Publications

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Classification of infant and parent vocalizations, particularly emotional vocalizations, is critical to understanding how infants learn to regulate emotions in social dyadic processes. This work is an experimental study of classifiers, features, and data augmentation strategies applied to the task of classifying infant and parent vocalization types. Our data were recorded both in the home and in the laboratory. Infant vocalizations were manually labeled as cry, fus (fuss), lau (laugh), bab (babble) or scr (screech), while parent (mostly mother) vocalizations were labeled as ids (infant-directed speech), ads (adult-directed speech), pla (playful), rhy (rhythmic speech or singing), lau (laugh) or whi (whisper). Linear discriminant analysis (LDA) was selected as a baseline classifier, because it gave the highest accuracy in a previously published study covering part of this corpus. LDA was compared to two neural network architectures: a two-layer fully-connected network (FCN), and a convolutional neural network with self-attention (CNSA). Baseline features extracted using the OpenSMILE toolkit were augmented by extra voice quality, phonetic, and prosodic features, each targeting perceptual features of one or more of the vocalization types. Three web data augmentation and transfer learning methods were tested: pre-training of network weights for a related task (adult emotion classification), augmentation of under-represented classes using data uniformly sampled from other corpora, and augmentation of under-represented classes using data selected by a minimum cross-corpus information difference criterion. Feature selection using Fisher scores and experiments of using weighted and unweighted samplers were also tested. Two datasets were evaluated: a benchmark dataset (CRIED) and our own corpus. In terms of unweighted-average recall of CRIED dataset, the CNSA achieved the best UAR compared with previous studies. In terms of classification accuracy, weighted F1, and macro F1 of our own dataset, the neural networks both significantly outperformed LDA; the FCN slightly (but not significantly) outperformed the CNSA. Cross-examining features selected by different feature selection algorithms permits a type of post-hoc feature analysis, in which the most important acoustic features for each binary type discrimination are listed. Examples of each vocalization type of overlapped features were selected, and their spectrograms are presented, and discussed with respect to the type-discriminative acoustic features selected by various algorithms. MFCC, log Mel Frequency Band Energy, LSP frequency, and F1 are found to be the most important spectral envelope features; F0 is found to be the most important prosodic feature.

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Increasing evidence supports a link between maternal prenatal cannabis use and altered neural and physiological development of the child. However, whether cannabis use relates to altered human brain development prior to birth, and specifically, whether maternal prenatal cannabis use relates to connectivity of fetal functional brain systems, remains an open question. The major objective of this study was to identify whether maternal prenatal cannabis exposure (PCE) is associated with variation in human brain hippocampal functional connectivity prior to birth. Prenatal drug toxicology and fetal fMRI data were available in a sample of 115 fetuses [43 % female; mean age 32.2 weeks (SD = 4.3)]. Voxelwise hippocampal connectivity analysis in a subset of age and sex-matched fetuses revealed that PCE was associated with alterations in fetal dorsolateral, medial and superior frontal, insula, anterior temporal, and posterior cingulate connectivity. Classification of group differences by age 5 outcomes suggest that compared to the non-PCE group, the PCE group is more likely to have increased connectivity to regions associated with less favorable outcomes and to have decreased connectivity to regions associated with more favorable outcomes. This is preliminary evidence that altered fetal neural connectome may contribute to neurobehavioral vulnerability observed in children exposed to cannabis in utero.

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A major challenge in designing large-scale, multi-site studies is developing a core, scalable protocol that retains the innovation of scientific advances while also lending itself to the variability in experience and resources across sites. In the development of a common Healthy Brain and Child Development (HBCD) protocol, one of the chief questions is “is fetal MRI ready for prime-time?” While there is agreement about the value of prenatal data obtained non-invasively through MRI, questions about practicality abound. There has been rapid progress over the past years in fetal and placental MRI methodology but there is uncertainty about whether the gains afforded outweigh the challenges in supporting fetal MRI protocols at scale. Here, we will define challenges inherent in building a common protocol across sites with variable expertise and will propose a tentative framework for evaluation of design decisions. We will compare and contrast various design considerations for both normative and high-risk populations, in the setting of the post-COVID era. We will conclude with articulation of the benefits of overcoming these challenges and would lend to the primary questions articulated in the HBCD initiative.

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A test-retest study of FreeSurfer derived cortical thickness, cortical surface area, and cortical volume, as well as quantitative R1 relaxometry assessed on the midpoint of the cortex, was performed on a cohort of pediatric subjects (6-12 years old) scanned without sedation using SNARE-MPnRAGE (self navigated retrospective motion corrected magnetization prepared with n rapid gradient echoes) imaging. Reliability was assessed with coefficients of variation (CoVs) and intraclass correlation coefficients (ICCs) and statistical tests were used to determine differences with and without SNARE motion correction. Comparison of the test-retest measures of SNARE-MPnRAGE with prospectively motion corrected PROMO MPRAGE were also performed. When SNARE motion correction was used all parameters had statistically significant improvements and demonstrated high reliability. Reliability varied depending on parameter, region, and measurement type (vertex or region of interest). For mean thickness/surface area/volume/mean R1 across the regions of FreeSurfer’s DK Atlas, the mean CoVs (% x100) were (1.2/1.6/1.9/0.9) and the mean ICCs were (0.88/0.96/0.94/0.83). When assessed on a per-vertex basis, the CoVs and ICCs for thickness/R1 had mean values of (2.9/1.9) and (0.82/0.68) across the regions of the DK Atlas. Retrospectively motion corrected MPnRAGE had significantly lower CoVs and higher ICCs for the morphological measures than PROMO MPRAGE. Motion correction effectively removed motion related biases in nearly all regions for R1 and morphometric measures.

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Prenatal opioid exposure has been linked to altered neurodevelopment and visual problems such as strabismus and nystagmus. The neural substrate underlying these alterations is unclear. Resting-state functional connectivity MRI (rsfMRI) is an advanced and well-established technique to evaluate brain networks. Few studies have examined the effects of prenatal opioid exposure on resting-state network connectivity in infancy. In this pilot study, we characterized network connectivity in opioid-exposed infants (n = 19) and controls (n = 20) between 4-8 weeks of age using both a whole-brain connectomic approach and a seed-based approach. Prenatal opioid exposure was associated with differences in distribution of betweenness centrality and connection length, with positive connections unique to each group significantly longer than common connections. The unique connections in the opioid-exposed group were more often inter-network connections while unique connections in controls and connections common to both groups were more often intra-network. The opioid-exposed group had smaller network volumes particularly in the primary visual network, but similar network strength as controls. Network topologies as determined by dice similarity index were different between groups, particularly in visual and executive control networks. These results may provide insight into the neural basis for the developmental and visual problems associated with prenatal opioid exposure.

