing measurements from the shared ones and afterwards is applied to the other data sets. Our proposed algorithm models the dependencies between ROI measurements via a graph neural network (GNN) and accounts for demographic differences in brain measurements (e.g. sex) by feeding the graph encoding into a parallel architecture. The architecture simultaneously optimizes a graph decoder to impute values and a classifier in predicting demographic factors. We test the approach, called Demographic Aware Graph-based Imputation (DAGI), on imputing those missing Freesurfer measurements of ABCD (N=3760; minimum age 12 years) by training the predictor on those publicly released by the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA, N=540). 5-fold cross-validation on NCANDA reveals that the imputed scores are more accurate than those generated by linear regressors and deep learning models. Adding them also to a classifier trained in identifying sex results in higher accuracy than only using those Freesurfer scores provided by ABCD.

Evidence from "big data" for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples

We sought to identify resting-state characteristics related to attention deficit/hyperactivity disorder, both as a categorical diagnosis and as a trait feature, using large-scale samples which were processed according to a standardized pipeline. In categorical analyses, we considered 1301 subjects with diagnosed ADHD, contrasted against 1301 unaffected controls (total N = 2602; 1710 males (65.72%); mean age = 10.86 years, sd = 2.05). Cases and controls were 1:1 nearest neighbor matched on in-scanner motion and key demographic variables and drawn from multiple large cohorts. Associations between ADHD-traits and resting-state connectivity were also assessed in a large multi-cohort sample (N = 10,113). ADHD diagnosis was associated with less anticorrelation between the default mode and salience/ventral attention (B = 0.009, t = 3.45, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.014), somatomotor (B = 0.008, t = 3.49, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.013), and dorsal attention networks (B = 0.01, t = 4.28, p-FDR < 0.001, d = 0.17, 95% CI = 0.006, 0.015). These results were robust to sensitivity analyses considering comorbid internalizing problems, externalizing problems and psychostimulant medication. Similar findings were observed when examining ADHD traits, with the largest effect size observed for connectivity between the default mode network and the dorsal attention network (B = 0.0006, t = 5.57, p-FDR < 0.001, partial-r = 0.06, 95% CI = 0.0004, 0.0008). We report significant ADHD-related differences in interactions between the default mode network and task-positive networks, in line with default mode interference models of ADHD. Effect sizes (Cohen's d and partial-r, estimated from the mega-analytic models) were small, indicating subtle group differences. The overlap between the affected brain networks in the clinical and general population samples supports the notion of brain phenotypes operating along an ADHD continuum.

Multi-atlas thalamic nuclei segmentation on standard T1-weighed MRI with application to normal aging

Specific thalamic nuclei are implicated in healthy aging and age-related neurodegenerative diseases. However, few methods are available for robust automated segmentation of thalamic nuclei. The threefold aims of this study were to validate the use of a modified thalamic nuclei segmentation method on standard T1 MRI data, to apply this method to quantify age-related volume declines, and to test functional meaningfulness by predicting performance on motor testing. A modified version of THalamus Optimized Multi-Atlas Segmentation (THOMAS) generated 22 unilateral thalamic nuclei. For validation, we compared nuclear volumes obtained from THOMAS parcellation of white-matter-nulled (WMn) MRI data to T1 MRI data in 45 participants. To examine the effects of age/sex on thalamic nuclear volumes, T1 MRI available from a second data set of 121 men and 117 women, ages 20-86 years, were segmented using THOMAS. To test for functional ramifications, composite regions and constituent nuclei were correlated with Grooved Pegboard test scores. THOMAS on standard T1 data showed significant quantitative agreement with THOMAS from WMn data, especially for larger nuclei. Sex differences revealing larger volumes in men than women were accounted for by adjustment with supratentorial intracranial volume (sICV). Significant sICV-adjusted correlations between age and thalamic nuclear volumes were detected in 20 of the 22 unilateral nuclei and whole thalamus. Composite Posterior and Ventral regions and Ventral Anterior/Pulvinar nuclei correlated selectively with higher scores from the eye-hand coordination task. These results support the use of THOMAS for standard T1-weighted data as adequately robust for thalamic nuclear parcellation.

Developmental trajectories of Big Five personality traits among adolescents and young adults: Differences by sex, alcohol use, and marijuana use

OBJECTIVE

Individual differences in adolescent personality are related to a variety of long-term health outcomes. While previous studies have demonstrated sex differences and non-linear changes in personality development, these results remain equivocal. The current study utilized longitudinal data (n = 831) from the National Consortium on Alcohol and Neurodevelopment in Adolescence to examine sex differences in the development of personality and the association between substance use and personality.

