Felicia A. Hardi’s research while affiliated with University of Michigan and other places

Mother–child closeness, a mutually trusting and affectionate bond, is an important factor in shaping positive youth development. However, little is known about the neural pathways through which mother–child closeness is related to brain organization. Utilizing a longitudinal sample primarily from low-income families (N = 181; 76% African American youth and 54% female), this study investigated the associations between mother–child closeness at ages 9 and 15 years and structural connectivity organization (network integration, robustness, and segregation) at age 15 years. The assessment of mother–child closeness included perspectives from both mother and child. The results revealed that greater mother–child closeness is linked with increased global efficiency and transitivity, but not with modularity. Specifically, both the mother’s and child’s reports of closeness at age 15 years predicted network metrics, but report at age 9 years did not. Our findings suggest that mother–child closeness is associated with neural white matter organization, as adolescents who experienced greater mother–child closeness displayed topological properties indicative of more integrated and robust structural networks.

Importance Parenting is associated with brain development and long-term health outcomes, although whether these associations depend on the developmental timing of exposure remains understudied. Identifying these sensitive periods can inform when and how parenting is associated with neurodevelopment and risk for mental illness. Objective To characterize how harsh and warm parenting during early, middle, and late childhood are associated with brain architecture during adolescence and, in turn, psychiatric symptoms in early adulthood during the COVID-19 pandemic. Design, Setting, and Participants This population-based, 21-year observational, longitudinal birth cohort study of low-income youths and families from Detroit, Michigan; Toledo, Ohio; and Chicago, Illinois, used data from the Future of Families and Child Well-being Study. Data were collected from February 1998 to June 2021. Analyses were conducted from May to October 2023. Exposures Parent-reported harsh parenting (psychological aggression or physical aggression) and observer-rated warm parenting (responsiveness) at ages 3, 5, and 9 years. Main Outcomes and Measures The primary outcomes were brainwide (segregation, integration, and small-worldness), circuit (prefrontal cortex [PFC]–amygdala connectivity), and regional (betweenness centrality of amygdala and PFC) architecture at age 15 years, determined using functional magnetic resonance imaging, and youth-reported anxiety and depression symptoms at age 21 years. The structured life-course modeling approach was used to disentangle timing-dependent from cumulative associations between parenting and brain architecture. Results A total of 173 youths (mean [SD] age, 15.88 [0.53] years; 95 female [55%]) were included. Parental psychological aggression during early childhood was positively associated with brainwide segregation (β = 0.30; 95% CI, 0.14 to 0.45) and small-worldness (β = 0.17; 95% CI, 0.03 to 0.28), whereas parental psychological aggression during late childhood was negatively associated with PFC-amygdala connectivity (β = −0.37; 95% CI, −0.55 to −0.12). Warm parenting during middle childhood was positively associated with amygdala centrality (β = 0.23; 95% CI, 0.06 to 0.38) and negatively associated with PFC centrality (β = −0.18; 95% CI, −0.31 to −0.03). Warmer parenting during middle childhood was associated with reduced anxiety (β = −0.05; 95% CI −0.10 to −0.01) and depression (β = −0.05; 95% CI −0.10 to −0.003) during early adulthood via greater adolescent amygdala centrality. Conclusions and Relevance Neural associations with harsh parenting were widespread across the brain in early childhood but localized in late childhood. Neural associations with warm parenting were localized in middle childhood and, in turn, were associated with mental health during future stress. These developmentally contingent associations can inform the type and timing of interventions.

