Longitudinal modeling in developmental neuroimaging research: Common challenges, and solutions from developmental psychology

Developmental trajectories of gyrification and sulcal morphometrics in children and adolescents at high familial risk for bipolar disorder or schizophrenia

Offspring of parents with severe mental illness are at increased risk of developing psychopathology. Identifying endophenotypic markers in high-familial-risk individuals can aid in early detection and inform development of prevention strategies. Using generalized additive mixed models, we compared age trajectories of gyrification index (GI) and sulcal morphometric measures (i.e., sulcal depth, length and width) between individuals at familial risk for bipolar disorder or schizophrenia and controls. 300 T1-weighted MRI scans were obtained of 187 individuals (53 % female, age range: 8-23 years) at familial risk for bipolar disorder (n = 80, n families=55) or schizophrenia (n = 53, n families=36) and controls (n = 54, n families=33). 113 individuals underwent two scans. Globally, GI, sulcal depth and sulcal length decreased significantly with age, and sulcal width increased significantly with age in a (near-)linear manner. There were no differences between groups in age trajectories or mean values of gyrification or any of the sulcal measures. These findings suggest that, on average, young individuals at familial risk for bipolar disorder or schizophrenia have preserved developmental patterns of gyrification and sulcal morphometrics during childhood and adolescence.

Longitudinal analysis of the ABCD® study

The Adolescent Brain Cognitive Development® (ABCD) Study provides a unique opportunity to investigate developmental processes in a large, diverse cohort of youths, aged approximately 9-10 at baseline and assessed annually for 10 years. Given the size and complexity of the ABCD Study, researchers analyzing its data will encounter a myriad of methodological and analytical considerations. This review provides an examination of key concepts and techniques related to longitudinal analyses of the ABCD Study data, including: (1) characterization of the factors associated with variation in developmental trajectories; (2) assessment of how level and timing of exposures may impact subsequent development; (3) quantification of how variation in developmental domains may be associated with outcomes, including mediation models and reciprocal relationships. We emphasize the importance of selecting appropriate statistical models to address these research questions. By presenting the advantages and potential challenges of longitudinal analyses in the ABCD Study, this review seeks to equip researchers with foundational knowledge and tools to make informed decisions as they navigate and effectively analyze and interpret the multi-dimensional longitudinal data currently available.

Measuring and interpreting individual differences in fetal, infant, and toddler neurodevelopment

As scientists interested in fetal, infant, and toddler (FIT) neurodevelopment, our research questions often focus on how individual children differ in their neurodevelopment and the predictive value of those individual differences for long-term neural and behavioral outcomes. Measuring and interpreting individual differences in neurodevelopment can present challenges: Is there a "standard" way for the human brain to develop? How do the semantic, practical, or theoretical constraints that we place on studying "development" influence how we measure and interpret individual differences? While it is important to consider these questions across the lifespan, they are particularly relevant for conducting and interpreting research on individual differences in fetal, infant, and toddler neurodevelopment due to the rapid, profound, and heterogeneous changes happening during this period, which may be predictive of long-term outcomes. This article, therefore, has three goals: 1) to provide an overview about how individual differences in neurodevelopment are studied in the field of developmental cognitive neuroscience, 2) to identify challenges and considerations when studying individual differences in neurodevelopment, and 3) to discuss potential implications and solutions moving forward.

Exploring Reciprocal Associations Between Self-Reported Anxiety and Eating Disorder Symptoms Longitudinally: A Bivariate Latent Change Score Approach

OBJECTIVE

Consistent data support an association between anxiety and eating disorders (EDs), and theoretical models of EDs suggest that anxiety may be involved in the etiology and maintenance of ED symptoms over time. However, the directionality of relations between these variables remains under-characterized, particularly within treatment settings.

METHOD

We used bivariate latent change score models to explore longitudinal associations between anxiety and ED symptoms in a sample of ED patients (N = 548, 93.2% female, Mage = 21.16, 78.8% White, 79.6% Non-Hispanic/Latinx) throughout intensive treatment and at 6- and 12-month follow-up.

RESULTS

Best-fitting models exploring change in each variable independently (i.e., univariate models) suggested that changes in ED and anxiety symptoms decreased over time, but that change was influenced by an individual's symptom severity at the previous timepoint. Models exploring associations between changes in both variables over time (i.e., bivariate latent change score models) suggested the best fit for a model where both anxiety and ED symptoms at one timepoint were associated with later change in the other. Specifically, parameters within these models suggested that higher levels of anxiety were associated with increased subsequent reductions in ED symptoms, whereas elevations in ED symptoms were associated with decreased later reductions in anxiety.

CONCLUSIONS

Our findings suggest that anxiety and ED symptoms are intricately related both within and outside of intensive treatment. Future multi-modal research exploring real-time links between anxiety and ED symptoms throughout treatment is critical to extend this work and inform improvements in targeted, mechanistic interventions for this population.