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There is a dire need for research regarding the implications of opioid use during pregnancy on fetal and childhood development to better inform both medical practice and policy. The Healthy Brain and Child Development Study will examine brain and behavioral development from birth through the first decade of life. Due to large scope and anticipated complexity of this initiative, an 18-month planning phase was implemented across 28 sites across the nation. A core element of the Phase I initiative involved the development of Stakeholder Advisory Committees to inform the next phase of the initiative. Phase I stakeholder meetings were conducted at Oregon Health and Science University, New York University Langone Medical Center, the University of Pittsburgh, and the University of Vermont to better understand perspectives and inform upcoming research. Despite differences in the structure of the stakeholder meetings by site, the overarching goals for the meetings included establishing relationships, gathering input, and learning about research engagement. Documents from each meeting were reviewed for location, duration, attendees, common research themes, and pertinent suggestions for improving research approaches. All stakeholders had high levels of interest in research for pregnant people with substance use disorders and agreed on research priorities including collaboration, connection, communication, and support. Different stakeholders offered unique perspectives on various aspects of study design and themes that emerged through meetings. Overall, there was excitement about the research, especially the opportunity to include the voices of people with lived experience; collaboration between providers, peer support specialists, patients, and others; and excitement around contributing to research that could elucidate new and pertinent findings in the realm of addiction medicine and child development. Sites also found that there is mistrust between people with substance use disorder and the medical system, and this could be addressed by including people with lived experience on the research team, forming connections, communicating clearly, training the research team in implicit bias, and practicing trauma-informed care. In conclusion, these stakeholder meetings provided valuable information for structuring upcoming studies; however, researchers would have benefitted from more time and more opportunities for in-person connection.

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The COVID-19 pandemic priorities have focused on prevention, detection, and response. Beyond morbidity and mortality, pandemics carry secondary impacts, such as children orphaned or bereft of their caregivers. Such children often face adverse consequences, including poverty, abuse, and institutionalisation. We provide estimates for the magnitude of this problem resulting from COVID-19 and describe the need for resource allocation.

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Increasing reports of long-term symptoms following COVID-19 infection, even among mild cases, necessitates systematic investigation into the prevalence and type of lasting illness. Notably, there is limited data regarding the influence of social determinants of health, like perceived discrimination and economic stress, which may exacerbate COVID-19 health risks. The primary goals of this study are to test the bearing of subjective experiences of discrimination, financial security, and quality of care on illness severity and lasting symptom complaints.

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Functional connectivity (FC) networks are typically inferred from resting-state fMRI data using the Pearson correlation between BOLD time series from pairs of brain regions. However, alternative methods of estimating functional connectivity have not been systematically tested for their sensitivity or robustness to head motion artifact. Here, we evaluate the sensitivity of eight different functional connectivity measures to motion artifact using resting-state data from the Human Connectome Project. We report that FC estimated using full correlation has a relatively high residual distance-dependent relationship with motion compared to partial correlation, coherence, and information theory-based measures, even after implementing rigorous methods for motion artifact mitigation. This disadvantage of full correlation, however, may be offset by higher test-retest reliability, fingerprinting accuracy, and system identifiability. FC estimated by partial correlation offers the best of both worlds, with low sensitivity to motion artifact and intermediate system identifiability, with the caveat of low test-retest reliability and fingerprinting accuracy. We highlight spatial differences in the sub-networks affected by motion with different FC metrics. Further, we report that intra-network edges in the default mode and retrosplenial temporal sub-networks are highly correlated with motion in all FC methods. Our findings indicate that the method of estimating functional connectivity is an important consideration in resting-state fMRI studies and must be chosen carefully based on the parameters of the study.

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Though electrophysiological measures (EEG and ERP) offer complementary information to MRI and a variety of advantages for studying infants and young children, these measures have not yet been included in large cohort studies of neurodevelopment. This review summarizes the types of EEG and ERP measures that could be used in the HEALthy Brain and Cognitive Development (HBCD) study, and the promises and challenges in doing so. First, we provide brief overview of the use of EEG/ERP for studying the developing brain and discuss exemplar findings, using resting or baseline EEG measures as well as the ERP mismatch negativity (MMN) as exemplars. We then discuss the promises of EEG/ERP such as feasibility, while balancing challenges such as ensuring good signal quality in diverse children with different hair types. We then describe an ongoing multi-site EEG data harmonization from our groups. We discuss the process of alignment and provide preliminary usability data for both resting state EEG data and auditory ERP MMN in diverse samples including over 300 infants and toddlers. Finally, we provide recommendations and considerations for the HBCD study and other studies of neurodevelopment.

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The number of children with prenatal polysubstance exposure is increasing. Supportive mother-child interaction is a protective factor, which can ameliorate adverse effects of prenatal polysubstance exposure on developmental outcomes.

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The National Institutes of Health announced the Healthy Brain and Child Development (HBCD) study to further understanding of infant brain development. This study examined perceptions and knowledge about research among the demographic groups to be studied in HBCD.

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Studies reporting significant associations between maternal prenatal stress and child outcomes are frequently confounded by correlates of prenatal stress that influence the postnatal rearing environment. The major objective of this study is to identify whether maternal prenatal stress is associated with variation in human brain functional connectivity prior to birth. We utilized fetal fMRI in 118 fetuses [48 female; mean age 32.9 weeks (SD = 3.87)] to evaluate this association and further addressed whether fetal neural differences were related to maternal health behaviors, social support, or birth outcomes. Community detection was used to empirically define networks and enrichment was used to isolate differential within- or between-network connectivity effects. Significance for χ enrichment was determined by randomly permuting the subject pairing of fetal brain connectivity and maternal stress values 10,000 times. Mixtures modelling was used to test whether fetal neural differences were related to maternal health behaviors, social support, or birth outcomes. Increased maternal prenatal negative affect/stress was associated with alterations in fetal frontoparietal, striatal, and temporoparietal connectivity (β = 0.82, p < 0.001). Follow-up analysis demonstrated that these associations were stronger in women with better health behaviors, more positive interpersonal support, and lower overall stress (β = 0.16, p = 0.02). Additionally, magnitude of stress-related differences in neural connectivity was marginally correlated with younger gestational age at delivery (β = -0.18, p = 0.05). This is the first evidence that negative affect/stress during pregnancy is reflected in functional network differences in the human brain in utero, and also provides information about how positive interpersonal and health behaviors could mitigate prenatal brain programming.