Associations between adversity and youth psychopathology likely vary based on the types and timing of experiences. Major theories suggest that the impact of childhood adversity may either be cumulative in type (the more types of adversity, the worse outcomes) or in timing (the longer exposure, the worse outcomes) or, alternatively, specific concerning the type (e.g., parenting, home, neighborhood) or the timing of adversity (e.g., specific developmental periods). In a longitudinal sample from the Future of Families and Wellbeing Study ( N = 4,210), we evaluated these competing hypotheses using a data-driven structured life-course modeling approach using risk factors examined at child age 1 (infancy), 3 (toddlerhood), 5 (early childhood), and 9 (middle childhood). Results showed that exposures to more types of adversity for longer durations (i.e., cumulative in both type and timing) best predicted youth psychopathology. Adversities that occurred at age 9 were better predictors of youth psychopathology as compared to those experienced earlier, except for neglect, which was predictive of internalizing symptoms when experienced at age 3. Throughout childhood (across ages 1–9), aside from the accumulation of all adversities, parental stress and low collective efficacy were the strongest predictors of internalizing symptoms, whereas psychological aggression was predictive of externalizing symptoms.

Importance Adverse childhood experiences are pervasive and heterogeneous, with potential lifelong consequences for psychiatric morbidity and brain health. Existing research does not capture the complex interplay of multiple adversities, resulting in a lack of precision in understanding their associations with neural function and mental health. Objectives To identify distinct childhood adversity profiles and examine their associations with adolescent mental health and brain connectivity. Design, Setting, and Participants This population-based birth cohort used data for children who were born in 20 large US cities between 1998 and 2000 and participated in the Future Families and Child Well-Being Study. Families were interviewed when children were born and at ages 1, 3, 5, 9, and 15 years. At age 15 years, neuroimaging data were collected from a subset of these youths. Data were collected from February 1998 to April 2017. Analyses were conducted from March to December 2023. Exposures Latent profiles of childhood adversity, defined by family and neighborhood risks across ages 0 to 9 years. Main Outcomes and Measures Internalizing and externalizing symptoms at age 15 years using parent- and youth-reported measures. Profile-specific functional magnetic resonance imaging connectivity across the default mode network (DMN), salience network (SN), and frontoparietal network (FPN). Results Data from 4210 individuals (2211 [52.5%] male; 1959 [46.5%] Black, 1169 [27.7%] Hispanic, and 786 [18.7%] White) revealed 4 childhood adversity profiles: low-adversity (1230 individuals [29.2%]), medium-adversity (1973 [46.9%]), high-adversity (457 [10.9%]), and high maternal depression (MD; 550 [13.1%]). High-adversity, followed by MD, profiles had the highest symptoms. Notably, internalizing symptoms did not differ between these 2 profiles (mean difference, 0.11; 95% CI, −0.03 to 0.26), despite the MD profile showing adversity levels most similar to the medium-adversity profile. In the neuroimaging subsample of 167 individuals (91 [54.5%] female; 128 [76.6%] Black, 11 [6.6%] Hispanic, and 20 [12.0%] White; mean [SD] age, 15.9 [0.5] years), high-adversity and MD profiles had the highest DMN density relative to other profiles ( F (3,163) = 11.14; P < .001). The high-adversity profile had lower SN density relative to the low-adversity profile (mean difference, −0.02; 95% CI, −0.04 to −0.003) and the highest FPN density among all profiles ( F (3,163) = 18.96; P < .001). These differences were specific to brain connectivity during an emotion task, but not at rest. Conclusions and Relevance In this cohort study, children who experienced multiple adversities, or only elevated MD, had worse mental health and different neural connectivity in adolescence. Interventions targeting multiple risk factors, with a focus on maternal mental health, could produce the greatest benefits.

Study Objectives Sleep disturbances are common in adolescence and associated with a host of negative outcomes. Here we assess associations between multifaceted sleep disturbances and a broad set of psychological, cognitive, and demographic variables using a data-driven approach, canonical correlation analysis (CCA). Methods Baseline data from 9,093 participants from the Adolescent Brain Cognitive Development℠ (ABCD) Study were examined using CCA, a multivariate statistical approach that identifies many-to-many associations between two sets of variables by finding combinations for each set of variables that maximize their correlation. We combined CCA with leave-one-site-out cross-validation across ABCD sites to examine the robustness of results and generalizability to new participants. The statistical significance of canonical correlations was determined by non-parametric permutation tests that accounted for twin, family, and site structure. To assess the stability of the associations identified at baseline, CCA was repeated using two-year follow-up data from 4,247 ABCD Study participants. Results Two significant sets of associations were identified: 1) difficulty initiating and maintaining sleep and excessive daytime somnolence were strongly linked to nearly all domains of psychopathology (r-squared = 0.36, p < .0001); 2) sleep breathing disorders were linked to BMI and African American/Black race (r-squared = 0.08, p < .0001). These associations generalized to unseen participants at all 22 ABCD sites and were replicated using two-year follow-up data. Conclusions These findings underscore interwoven links between sleep disturbances in early adolescence and psychological, social, and demographic factors.