METHOD

Participants (ages 12-21 at baseline) completed the Ten-Item Personality Inventory and self-reported past year alcohol and marijuana use at up to 7 yearly visits. Data were analyzed using generalized additive mixed-effects models and linear mixed-effects models.

RESULTS

Findings support linear increases in agreeableness and conscientious and decreases in openness with age and inform on timing of sex-specific non-linear development of extraversion and emotional stability. Further, results provide novel information regarding the timing of the association between substance use and personality, and replicate past reporting of differential associations between alcohol and marijuana use and extraversion, and sex-dependent effects of marijuana use on emotional stability.

CONCLUSIONS

These findings highlight the importance of modeling sex differences in personality development using flexible non-linear modeling strategies, and accounting for sex- and age-specific effects of alcohol and marijuana use.

Alcohol's effects on the mouse brain are modulated by age and sex

Binge alcohol consumption is common among adolescents and may impair normal brain development. Emerging, longitudinal studies in adolescents suggest that the effects of binge alcohol exposure on brain structure differ between sexes. To test the hypothesis that the effects of binge alcohol exposure on developmental brain growth trajectories are influenced by age of exposure and sex, adolescent and adult, male and female C57Bl/6 mice (n = 32), were exposed to a binge‐like ethanol (EtOH) exposure paradigm (i.e., 5 cycles of 2 on/2 off days of 5 g/kg EtOH intraperitoneal) or served as saline controls. Longitudinal structural magnetic resonance imaging was acquired at baseline, following binge EtOH exposure, and after 2 weeks of recovery. Alcohol treatment showed interactions with age and sex in altering whole brain volume: adolescents of both sexes demonstrated inhibited whole brain growth relative to their control counterparts, although significance was only attained in female mice which showed a larger magnitude response to EtOH compared to male mice. In region of interest analyses, the somatosensory cortex and cerebellum showed inhibited growth in male and female adolescent mice exposed to EtOH, but the difference relative to controls did not reach multiple comparison‐corrected statistical significance. These data suggest that in mice exposed to binge EtOH treatment, adolescent age of exposure and female sex may confer a higher risk to the detrimental effects of EtOH on brain structure and reinforce the need for direct testing of both sexes.

Drug-resistant focal epilepsy in children is associated with increased modal controllability of the whole brain and epileptogenic regions

Network control theory provides a framework by which neurophysiological dynamics of the brain can be modelled as a function of the structural connectome constructed from diffusion MRI. Average controllability describes the ability of a region to drive the brain to easy-to-reach neurophysiological states whilst modal controllability describes the ability of a region to drive the brain to difficult-to-reach states. In this study, we identify increases in mean average and modal controllability in children with drug-resistant epilepsy compared to healthy controls. Using simulations, we purport that these changes may be a result of increased thalamocortical connectivity. At the node level, we demonstrate decreased modal controllability in the thalamus and posterior cingulate regions. In those undergoing resective surgery, we also demonstrate increased modal controllability of the resected parcels, a finding specific to patients who were rendered seizure free following surgery. Changes in controllability are a manifestation of brain network dysfunction in epilepsy and may be a useful construct to understand the pathophysiology of this archetypical network disease. Understanding the mechanisms underlying these controllability changes may also facilitate the design of network-focussed interventions that seek to normalise network structure and function.

Adolescent Brain Development and Contextual Influences: A Decade in Review

Adolescence is a developmental period characterized by substantial psychological, biological, and neurobiological changes. This review discusses the past decade of research on the adolescent brain, as based on the overarching framework that development is a dynamic process both within the individual and between the individual and external inputs. As such, this review focuses on research showing that the development of the brain is influenced by multiple ongoing and dynamic elements. It highlights the implications this body of work on behavioral development and offers areas of opportunity for future research in the coming decade.

Hepatitis C Virus-Related Central and Peripheral Nervous System Disorders

Hepatitis C Virus (HCV), despite being a hepatotropic virus, is the causative agent of many systemic disorders, such as vasculitis, autoimmune diseases, lymphoproliferative disorders, and a broad spectrum of neurological and psychiatric manifestations. Although symptoms have been misdiagnosed or underdiagnosed, only recently, evidence of direct (inflammatory) or indirect (immune-mediated) HCV-dependent cerebral effects has been established. HCV infection can promote acute inflammatory response, pro-coagulative status and ischemic disorders, and neurodegeneration. These effects rely on cerebral HCV replication, possibly mediated by blood-brain barrier alterations. Further study is needed to better understand the HCV-related mechanisms of brain damage.