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Different functional networks exhibit distinct longitudinal trajectories throughout development, but the timeline of the dynamics of functional connectivity across the whole brain remains to be elucidated. Here we used resting-state fMRI to investigate the development of voxel-level changes in functional connectivity across the first six years of life. Globally, we found that developmental changes in functional connectivity are nonlinear with more changes during the first postnatal year than the second, followed by most significant changes from ages 2-4 and from ages 4-6. However, the overall global difference observed between the first and second year appears to have been driven by girls. Limbic and subcortical areas consistently demonstrated the most substantial changes, whereas primary sensory areas were the most stable. These patterns were consistent in full-term and preterm subgroups. Validation on randomly divided subsamples as well as in an independent cross-sectional sample revealed global patterns consistent with the main results. Overall, the derived developmental heatmaps reveal novel dynamics underlying functional circuit development during the first 6 years of life.

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Exposure to adversity can accelerate biological aging. However, existing biomarkers of early aging are either costly and difficult to collect, like epigenetic signatures, or cannot be detected until late childhood, like pubertal onset. We evaluated the hypothesis that early adversity is associated with earlier molar eruption, an easily assessed measure that has been used to track the length of childhood across primates. In a preregistered analysis ( = 117, ages 4 to 7 y), we demonstrate that lower family income and exposure to adverse childhood experiences (ACEs) are significantly associated with earlier eruption of the first permanent molars, as rated in T2-weighted magnetic resonance images (MRI). We replicate relationships between income and molar eruption in a population-representative dataset (National Health and Nutrition Examination Survey; = 1,973). These findings suggest that the impact of stress on the pace of biological development is evident in early childhood, and detectable in the timing of molar eruption.

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The study examined whether mother-child reciprocity across increasingly challenging contexts moderated the association between household chaos and early childhood behavior problems.

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First-person accounts of COVID-19 illness and treatment complement and enrich data derived from electronic medical or public health records. With patient-reported data, it is uniquely possible to ascertain in-depth contextual information as well as behavioral and emotional responses to illness. The Novel Coronavirus Illness Patient Report (NCIPR) dataset includes complete survey responses from 1,592 confirmed COVID-19 patients ages 18 to 98. NCIPR survey questions address symptoms, medical complications, home and hospital treatments, lasting effects, anxiety about illness, employment impacts, quarantine behaviors, vaccine-related behaviors and effects, and illness of other family/household members. Additional questions address financial security, perceived discrimination, pandemic impacts (relationship, social, stress, sleep), health history, and coping strategies. Detailed patient reports of illness, environment, and psychosocial impact, proximal to timing of infection and considerate of demographic variation, is meaningful for understanding pandemic-related public health from the perspective of those that contracted the disease.

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Deep networks are now ubiquitous in large-scale multi-center imaging studies. However, the direct aggregation of images across sites is contraindicated for downstream statistical and deep learning-based image analysis due to inconsistent contrast, resolution, and noise. To this end, in the absence of paired data, variations of Cycle-consistent Generative Adversarial Networks have been used to harmonize image sets between a source and target domain. Importantly, these methods are prone to instability, contrast inversion, intractable manipulation of pathology, and steganographic mappings which limit their reliable adoption in real-world medical imaging. In this work, based on an underlying assumption that morphological shape is consistent across imaging sites, we propose a segmentation-renormalized image translation framework to reduce inter-scanner heterogeneity while preserving anatomical layout. We replace the affine transformations used in the normalization layers within generative networks with trainable scale and shift parameters conditioned on jointly learned anatomical segmentation embeddings to modulate features at every level of translation. We evaluate our methodologies against recent baselines across several imaging modalities (T1w MRI, FLAIR MRI, and OCT) on datasets with and without lesions. Segmentation-renormalization for translation GANs yields superior image harmonization as quantified by Inception distances, demonstrates improved downstream utility via post-hoc segmentation accuracy, and improved robustness to translation perturbation and self-adversarial attacks.

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Recent studies indicate that sex-based differences exist in co-occurring psychiatric symptoms and disorders among individuals with opioid use disorders (OUD). Whether these associations are present in adolescent samples and change during OUD treatment is poorly understood.

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Understanding the impact of substance use during pregnancy on fetal development and child health is essential for designing effective approaches for reducing prenatal substance exposures and improving child outcomes. Research on the developmental impacts of prenatal substance exposure has been limited by legal, ethical, and practical challenges. This study examined approaches to engage substance-using (with an emphasis on opioids) pregnant persons in longitudinal research, from multi-stakeholder perspectives.

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We design a framework for studying prelinguistic child voice from 3 to 24 months based on state-of-the-art algorithms in diarization. Our system consists of a time-invariant feature extractor, a context-dependent embedding generator, and a classifier. We study the effect of swapping out different components of the system, as well as changing loss function, to find the best performance. We also present a multiple-instance learning technique that allows us to pre-train our parameters on larger datasets with coarser segment boundary labels. We found that our best system achieved 43.8% DER on test dataset, compared to 55.4% DER achieved by LENA software. We also found that using convolutional feature extractor instead of logmel features significantly increases the performance of neural diarization.

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Black Americans have vastly increased odds and earlier onsets of stress- and age-related disease compared to White Americans. However, what contributes to these racial health disparities remains poorly understood. Using a sample of 1577 older adults (32.7% Black; ages 55-65 at baseline), we examined whether stress, health behaviors, social isolation, and inflammation are associated with racial disparities in self-reported physical health. A latent cumulative stress factor and unique stress-domain specific factors were modeled by applying bifactor confirmatory analysis to assessments across the lifespan (i.e., childhood maltreatment, trauma exposure, discrimination, stressful life events, and indices of socioeconomic status). Physical health, health behavior, and social isolation were assessed using self-report. Interleukin-6 (IL-6) and C-reactive protein (CRP) were assayed from morning fasting serum samples; a z-scored inflammation index was formed across these 2 cytokines. A parallel serial mediational model tested whether race (i.e., Black/White) is indirectly associated with health through the following 3 independent pathways: (1) cumulative stress to preventative health behaviors (e.g., healthy eating) to inflammation, (2) cumulative stress to risky health behaviors (e.g., substance use) to inflammation; and (3) cumulative stress to social isolation to inflammation. There were significant indirect effects between race and self-reported physical health through cumulative stress, preventative health behaviors, and inflammation (B = -0.02, 95% CI: -0.05, -0.01). Specifically, Black Americans were exposed to greater cumulative stress, which was associated with reduced engagement in preventative health behaviors, which was, in turn, associated with greater inflammation and reduced physical health. A unique SES factor also indirectly linked race to physical health through preventative health behaviors. Cumulative stress exposure and unique aspects of socioeconomic status are indirectly associated with Black-White racial health disparities through behavioral (i.e., preventative health behavior) and biological (i.e., inflammation) factors. Culturally responsive evidence-based interventions that enhance engagement in preventative health behaviors are needed to directly confront health disparities. Ultimately, large scale anti-racist public policies that reduce cumulative stress burden (e.g., a living wage, universal healthcare) may best attenuate racial health disparities.