Poverty is associated with changes in brain development and elevates the risk for psychopathology in childhood, adolescence, and adulthood. Although the field is rapidly expanding, there are methodological challenges that raise questions about the validity of current findings. These challenges include the interrelated issues of reliability, effect size, interindividual heterogeneity, and replicability. To address these issues, we propose a multipronged approach that spans short-, medium-, and long-term solutions, including changes to data pipelines along with more comprehensive data acquisition of environment, brain, and mental health. Additional suggestions are to use open science approaches, more robust statistical analyses, and replication testing. Furthermore, we propose increased integration between advanced analytical approaches using large samples and neuroscience models in intervention research to enhance the interpretability of findings. Collectively, these approaches will expand the application of neuroimaging findings and provide a foundation for eventual policy changes designed to improve conditions for children in poverty. Expected final online publication date for the Annual Review of Developmental Psychology, Volume 5 is December 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Unstable and unpredictable environments are linked to risk for psychopathology, but the underlying neural mechanisms that explain how instability relate to subsequent mental health concerns remain unclear. In particular, few studies have focused on the association between instability and white matter structures despite white matter playing a crucial role for neural development. In a longitudinal sample recruited from a population-based study (N = 237), household instability (residential moves, changes in household composition, caregiver transitions in the first 5 years) was examined in association with adolescent structural network organization (network integration, segregation, and robustness of white matter connectomes; Mage = 15.87) and young adulthood anxiety and depression (six years later). Results indicate that greater instability related to greater global network efficiency, and this association remained after accounting for other types of adversity (e.g., harsh parenting, neglect, food insecurity). Moreover, instability predicted increased depressive symptoms via increased network efficiency even after controlling for previous levels of symptoms. Exploratory analyses showed that structural connectivity involving the left fronto-lateral and temporal regions were most strongly related to instability. Findings suggest that structural network efficiency relating to household instability may be a neural mechanism of risk for later depression and highlight the ways in which instability modulates neural development.

Background Stressful events, such as the COVID‐19 pandemic, are major contributors to anxiety and depression, but only a subset of individuals develop psychopathology. In a population‐based sample (N = 174) with a high representation of marginalized individuals, this study examined adolescent functional network connectivity as a marker of susceptibility to anxiety and depression in the context of adverse experiences. Methods Data‐driven network‐based subgroups were identified using an unsupervised community detection algorithm within functional neural connectivity. Neuroimaging data collected during emotion processing (age 15) were extracted from a priori regions of interest linked to anxiety and depression. Symptoms were self‐reported at ages 15, 17, and 21 (during COVID‐19). During COVID‐19, participants reported on pandemic‐related economic adversity. Differences across subgroup networks were first examined, then subgroup membership and subgroup–adversity interaction were tested to predict change in symptoms over time. Results Two subgroups were identified: Subgroup A, characterized by relatively greater neural network variation (i.e., heterogeneity) and density with more connections involving the amygdala, subgenual cingulate, and ventral striatum; and the more homogenous Subgroup B, with more connections involving the insula and dorsal anterior cingulate. Accounting for initial symptoms, subgroup A individuals had greater increases in symptoms across time (β = .138, p = .042), and this result remained after adjusting for additional covariates (β = .194, p = .023). Furthermore, there was a subgroup–adversity interaction: compared with Subgroup B, Subgroup A reported greater anxiety during the pandemic in response to reported economic adversity (β = .307, p = .006), and this remained after accounting for initial symptoms and many covariates (β = .237, p = .021). Conclusions A subgrouping algorithm identified young adults who were susceptible to adversity using their personalized functional network profiles derived from a priori brain regions. These results highlight potential prospective neural signatures involving heterogeneous emotion networks that predict individuals at the greatest risk for anxiety when experiencing adverse events.