Adolescent Binge Drinking Is Associated With Accelerated Decline of Gray Matter Volume

The age- and time-dependent effects of binge drinking on adolescent brain development have not been well characterized even though binge drinking is a health crisis among adolescents. The impact of binge drinking on gray matter volume (GMV) development was examined using 5 waves of longitudinal data from the National Consortium on Alcohol and NeuroDevelopment in Adolescence study. Binge drinkers (n = 166) were compared with non-binge drinkers (n = 82 after matching on potential confounders). Number of binge drinking episodes in the past year was linked to decreased GMVs in bilateral Desikan-Killiany cortical parcellations (26 of 34 with P < 0.05/34) with the strongest effects observed in frontal regions. Interactions of binge drinking episodes and baseline age demonstrated stronger effects in younger participants. Statistical models sensitive to number of binge episodes and their temporal proximity to brain volumes provided the best fits. Consistent with prior research, results of this study highlight the negative effects of binge drinking on the developing brain. Our results present novel findings that cortical GMV decreases were greater in closer proximity to binge drinking episodes in a dose-response manner. This relation suggests a causal effect and raises the possibility that normal growth trajectories may be reinstated with alcohol abstinence.

Subclinical Anxiety and Posttraumatic Stress Influence Cortical Thinning During Adolescence

OBJECTIVE

Adolescence is a sensitive period for the development and emergence of anxiety and mood disorders. Research suggests that symptoms ranging from subclinical to clinical levels are associated with pathological developmental changes in the neocortex. However, much of this research has been cross-sectional, limiting the field's ability to identify the neurodevelopmental impacts of these symptoms. The present study examined how early reported symptoms predict baseline cortical thickness and surface area, and trajectories of change in these measures during adolescence.

METHOD

A total of 205 typically developing individuals 9 to 15 years of age (103 male and 102 female participants) completed 3T structural magnetic resonance imaging annually for 3 years. From these, we extracted mean cortical thickness and total surface area for each year. Youth self-reported their anxiety, depressive, and posttraumatic stress symptoms during their first visit. We used latent growth curve modeling to determine how these symptoms along with sex interactions predicted baseline thickness and surface area, and rates of change in these measures over the 3-year period.

RESULTS

Higher anxiety was associated with lower baseline thickness and slowed cortical thinning over time. Conversely, greater posttraumatic stress predicted higher baseline thickness and accelerated thinning over time. Sex interactions suggested that the effects were dampened among female compared to male participants. Depressive symptoms were not related to cortical thickness or surface area.

CONCLUSION

Female adolescents may express more regionally specific effects of symptoms sets on cortical thickness, although this requires further investigation. Cortical thickness in male adolescents appears to be preferentially susceptible to anxiety and posttraumatic stress symptoms, exhibiting global changes across multiple years.

Adversarial Bayesian Optimization for Quantifying Motion Artifact Within MRI

Subject motion during an MRI sequence can cause ghosting effects or diffuse image noise in the phase-encoding direction and hence is likely to bias findings in neuroimaging studies. Detecting motion artifacts often relies on experts visually inspecting MRIs, which is subjective and expensive. To improve this detection, we develop a framework to automatically quantify the severity of motion artifact within a brain MRI. We formulate this task as a regression problem and train the regressor from a data set of MRIs with various amounts of motion artifacts. To resolve the issue of missing fine-grained ground-truth labels (level of artifacts), we propose Adversarial Bayesian Optimization (ABO) to infer the distribution of motion parameters (i.e., rotation and translation) underlying the acquired MRI data and then inject synthetic motion artifacts sampled from that estimated distribution into motion-free MRIs. After training the regressor on the synthetic data, we applied the model to quantify the motion level in 990 MRIs collected by the National Consortium on Alcohol and Neurodevelopment in Adolescence. Results show that the motion level derived by our approach is more reliable than the traditional metric based on Entropy Focus Criterion and manually defined binary labels.