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Maternal smoking is a well-known risk factor for youth smoking, yet whether this relationship is causal remains unresolved. This study utilizes propensity score methods for causal inference to robustly account for shared risk factors between maternal and offspring smoking.

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Numerous developmental scholars have been influenced by the research, policies, and thinking of the late Edward Zigler, who was instrumental in founding Head Start and Early Head Start. In line with the research and advocacy work of Zigler, we discuss two models that support the development of the whole child. We begin by reviewing how adverse and protective experiences “get under the skin” and affect developmental trajectories and risk and resilience processes. We then present research and examples of how experiences affect the whole child, the heart and the head (social, emotional, cognitive, and physical development), and consider development within context and across domains. We discuss examples of interventions that strengthen nurturing relationships as the mechanism of change. We offer a public health perspective on promoting optimal development through nurturing relationships and access to resources during early childhood. We end with a discussion of the myth that our current society is child-focused and argue for radical, essential change to make promoting optimal development for all children the cornerstone of our society.

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Childhood socio-economic status (SES), a measure of the availability of material and social resources, is one of the strongest predictors of lifelong well-being. Here we review evidence that experiences associated with childhood SES affect not only the outcome but also the pace of brain development. We argue that higher childhood SES is associated with protracted structural brain development and a prolonged trajectory of functional network segregation, ultimately leading to more efficient cortical networks in adulthood. We hypothesize that greater exposure to chronic stress accelerates brain maturation, whereas greater access to novel positive experiences decelerates maturation. We discuss the impact of variation in the pace of brain development on plasticity and learning. We provide a generative theoretical framework to catalyse future basic science and translational research on environmental influences on brain development.

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The opioid epidemic in the United States has led to a significant increase in the incidence of neonatal opioid withdrawal syndrome (NOWS); however, the understanding of long-term consequences of NOWS is limited. The objective of this study was to evaluate post-discharge healthcare utilization in infants with NOWS and examine the association between NOWS severity and healthcare utilization. A retrospective cohort design was used to ascertain healthcare utilization in the first year after birth-related discharge using the CERNER Health Facts® database. ICD-9/ICD-10 diagnostic codes were used to identify live births and to classify infants into two study groups: NOWS and uncomplicated births (a 25% random sample). Evaluated outcomes included rehospitalization, emergency department (ED) visits within 30-days and one-year after discharge, and a composite one-year utilization event (either hospitalization or emergency department visit during that year). NOWS severity was operationalized as pharmacologic treatment, length of hospitalization, and medical conditions often associated with NOWS. In 3,526 infants with NOWS (restricted to gestational age ≥ 33 weeks), NOWS severity was associated with an increase in composite one-year utilization (OR: 1.1; 95% CI: 1.04-1.2) after adjusting for prematurity, sepsis, jaundice, use of antibiotics, infant sex, insurance status, race, hospital bed size, year of birth, and census division. In a subset of full-term infants (3008 with NOWS and 88,452 uncomplicated births), having a NOWS diagnosis was associated with higher odds of a 30-day (OR: 1.6; 95% CI: 1.03-2.4) and one-year rehospitalization (OR: 1.6; 95% CI: 1.1-2.4) after adjusting for infant sex, race, type of medical insurance, hospital location, census division, year of primary encounter, hospital bed size, and medical conditions. This study found higher healthcare utilization during the first year of life in infants diagnosed with NOWS, especially those with severe NOWS. Findings suggest a need for closer post-discharge follow-up and management of infants with NOWS.

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Longitudinal cohort studies present unique methodological challenges, especially when they focus on vulnerable populations, such as pregnant women. The purpose of this review is to synthesize the existing knowledge on recruitment and retention (RR) of pregnant women in birth cohort studies and to make recommendations for researchers to improve research engagement of this population. A scoping review and content analysis were conducted to identify facilitators and barriers to the RR of pregnant women in cohort studies. The search retrieved 574 articles, with 38 meeting eligibility criteria and focused on RR among English-speaking, adult women, who are pregnant or in early postpartum period, enrolled in birth cohort studies. Selected studies were birth cohort (including longitudinal) (n = 20), feasibility (n = 14), and other (n = 4) non-interventional study designs. The majority were from low-risk populations. Abstracted data were coded according to emergent theme clusters. The majority of abstracted data (79%) focused on recruitment practices, with only 21% addressing retention strategies. Overall, facilitators were reported more often (75%) than barriers (25%). Building trusting relationships and employing diverse recruitment methods emerged as major recruitment facilitators; major barriers included heterogeneous participant reasons for refusal and cultural factors. Key retention facilitators included flexibility with scheduling, frequent communication, and culturally sensitive practices, whereas participant factors such as loss of interest, pregnancy loss, relocation, multiple caregiver shifts, and substance use/psychiatric problems were cited as major barriers. Better understanding of facilitators and barriers of RR can help enhance the internal and external validity of future birth/pre-birth cohorts. Strategies presented in this review can help inform investigators and funding agencies of best practices for RR of pregnant women in longitudinal studies.

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Two of the most commonly used illegal substances by adolescents are alcohol and cannabis. Alcohol use disorder (AUD) and cannabis use disorder (CUD) are associated with poorer decision-making in adolescents. In adolescents, level of AUD symptomatology has been negatively associated with striatal reward responsivity. However, little work has explored the relationship with striatal reward prediction error (RPE) representation and the extent to which any augmentation of RPE by novel stimuli is impacted. One-hundred fifty-one adolescents participated in the Novelty Task while undergoing functional magnetic resonance imaging (fMRI). In this task, participants learn to choose novel or non-novel stimuli to gain monetary reward. Level of AUD symptomatology was negatively associated with both optimal decision-making and BOLD response modulation by RPE within striatum and regions of prefrontal cortex. The neural alterations in RPE representation were particularly pronounced when participants were exploring novel stimuli. Level of CUD symptomatology moderated the relationship between novelty propensity and RPE representation within inferior parietal lobule and dorsomedial prefrontal cortex. These data expand on an emerging literature investigating individual associations of AUD symptomatology levels versus CUD symptomatology levels and RPE representation during reinforcement processing and provide insight on the role of neuro-computational processes underlying reinforcement learning/decision-making in adolescents.