Increasing evidence demonstrates that environmental factors meaningfully impact the development of the brain (Hyde et al., 2020; McEwen and Akil, 2020). Recent work from the Adolescent Brain Cognitive Development (ABCD) Study® suggests that puberty may indirectly account for some association between the family environment and brain structure and function (Thijssen et al., 2020). However, a limited number of large studies have evaluated what, how, and why environmental factors impact neurodevelopment. When these topics are investigated, there is typically inconsistent operationalization of variables between studies which may be measuring different aspects of the environment and thus different associations in the analytic models. Multiverse analyses (Steegen et al., 2016) are an efficacious technique for investigating the effect of different operationalizations of the same construct on underlying interpretations. While one of the assets of Thijssen et al. (2020) was its large sample from the ABCD data, the authors used an early release that contained 38% of the full ABCD sample. Then, the analyses used several ‘researcher degrees of freedom’ (Gelman and Loken, 2014) to operationalize key independent, mediating and dependent variables, including but not limited to, the use of a latent factor of preadolescents' environment comprised of different subfactors, such as parental monitoring and child-reported family conflict. While latent factors can improve reliability of constructs, the nuances of each subfactor and measure that comprise the environment may be lost, making the latent factors difficult to interpret in the context of individual differences. This study extends the work of Thijssen et al. (2020) by evaluating the extent to which the analytic choices in their study affected their conclusions. In Aim 1, using the same variables and models, we replicate findings from the original study using the full sample in Release 3.0. Then, in Aim 2, using a multiverse analysis we extend findings by considering nine alternative operationalizations of family environment, three of puberty, and five of brain measures (total of 135 models) to evaluate the impact on conclusions from Aim 1. In these results, 90% of the directions of effects and 60% of the p-values (e.g. p > .05 and p < .05) across effects were comparable between the two studies. However, raters agreed that only 60% of the effects had replicated. Across the multiverse analyses, there was a degree of variability in beta estimates across the environmental variables, and lack of consensus between parent reported and child reported pubertal development for the indirect effects. This study demonstrates the challenge in defining which effects replicate, the nuance across environmental variables in the ABCD data, and the lack of consensus across parent and child reported puberty scales in youth.

Accumulating literature has linked poverty to brain structure and function, particularly in affective neural regions; however, few studies have examined associations with structural connections or the importance of developmental timing of exposure. Moreover, prior neuroimaging studies have not used a proximal measure of poverty (i.e., material hardship, which assesses food, housing, and medical insecurity) to capture the lived experience of growing up in harsh economic conditions. The present investigation addressed these gaps collectively by examining the associations between material hardship (ages 1, 3, 5, 9, and 15 years) and white matter connectivity of frontolimbic structures (age 15 years) in a low-income sample. We applied probabilistic tractography to diffusion imaging data collected from 194 adolescents. Results showed that material hardship related to amygdala–prefrontal, but not hippocampus–prefrontal or hippocampus–amygdala, white matter connectivity. Specifically, hardship during middle childhood (ages 5 and 9 years) was associated with greater connectivity between the amygdala and dorsomedial pFC, whereas hardship during adolescence (age 15 years) was related to reduced amygdala–orbitofrontal (OFC) and greater amygdala–subgenual ACC connectivity. Growth curve analyses showed that greater increases of hardship across time were associated with both greater (amygdala–subgenual ACC) and reduced (amygdala–OFC) white matter connectivity. Furthermore, these effects remained above and beyond other types of adversity, and greater hardship and decreased amygdala–OFC connectivity were related to increased anxiety and depressive symptoms. Results demonstrate that the associations between material hardship and white matter connections differ across key prefrontal regions and developmental periods, providing support for potential windows of plasticity for structural circuits that support emotion processing.