Sex-specific patterns of white matter microstructure are associated with emerging depression during adolescence

Prior research has demonstrated associations between adolescent depression and alterations in the white matter microstructure of fiber tracts implicated in emotion regulation. Using diffusion tensor imaging, this study explored premorbid, sex-specific white matter microstructural features that related to future emergence of major depressive disorder (MDD) during adolescence and young adulthood. Adolescents from the National Consortium on Alcohol and Neurodevelopment in Adolescence study, who were 12-21 years old at study entry and had not experienced major depression as of the baseline assessment, were selected for inclusion (N = 462, n = 223 female adolescents). Over five years of annual follow-up, 63 participants developed a diagnosis of MDD, as determined by the Computerized Semi-Structured Assessment for the Genetics of Alcoholism (n = 39 female adolescents). A whole-brain multivariate modeling approach was used to examine the relationship between fractional anisotropy (FA) at baseline and emergence into MDD, as a function of sex, controlling for age at baseline. Among female adolescents, those who developed MDD had significantly lower baseline FA in a portion of left precentral gyrus white matter, while male adolescents exhibited the opposite pattern. These results may serve as indirect microstructural markers of risk and targets for the prevention of depression during adolescence.

Neuroimaging markers of adolescent depression in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study

BACKGROUND

Adolescents are at increased risk of developing major depressive disorder (MDD) than many other age groups. Although the neural correlates of MDD in adults have been studied prospectively, such adolescent depression studies are mainly cross-sectional. We extracted data regarding the relationship between cortical thickness and later development of adolescent MDD from a national community study that uses an accelerated longitudinal design to examine the psychological, environmental, and neural differences related to drinking and brain development.

METHODS

692 subjects (age 12-21 years; 50% female) without a history of MDD were assessed with structural neuroimaging at baseline. We compared those 101 subjects who transitioned to MDD by 1-year follow-up to those who remained non-depressed over the same time period. FreeSurfer's autosegmentation process estimated vertex-wide cortical thicknesses and its Query, Design, Estimate, Contrast (Qdec) application investigated cortical thickness between those who later developed MDD and those who remained without MDD (Monte Carlo corrected for multiple comparisons, vertex-wise cluster threshold of 1.3, p < 0.01).

RESULTS

Those who transitioned in the next year to MDD had, at baseline, thinner cortices in the superior frontal cortex, precentral and postcentral regions, and superior temporal cortex, above and beyond effects attributable to age and sex. No cortical thickness sex differences or sex-by-depression interactions were observed.

LIMITATIONS

A larger sample size could improve statistical power and future investigations will be needed to confirm our results.

CONCLUSIONS

Thinner cortices over frontal and temporal regions may be linked to enhanced vulnerability for future depression during the adolescent-young adulthood transition.

Promising vulnerability markers of substance use and misuse: A review of human neurobehavioral studies

Substance use often begins, and noticeably escalates, during adolescence. Identifying predictive neurobehavioral vulnerability markers of substance use and related problems may improve targeted prevention and early intervention initiatives. This review synthesizes 44 longitudinal studies and explores the utility of developmental imbalance models and neurobehavioral addiction frameworks in predicting neural and cognitive patterns that are associated with prospective substance use initiation and escalation among young people. A total of 234 effect sizes were calculated and compared. Findings suggest that aberrant neural structure and function of regions implicated in reward processing, cognitive control, and impulsivity can predate substance use initiation, escalation, and disorder. Functional vulnerability markers of substance use include hyperactivation during reward feedback and risk evaluation in prefrontal and ventral striatal regions, fronto-parietal hypoactivation during working memory, distinctive neural patterns during successful (fronto-parietal hyperactivation) and failed response inhibition (frontal hypoactivation), and related cognitive deficits. Structurally, smaller fronto-parietal and amygdala volume and larger ventral striatal volume predicts prospective substance misuse. Taken together, the findings of this review suggest that neurobehavioral data can be useful in predicting future substance use behaviors. Notably, little to no research has empirically tested the underlying assumptions of widely used theoretical frameworks. To improve the reliability and utility of neurobehavioral data in predicting future substance use behaviors, recommendations for future research are provided. This article is part of the special issue on 'Vulnerabilities to Substance Abuse.'

Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence

Background

Adolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pubertal development and aging by longitudinally tracking structural brain development during adolescence.

Methods

Two cohorts of healthy children were recruited (cohort 1: 9–10 years old; cohort 2: 12–13 years old at baseline). MRI data were acquired for gray matter volume and white matter tract measures. To determine whether age, pubertal status, both or their interaction best modelled longitudinal data, we compared four multi-level linear regression models to the null model (general brain growth indexed by total segmented volume) using Bayesian model selection.

Results

Data were collected at baseline (n = 116), 12 months (n = 97) and 24 months (n = 84) after baseline. Findings demonstrated that the development of most regional gray matter volume, and white matter tract measures, were best modelled by age. Interestingly, precentral and paracentral regions of the cortex, as well as the accumbens demonstrated significant preference for the pubertal status model. None of the white matter tract measures were better modelled by pubertal status.