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Early adversity influences brain development and emerging behavioral phenotypes relevant for psychiatric disorders. Understanding the effects of adversity before and after conception on brain development has implications for contextualizing current public health crises and pervasive health inequities. The use of functional magnetic resonance imaging (fMRI) to study the brain at rest has shifted understanding of brain functioning and organization in the earliest periods of life. Here we review applications of this technique to examine effects of early life stress (ELS) on neurodevelopment in infancy, and highlight targets for future research. Building on the foundation of existing work in this area will require tackling significant challenges, including greater inclusion of often marginalized segments of society, and conducting larger, properly powered studies.

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The hippocampus is a key limbic region involved in higher-order cognitive processes including learning and memory. Although both typical and atypical functional connectivity patterns of the hippocampus have been well-studied in adults, the developmental trajectory of hippocampal connectivity during infancy and how it relates to later working memory performance remains to be elucidated. Here we used resting state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of hippocampal functional connectivity using a large cohort (N = 202) of infants at 3 weeks (neonate), 1 year, and 2 years of age. Next, we used multivariate modeling to investigate the relationship between both cross-sectional and longitudinal growth in hippocampal connectivity and 4-year working memory outcome. Results showed robust local functional connectivity of the hippocampus in neonates with nearby limbic and subcortical regions, with dramatic maturation and increasing connectivity with key default mode network (DMN) regions resulting in adult-like topology of the hippocampal functional connectivity by the end of the first year. This pattern was stabilized and further consolidated by 2 years of age. Importantly, cross-sectional and longitudinal measures of hippocampal connectivity in the first year predicted subsequent behavioral measures of working memory at 4 years of age. Taken together, our findings provide insight into the development of hippocampal functional circuits underlying working memory during this early critical period.

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Accurate characterization of prenatal alcohol exposure (PAE) is challenging due to inconsistent use of screening questionnaires in routine prenatal care and substantial underreporting due to stigma associated with alcohol use in pregnancy. The aim of this study was to identify self-report tools that are efficient in accurately characterizing PAE.

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This article proposes a model for understanding the effects of adverse childhood experiences (ACEs) as dynamic and interrelated biobehavioral adaptations to early life stress that have predictable consequences on development and health. Drawing upon research from multiple theoretical and methodological approaches, the intergenerational and cumulative adverse and resilient experiences (ICARE) model posits that the negative consequences of ACEs result from biological and behavioral adaptations to adversity that alter cognitive, social, and emotional development. These adaptations often have negative consequences in adulthood and may be transmitted to subsequent generations through epigenetic changes as well as behavioral and environmental pathways. The ICARE model also incorporates decades of resilience research documenting the power of protective relationships and contextual resources in mitigating the effects of ACEs. Examples of interventions are provided that illustrate the importance of targeting the dysregulated biobehavioral adaptations to ACEs and developmental impairments as well as resulting problem behaviors and health conditions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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The way we communicate about addiction, its treatment, and treatment outcomes matters to individuals affected by addiction, their families, and communities. Stigmatizing language can worsen addiction-related stigma and outcomes. Although non-professional terminology may be used by individuals with addiction, the role of clinicians, educators, researchers, policymakers, and community and cultural leaders is to actively work toward destigmatization of addiction and its treatment, in part through the use of non-stigmatizing language. Role-modeling better approaches can help us move away from the inaccurate, outdated view of addiction as a character flaw or moral failing deserving of punishment, and toward that of a chronic disease requiring long-term treatment. Non-stigmatizing, non-judgmental, medically-based terminology and the adoption of person-first language can facilitate improved communication as well as patient access to and engagement with addiction care. Person-first language, which shifts away from defining a person through the lens of disease (eg, the term “a person with addiction” is recommended over the terms “addict” or “addicted patient”), implicitly acknowledges that a patient’s life extends beyond a given disease. While such linguistic changes may seem subtle, they communicate that addiction, chronic pain and other diseases are only one aspect of a person’s health and quality of life, and can promote therapeutic relationships, reduce stigma and health and disparities in addiction care. This article provides examples of stigmatizing terms to be avoided and recommended replacements to facilitate the dialogue about addiction in a more intentional, therapeutic manner.

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The presence of heterogeneity/subgroups in infants and older populations against single-domain brain or behavioral measures has been previously characterized. However, few attempts have been made to explore heterogeneity at the brain-behavior relationship level. Such a hypothesis posits that different subgroups of infants may possess qualitatively different brain-behavior relationships that could ultimately contribute to divergent developmental outcomes even with relatively similar brain phenotypes. In this study, we aimed to explore such relationship-level heterogeneity and delineate the subgrouping structure of newborns with differential brain-behavior associations based on a typically developing sample of 81 infants with 3-week resting-state functional magnetic resonance imaging scans and 4-year intelligence quotient (IQ) measures. Our results not only confirmed the existence of relationship-level heterogeneity in newborns but also revealed divergent developmental outcomes associated with two subgroups showing similar brain functional connectivity but contrasting brain-behavior relationships. Importantly, further analyses unveiled an intriguing pattern that the subgroup with higher 4-year IQ outcomes possessed brain-behavior relationships that were congruent to their functional connectivity pattern in neonates while the subgroup with lower 4-year IQ not, providing potential explanations for the observed IQ differences. The characterization of heterogeneity at the brain-behavior relationship level may not only improve our understanding of the patterned intersubject variability during infancy but could also pave the way for future development of heterogeneity-inspired, personalized, subgroup-specific models for better prediction.

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The use of opioids for the treatment of pain is a risk versus benefit analysis and metabolic disease is an often overlooked variable in the equation and may lead to increased risk of comorbidities of cardiovascular and cerebrovascular disease and diabetes.

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Early life stress increases risk for later psychopathology, due in part to changes in dopaminergic brain systems that support reward processing and motivation. Work in animals has shown that early life stress has a profound impact on the ventral tegmental area (VTA), which provides dopamine to regions including nucleus accumbens (NAcc), anterior hippocampus, and medial prefrontal cortex (mPFC), with cascading effects over the course of development. However, little is known about how early stress exposure shifts the developmental trajectory of mesocorticolimbic circuitry in humans. In the current study, 88 four- to nine-year-old children participated in resting-state fMRI. Parents completed questionnaires on their children’s chronic stress exposure, including socioeconomic status (SES) and adverse childhood experiences (ACEs). We found an age x SES interaction on VTA connectivity, such that children from higher SES backgrounds showed a positive relationship between age and VTA-mPFC connectivity. Similarly, we found an age x ACEs exposure interaction on VTA connectivity, such that children with no ACEs exposure showed a positive relationship between age and VTA-mPFC connectivity. Our findings suggest that early stress exposure relates to the blunted maturation of VTA connectivity in young children, which may lead to disrupted reward processing later in childhood and beyond.