Limitations: The major limitation of this study is the two-cohort recruitment. Although this allowed a faster coverage of the age span, a complete per person trajectory over 6 years of development (9–15 years) could not be investigated.

Conclusions

Comparing the impact of age and pubertal status on regional gray matter volume and white matter tract measures, we found age to best predict longitudinal changes. Further longitudinal studies investigating the differential influence of puberty status and age on brain development in more diverse samples are needed to replicate the present results and address mechanisms underlying norm-variants in brain development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00429-020-02208-1.

Exploring valence bias as a metric for frontoamygdalar connectivity and depressive symptoms in childhood

Negativity bias is a core feature of depression that is associated with dysfunctional frontoamygdalar connectivity; this pathway is associated with emotion regulation and sensitive to neurobiological change during puberty. We used a valence bias task (ratings of emotional ambiguity) as a potential early indicator of depression risk and differences in frontoamygdalar connectivity. Previous work using this task demonstrated that children normatively have a negative bias that attenuates with maturation. Here, we test the hypothesis that persistence of this negativity bias as maturation ensues may reveal differences in emotion regulation development, and may be associated with increased risk for depression. In children aged 6-13 years, we tested the moderating role of puberty on relationships between valence bias, depressive symptoms, and frontoamygdalar connectivity. A negative bias was associated with increased depressive symptoms for those at more advanced pubertal stages (within this sample) and less regulatory frontoamygdalar connectivity, whereas a more positive bias was associated with more regulatory connectivity patterns. These data suggest that with maturation, individual differences in positivity biases and associated emotion regulation circuitry confer a differential risk for depression. Longitudinal work is necessary to determine the directionality of these effects and explore the influence of early life events.

Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study

Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30-0.65, all P_FDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31-0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24-0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10-0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.

Perceived stress, self-efficacy, and the cerebral morphometric markers in binge-drinking young adults

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Self-efficacy is negatively correlated with perceived stress in young adult drinkers.

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Binge vs. non-binge drinking men show diminished PCC thickness and dmPFC GMV.

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The metrics are positively/negatively each correlated with self-efficacy/stress.

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Path analyses show daily drinks → neural metrics → low self-efficacy → high stress.

Studies have identified cerebral morphometric markers of binge drinking and implicated cortical regions in support of self-efficacy and stress regulation. However, it remains unclear how cortical structures of self-control play a role in ameliorating stress and alcohol consumption or how chronic alcohol exposure alters self-control and leads to emotional distress. We examined the data of 180 binge (131 men) and 256 non-binge (83 men) drinkers from the Human Connectome Project. We obtained data on regional cortical thickness from the HCP and derived gray matter volumes (GMVs) with voxel-based morphometry. At a corrected threshold, binge relative to non-binge drinking men showed diminished posterior cingulate cortex (PCC) thickness and dorsomedial prefrontal cortex (dmPFC) GMV. PCC thickness and dmPFC GMVs were positively and negatively correlated with self-efficacy and perceived stress, respectively, as assessed with the NIH Emotion Toolbox. Mediation and path analyses to query the inter-relationships between the neural markers and clinical variables showed a best fit of the model with daily drinks → lower PCC thickness and dmPFC GMV → lower self-efficacy → higher perceived stress in men. In contrast, binge and non-binge drinking women did not show significant differences in regional cortical thickness or GMVs. These findings suggest a pathway whereby chronic alcohol consumption alters cortical structures and self-efficacy mediates the effects of cortical structural deficits on perceived stress in men. The findings also suggest the need to investigate multimodal neural markers underlying the interplay between stress, self-control and alcohol use behavior in women.

Training confounder-free deep learning models for medical applications

The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging studies. Confounders affect the relationship between input data (e.g., brain MRIs) and output variables (e.g., diagnosis). Improper modeling of those relationships often results in spurious and biased associations. Traditional machine learning and statistical models minimize the impact of confounders by, for example, matching data sets, stratifying data, or residualizing imaging measurements. Alternative strategies are needed for state-of-the-art deep learning models that use end-to-end training to automatically extract informative features from large set of images. In this article, we introduce an end-to-end approach for deriving features invariant to confounding factors while accounting for intrinsic correlations between the confounder(s) and prediction outcome. The method does so by exploiting concepts from traditional statistical methods and recent fair machine learning schemes. We evaluate the method on predicting the diagnosis of HIV solely from Magnetic Resonance Images (MRIs), identifying morphological sex differences in adolescence from those of the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA), and determining the bone age from X-ray images of children. The results show that our method can accurately predict while reducing biases associated with confounders. The code is available at https://github.com/qingyuzhao/br-net .