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Alcohol and cannabis are commonly used by adolescents in the United States. Both alcohol use disorder (AUD) and cannabis use disorder (CUD) have been associated with an increased risk of aggression. One form of aggression seen during retaliation is reactive aggression to social provocation. This study investigated the association between AUD and CUD symptom severity and recruitment of neural regions implicated in retaliation.

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To examine associations between amounts of fatty acid ethyl esters (FAEEs) in meconium and behavior in school aged children exposed to alcohol and drugs in utero.

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The vast individual differences in the developmental origins of risk and resilience pathways combined with sophisticated capabilities of big data science increasingly point to the imperative of large, neurodevelopmental consortia to capture population heterogeneity and key variations in developmental trajectories. At the same time, such large-scale population-based designs involving multiple independent sites also must weigh competing demands. For example, the need for efficient, scalable assessment strategies must be balanced with the need for nuanced, developmentally sensitive phenotyping optimized for linkage to neural mechanisms and specification of common and distinct exposure pathways. Standardized epidemiologic batteries designed for this purpose such as PhenX (consensus measures for types and eposures) and the National Institutes of Health (NIH) Toolbox provide excellent “off the shelf” assessment tools that are well-validated and enable cross-study comparability. However, these standardized toolkits can also constrain ability to leverage advances in neurodevelopmental measurement over time, at times disproportionately advantaging established measures. In addition, individual consortia often expend exhaustive effort “reinventing the wheel,” which is inefficient and fails to fully maximize potential synergies with other like initiatives. To address these issues, this paper lays forth an early childhood neurodevelopmental assessment strategy, guided by a set of principles synthesizing developmental and pragmatic considerations generated by the Neurodevelopmental Workgroup of the HEALthy Brain and Child Development (HBCD) Planning Consortium. These principles emphasize characterization of both risk- and resilience-promoting processes. Specific measurement recommendations to HBCD are provided to illustrate application. However, principles are intended as a guiding framework to transcend any particular initiative as a broad neurodevelopmentally informed, early childhood assessment strategy for large-scale consortia science.

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The speed and scale of the COVID-19 pandemic has highlighted the limits of current health systems and the potential promise of non-establishment research such as “DIY” research. We consider one example of how DIY research is responding to the pandemic, discuss the challenges faced by DIY research more generally, and suggest that a “trust architecture” should be developed now to contribute to successful future DIY efforts.

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There are significant barriers in engaging pregnant and postpartum women that are considered high-risk (e.g., those experiencing substance use and/or substance use disorders (SUD)) into longitudinal research studies. To improve recruitment and retention of this population in studies spanning from the prenatal period to middle childhood, it is imperative to determine ways to improve key research engagement factors. The current manuscript uses a qualitative approach to determine important factors related to recruiting, enrolling, and retaining high-risk pregnant and postpartum women. The current sample included 41 high-risk women who participated in focus groups or individual interviews. All interviews were analyzed to identify broad themes related to engaging high-risk pregnant and parenting women in a 10-year longitudinal research project. Themes were organized into key engagement factors related to the following: (1) recruitment strategies, (2) enrollment, and (3) retention of high-risk pregnant and parenting women in longitudinal research studies. Results indicated recruitment strategies related to ideal recruitment locations, material, and who should share research study information with high-risk participants. Related to enrollment, key areas disclosed focused on enrollment decision-making, factors that create interest in joining a research project, and barriers to joining a longitudinal research study. With regard to retention, themes focused on supports needed to stay in research, barriers to staying in research, and best ways to stay in contact with high-risk participants. Overall, the current qualitative data provide preliminary data that enhance the understanding of a continuum of factors that impact engagement of high-risk pregnant and postpartum women in longitudinal research with current results indicating the need to prioritize recruitment, enrollment, and retention strategies in order to effectively engage vulnerable populations in research.

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Current efforts to design research on developmental effects of prenatal opioid exposure can benefit from knowledge gained from 50 years of studies of fetal alcohol and prenatal drug exposures such as cocaine. Scientific advances in neurobiology, developmental psychopathology, infant assessments, genetics, and imaging support the principles of developmental neurotoxicology that guide research in prenatal exposures. Important to research design is accurate assessment of amount, frequency, and timing of exposure which benefits from accurate self-report and biomarkers of exposure. Identifying and control of pre- and postnatal factors that impact development are difficult and dependent on appropriate research design and selection of comparison groups and measurement of confounding, mediating, and moderating variables. Polysubstance exposure has increased due to the number of prescribed and nonprescribed substances used by pregnant women and varying combinations of drugs may have differential effects on the outcome. Multiple experimental and clinical assessments of infant behavior have been developed but predicting outcome before 18-24 months of age remains difficult. With some exceptions, prenatal substance exposure effect sizes have been small, and cognitive and behavioral effects tend to be specific rather than global. Studies require large sample sizes, adequate retention, and support for social services in at-risk samples. The ethical and legal contexts and stigma associated with drug/alcohol use disorder should be considered in order to prevent harm to families in research programs. Recognition of the pervasive use of addictive substances in this nation should lead to broad scientific efforts to understand how substances affect child outcomes and to initiate prevention and intervention where needed.

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This manuscript is the result of an interdisciplinary team approach to examine the ethical and cultural considerations of biospecimen collection among American Indian and Alaskan Native (AIAN) communities for the planned Healthy Brain and Child Development (HBCD) study. We begin by reviewing a brief history of the treatment of AIAN communities by the US government and within research studies. Based in part on this history, we highlight the overlapping and intersecting vulnerabilities of AIAN communities, including historical trauma, poverty, lack of healthcare access, and environmental hazards. After consideration of ethical and legal implications, we introduce our recommendations for biospecimen collection/biobanking with AIAN communities in the context of population-representative, multi-site, national studies. We recommend the following key considerations: (1) authentic partnership development; (2) beneficence to the community; (3) culturally respectful research design; (4) meaningful consent to support enrollment and retention; (5) culturally appropriate data management. Adherence to a culturally aware approach for inclusion of underrepresented communities assures external validity in the national studies and increases likelihood of bidirectional value exchange.

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Defining reliable brain markers for the prediction of abnormal behavioral outcomes remains an urgent but extremely challenging task in neuroscience research. This is particularly important for infant studies given the most dramatic brain and behavioral growth during infancy.

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Prenatal drug exposure (PDE) is known to affect fetal brain development with documented long-term consequences. Most studies of PDE effects on the brain are based on animal models. In this study, based on a large sample of 133 human neonates and leveraging a novel linear mixed-effect model designed for intersubject variability analyses, we studied the effects of six prenatally exposed drugs (i.e., nicotine, alcohol, selective serotonin reuptake inhibitor, marijuana, cocaine, and opioids) on neonatal whole-brain functional organization and compared them with five other critical nondrug variables (i.e., gestational age at birth/scan, sex, birth weight, and maternal depression). The behavioral implications were also examined. Magnitude-wise, through summing across individual drug effects, our results highlighted ~5% of whole-brain functional connections (FCs) affected by PDE, which was highly comparable with the combined effects of the five nond rug variables. Spatially, the detected PDE effects featured drug-specific patterns with a common bias in higher-order brain regions/networks. Regarding brain-behavioral relationships, the detected connections showing significant drug effects also demonstrated significant correlations with 3-month behavioral outcomes. Further mediation analyses supported a mediation role of the detected brain FCs between PDE status and cognitive/language outcomes. Our findings of widespread, and spatially biased PDE effect patterns coupled with significant behavioral implications may hopefully stimulate more human-based studies into effects of PDE on long-term developmental outcomes.

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Prenatal development is a time when the brain is acutely vulnerable to insult and alteration by environmental factors (e.g., toxins, maternal health). One important risk factor is maternal obesity (Body Mass Index > 30). Recent research indicates that high maternal BMI during pregnancy is associated with increased risk for numerous physical health, cognitive, and mental health problems in offspring across the lifespan. It is possible that heightened maternal prenatal BMI influences the developing brain even before birth.

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Infants with prenatal substance exposure are at increased risk for developmental problems, with self-regulatory challenges being some of the most pronounced. The current study aimed to investigate the extent to which prenatal substance exposure (alcohol, opioids) impacts infant self-regulation during a relational stressor and the association between self-regulation and infant affect.

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To test the performance of the MPnRAGE motion-correction algorithm on quantitative relaxometry estimates.

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Two of the most commonly used substances by adolescents in the United States are cannabis and alcohol. Cannabis use disorder (CUD) and alcohol use disorder (AUD) are associated with impairments in decision-making processes. One mechanism for impaired decision-making in these individuals is thought to be an inability to adequately represent future events during decision-making. In the current study involving 112 adolescents, we used a comparative optimism task to examine the relationship between relative severity of CUD/AUD (as indexed by the CUD/AUD Identification Tests [CUDIT/AUDIT]) and atypical function within neural systems underlying affect-based neural represenation future events. Greater CUDIT scores were negatively related to responses within subgenual anterior and posterior cingulate cortex when processing high-intensity potential future positive and negative events. There was also a particularly marked negative relationship between CUD symptoms and blood oxygen level-dependent (BOLD) responses within visual and premotor cortices to high-intensity, negatively valenced potential future events. However, AUD symptom severity was not associated with dysfunction within these brain regions. These data indicate that relative risk/severity of CUD is associated with reduced responsiveness to future high-intensity events. This may impair decision-making where future significant consequences should guide response choice.

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The two most commonly used illegal substances by adolescents in the United States are alcohol and cannabis. Alcohol use disorder (AUD) and cannabis use disorder (CUD) have been associated with dysfunction in decision-making processes in adolescents. One potential mechanism for these impairments is thought to be related to abnormalities in reward and punishment processing. However, very little work has directly examined potential differential relationships between AUD and CUD symptom severity and neural dysfunction during decision making in adolescents.

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Magnetic resonance imaging, histological, and gene analysis approaches in living and nonliving human fetuses and in prematurely born neonates have provided insight into the staged processes of prenatal brain development. Increased understanding of micro- and macroscale brain network development before birth has spurred interest in understanding the relevance of prenatal brain development to common neurological diseases. Questions abound as to the sensitivity of the intrauterine brain to environmental programming, to windows of plasticity, and to the prenatal origin of disorders of childhood that involve disruptions in large-scale network connectivity. Much of the available literature on human prenatal neural development comes from cross-sectional or case studies that are not able to resolve the longitudinal consequences of individual variation in brain development before birth. This review will 1) detail specific methodologies for studying the human prenatal brain, 2) summarize large-scale human prenatal neural network development, integrating findings from across a variety of experimental approaches, 3) explore the plasticity of the early developing brain as well as potential sex differences in prenatal susceptibility, and 4) evaluate opportunities to link specific prenatal brain developmental processes to the forms of aberrant neural connectivity that underlie common neurological disorders of childhood.

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This review examines how research focused on treatment for opioid use in perinatal populations and preventive interventions for postpartum psychopathology have remained separate, despite significant overlap.

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Test-retest of automated image segmentation algorithms (FSL FAST, FSL FIRST, and FREESURFER) are computed on magnetic resonance images from 12 unsedated children aged 9.4±2.6 years ([min,max] ​= ​[6.5 years, 13.8 years]) using different approaches to motion correction (prospective versus retrospective). The prospective technique, PROMO MPRAGE, dynamically estimates motion using specially acquired navigator images and adjusts the remaining acquisition accordingly, whereas the retrospective technique, MPnRAGE, uses a self-navigation property to retrospectively estimate and account for motion during image reconstruction. To increase the likelihood and range of motions, participants heads were not stabilized with padding during repeated scans. When motion was negligible both techniques had similar performance. When motion was not negligible, the automated image segmentation and anatomical labeling software tools showed the most consistent performance with the retrospectively corrected MPnRAGE technique (≥80% volume overlaps for 15 of 16 regions for FIRST and FREESURFER, with greater than 90% volume overlaps for 12 regions with FIRST and 11 regions with FREESURFER). Prospectively corrected MPRAGE with linear view-ordering also demonstrated lower performance than MPnRAGE without retrospective motion correction.