Regional growth trajectories of cortical myelination in adolescents and young adults: longitudinal validation and functional correlates

Adolescence is a time of continued cognitive and emotional evolution occurring with continuing brain development involving synaptic pruning and cortical myelination. The hypothesis of this study is that heavy myelination occurs in cortical regions with relatively direct, predetermined circuitry supporting unimodal sensory or motor functions and shows a steep developmental slope during adolescence (12-21 years) until young adulthood (22-35 years) when further myelination decelerates. By contrast, light myelination occurs in regions with highly plastic circuitry supporting complex functions and follows a delayed developmental trajectory. In support of this hypothesis, cortical myelin content was estimated and harmonized across publicly available datasets provided by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) and the Human Connectome Project (HCP). The cross-sectional analysis of 226 no-to-low alcohol drinking NCANDA adolescents revealed relatively steeper age-dependent trajectories of myelin growth in unimodal primary motor cortex and flatter age-dependent trajectories in multimodal mid/posterior cingulate cortices. This pattern of continued myelination showed smaller gains when the same analyses were performed on 686 young adults of the HCP cohort free of neuropsychiatric diagnoses. Critically, a predicted correlation between a motor task and myelin content in motor or cingulate cortices was found in the NCANDA adolescents, supporting the functional relevance of this imaging neurometric. Furthermore, the regional trajectory slopes were confirmed by performing longitudinally consistent analysis of cortical myelin. In conclusion, coordination of myelin content and circuit complexity continues to develop throughout adolescence, contributes to performance maturation, and may represent active cortical development climaxing in young adulthood.

Little evidence for associations between the Big Five personality traits and variability in brain gray or white matter

Attempts to link the Big Five personality traits of Openness-to-Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism with variability in trait-like features of brain structure have produced inconsistent results. Small sample sizes and heterogeneous methodology have been suspected in driving these inconsistencies. Here, using data collected from 1,107 university students (636 women, mean age 19.69 ​± ​1.24 years), representing the largest sample to date of unrelated individuals, we tested for associations between the Big Five personality traits and measures of cortical thickness and surface area, subcortical volume, and white matter microstructural integrity. In addition to replication analyses based on a prior study, we conducted exploratory whole-brain analyses. Four supplementary analyses were also conducted to examine 1) possible associations with lower-order facets of personality; 2) modulatory effects of sex; 3) effect of controlling for non-target personality traits; and 4) parcellation scheme effects. Our analyses failed to identify significant associations between the Big Five personality traits and brain morphometry, except for a weak association between greater surface area of the superior temporal gyrus and lower conscientiousness scores. As the latter association is not supported by previous studies, it should be treated with caution. Our supplementary analyses mirrored these predominantly null findings, suggesting they were not substantively biased by our analytic choices. Collectively, these results indicate that if there are associations between the Big Five personality traits and brain structure, they are likely of very small effect size and will require very large samples for reliable detection.

The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain

Brain development has largely been studied through unimodal analysis of neuroimaging data, providing independent results for structural and functional data. However, structure clearly impacts function and vice versa, pointing to the need for performing multimodal data collection and analysis to improve our understanding of brain development, and to further inform models of typical and atypical brain development across the lifespan. Ultimately, such models should also incorporate genetic and epigenetic mechanisms underlying brain structure and function, although currently this area is poorly specified. To this end, we are reporting here a multi-site, multi-modal dataset that captures cognitive function, brain structure and function, and genetic and epigenetic measures to better quantify the factors that influence brain development in children originally aged 9-14 years. Data collection for the Developmental Chronnecto-Genomics (Dev-CoG) study (http://devcog.mrn.org/) includes cognitive, emotional, and social performance scales, structural and functional MRI, diffusion MRI, magnetoencephalography (MEG), and saliva collection for DNA analysis of single nucleotide polymorphisms (SNPs) and DNA methylation patterns. Across two sites (The Mind Research Network and the University of Nebraska Medical Center), data from over 200 participants were collected and these children were re-tested annually for at least 3 years. The data collection protocol, sample demographics, and data quality measures for the dataset are presented here. The sample will be made freely available through the collaborative informatics and neuroimaging suite (COINS) database at the conclusion of the study.