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Large-scale functional connectome formation and reorganization is apparent in the second trimester of pregnancy, making it a crucial and vulnerable time window in connectome development. Here we identified which architectural principles of functional connectome organization are initiated before birth, and contrast those with topological characteristics observed in the mature adult brain. A sample of 105 pregnant women participated in human fetal resting-state fMRI studies (fetal gestational age between 20 and 40 weeks). Connectome analysis was used to analyze weighted network characteristics of fetal macroscale brain wiring. We identified efficient network attributes, common functional modules, and high overlap between the fetal and adult brain network. Our results indicate that key features of the functional connectome are present in the second and third trimesters of pregnancy. Understanding the organizational principles of fetal connectome organization may bring opportunities to develop markers for early detection of alterations of brain function. The fetal to neonatal period is well known as a critical stage in brain development. Rapid neurodevelopmental processes establish key functional neural circuits of the human brain. Prenatal risk factors may interfere with early trajectories of connectome formation and thereby shape future health outcomes. Recent advances in MRI have made it possible to examine fetal brain functional connectivity. In this study, we evaluate the network topography of normative functional network development during connectome genesis Understanding the developmental trajectory of brain connectivity provides a basis for understanding how the prenatal period shapes future brain function and disease dysfunction.

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This study describes maternal and infant contributions to dyadic affective exchanges during the Still-Face Paradigm (SFP) in an understudied mostly low-income sample. One hundred eleven mothers and their 7-month-old infants were videotaped during the SFP to analyze how a social stressor affects mother-infant positive and negative affective exchanges during interaction. The SFP includes 3 episodes: baseline, maternal still-face, and reunion. Maternal and infant positive and negative affect were scored by masked reliable coders. Data were analyzed using the Actor-Partner Interdependence Model to test the hypotheses that each partner’s affectivity during the baseline episode would predict their own affectivity during the reunion episode (actor effects). We also expected that each partner’s affectivity during the baseline episode would influence the other partner’s affectivity during the reunion episodes (partner effects). After controlling for infant sex and maternal education, results provided evidence for actor effects for maternal and infant positive affect, and for partner effects for maternal baseline positive affect to infant positive affect during the reunion. One significant partner effect was observed for negative affect: Infant negativity during baseline predicted greater maternal negativity during reunion. Findings confirm that both mothers and infants contribute to dyadic affective processes during the SFP but specific findings vary depending on the affective valence in question. Clinical implications and future research are discussed.

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Childhood trauma is associated with many long-term negative outcomes, and is not limited to the individual experiencing the trauma, but extends to subsequent generations. However, mechanisms underlying the association between maternal childhood trauma and child psychopathology are not well understood. Here, we targeted frontal alpha asymmetry (FAA) as a potential underlying factor of the relationship between maternal childhood trauma and child behavioral problems. Electroencephalography (EEG) was recorded from (N = 45) children (Mean age = 57.9 months, SD = 3.13) during an eyes-closed paradigm in order to evaluate FAA. Mothers reported on their childhood trauma experiences using the Childhood Trauma Questionnaire (CTQ), and on their child’s behavior using the child behavior checklist (CBCL). We found that maternal childhood trauma significantly predicted child total, internalizing, and externalizing behavior at age 5 years. We also observed a role for FAA such that it acted as a moderator, but not mediator, for behavioral problems. We found that children with relative more right/less left frontal activity were more at risk to develop behavioral problems when their mother had been exposed to trauma in her childhood. These results indicate that child frontal asymmetry may serve as a susceptibility marker for child behavioral problems.

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The developmental impact of opioid use during pregnancy is a subject of ongoing debate. Short-term neonatal outcomes, such as lower birth weight and neonatal abstinence syndrome, are the most well-recognized outcomes. However, knowledge gaps exist regarding longer-term neurocognitive and mental health outcomes. In this article, we summarize an expert panel discussion that was held in April 2018 by the Substance Abuse and Mental Health Services Administration and attended by national experts in the field of perinatal opioid exposure and its impact on child development. Despite the challenges with research in this area, there is emerging literature revealing an association between neonates exposed to opioids in utero and longer-term adverse neurocognitive, behavioral, and developmental outcomes. Although adverse sequalae may not be apparent in the neonatal period, they may become more salient as children develop and reach preschool and school age. Multiple variables (genetic, environmental, and biological) result in a highly complex picture. The next steps and strategies to support families impacted by opioid use disorder are explored. Model programs are also considered, including integrated care for the child and mother, parenting supports, and augmentations to home visiting.

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Despite the proliferation of fentanyl and fentanyl-adulterated opioids in North America, the impacts of this drug market change on injection initiation processes have not been examined. With the aim of informing structural interventions to address injection initiation and related harms, we explore how people who inject drugs (PWID) in Vancouver, Canada understand and navigate social norms of initiating others into injecting within the context of an overdose crisis. In-depth qualitative interviews were conducted with 19 PWID who reported helping someone inject for the first time. Participants were recruited from two cohort studies of PWID. Participants articulated moral dilemmas about assisting others with injecting. While participants described a ‘moral code’ prohibiting assisting injection-naïve individuals, this code was not the sole consideration shaping social action around injection initiation. Rather, PWID exercised agency about whether and how to assist novice injectors within the context of constraining and enabling social norms around practicing interpersonal responsibility. Changes to the drug market heightened feelings of moral culpability and criminal liability among PWID who assisted others into injection, given that injecting heightened initiates’ risk of overdose. These concerns operated in tension with the aim of protecting novice injectors from harms associated with an increasingly potent and unpredictable drug supply by providing them with injection assistance, education and supervision. Our analysis of how PWID practice interpersonal responsibility helps conceptualise how ‘moral codes’ prohibiting initiation assistance are managed and negotiated amidst structural vulnerability. Structural interventions reducing the vulnerability of novice injectors should be prioritized, including the implementation of supervised injection sites allowing for assisted injection, Good Samaritan laws, and policy changes conducive to a safer drug supply.

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Sex-related differences in brain and behavior are apparent across the life course, but the exact set of processes that guide their emergence in utero remains a topic of vigorous scientific inquiry. Here, we evaluate sex and gestational age (GA)-related change in functional connectivity (FC) within and between brain wide networks. Using resting-state functional magnetic resonance imaging we examined FC in 118 human fetuses between 25.9 and 39.6 weeks GA (70 male; 48 female). Infomap was applied to the functional connectome to identify discrete prenatal brain networks in utero. A consensus procedure produced an optimal model comprised of 16 distinct fetal neural networks distributed throughout the cortex and subcortical regions. We used enrichment analysis to assess network-level clustering of strong FC-GA correlations separately in each sex group, and to identify network pairs exhibiting distinct patterns of GA-related change in FC between males and females. We discovered both within and between network FC-GA associations that varied with sex. Specifically, associations between GA and posterior cingulate-temporal pole and fronto-cerebellar FC were observed in females only, whereas the association between GA and increased intracerebellar FC was stronger in males. These observations confirm that sexual dimorphism in functional brain systems emerges during human gestation.

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The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.

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