Collateral effects of Coping Power on caregiver symptoms of depression and long-term changes in child behavior

A large body of research demonstrates positive impacts of the Coping Power Program as a preventive intervention for youth behavioral outcomes, but potential collateral effects for caregivers is less known. The current study examined whether the youth-focused Coping Power Program can have a secondary impact on caregiver self-reported symptoms of depression and in turn result in longer-term impacts on child disruptive behavior problems including aggression, conduct problems and hyperactivity. Data from 360 youth/caregiver pairs across 8 waves of data (grades 4 through 10) were analyzed. We used two methodological approaches to (a) assess indirect effects in the presence of potential bidirectionality using timepoint-to-timepoint dynamic effects under Autoregressive Latent Trajectory modeling and (b) estimate scale scores in the presence of measurement non-invariance. Results showed that individually delivered Coping Power (ICP) produced greater direct effects on conduct problems and indirect effects on general externalizing and hyperactivity (through reductions in caregiver self-reported symptoms of depression), compared to group Coping Power (GCP). In comparison to GCP, ICP produced similar direct effects on reductions in caregiver depression. Child-focused prevention interventions can have an indirect impact on caregiver depression, which later shows improvements in longer-term reductions for child disruptive problems.

Longitudinal Image Data for Outcome Modeling

In oncology, medical imaging is crucial for diagnosis, treatment planning and therapy execution. Treatment responses can be complex and varied and are known to involve factors of treatment, patient characteristics and tumor microenvironment. Longitudinal image analysis is able to track temporal changes, aiding in disease monitoring, treatment evaluation, and outcome prediction. This allows for the enhancement of personalized medicine. However, analyzing longitudinal 2D and 3D images presents unique challenges, including image registration, reliable segmentation, dealing with variable imaging intervals, and sparse data. This review presents an overview of techniques and methodologies in longitudinal image analysis, with a primary focus on outcome modeling in radiation oncology.

Enhancing causal inference in population-based neuroimaging data in children and adolescents

Recent years have seen the increasing availability of large, population-based, longitudinal neuroimaging datasets, providing unprecedented capacity to examine brain-behavior relationships in the neurodevelopmental context. However, the ability of these datasets to deliver causal insights into brain-behavior relationships relies on the application of purpose-built analysis methods to counter the biases that otherwise preclude causal inference from observational data. Here we introduce these approaches (i.e., propensity score-based methods, the 'G-methods', targeted maximum likelihood estimation, and causal mediation analysis) and conduct a review to determine the extent to which they have been applied thus far in the field of developmental cognitive neuroscience. We identify just eight relevant studies, most of which employ propensity score-based methods. Many approaches are entirely absent from the literature, particularly those that promote causal inference in settings with complex, multi-wave data and repeated neuroimaging assessments. Causality is central to an etiological understanding of the relationship between the brain and behavior, as well as for identifying targets for prevention and intervention. Careful application of methods for causal inference may help the field of developmental cognitive neuroscience approach these goals.

Psychiatric neuroimaging at a crossroads: Insights from psychiatric genetics

Thanks to methodological advances, large-scale data collections, and longitudinal designs, psychiatric neuroimaging is better equipped than ever to identify the neurobiological underpinnings of youth mental health problems. However, the complexity of such endeavors has become increasingly evident, as the field has been confronted by limited clinical relevance, inconsistent results, and small effect sizes. Some of these challenges parallel those historically encountered by psychiatric genetics. In past genetic research, robust findings were historically undermined by oversimplified biological hypotheses, mistaken assumptions about expectable effect sizes, replication problems, confounding by population structure, and shared biological patterns across disorders. Overcoming these challenges has contributed to current successes in the field. Drawing parallels across psychiatric genetics and neuroimaging, we identify key shared challenges as well as pinpoint relevant insights that could be gained in psychiatric neuroimaging from the transition that occurred from the candidate gene to (post) genome-wide "eras" of psychiatric genetics. Finally, we discuss the prominent developmental component of psychiatric neuroimaging and how that might be informed by epidemiological and omics approaches. The evolution of psychiatric genetic research offers valuable insights that may expedite the resolution of key challenges in psychiatric neuroimaging, thus potentially moving our understanding of psychiatric pathophysiology forward.

Non-linear development of brain morphometry in child and adolescent offspring of individuals with bipolar disorder or schizophrenia

Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at increased risk of developing psychopathology. Structural brain alterations have been found in child and adolescent offspring of patients with bipolar disorder and schizophrenia, but the developmental trajectories of brain anatomy in this high-familial-risk population are still unclear. 300 T1-weighted scans were obtained of 187 offspring of at least one parent diagnosed with bipolar disorder (n=80) or schizophrenia (n=53) and offspring of parents without severe mental illness (n=54). The age range was 8 to 23 years old; 113 offspring underwent two scans. Global brain measures and regional cortical thickness and surface area were computed. A generalized additive mixed model was used to capture non-linear age trajectories. Offspring of parents with schizophrenia had smaller total brain volume than offspring of parents with bipolar disorder (d=-0.20, p=0.004) and control offspring (d=-0.22, p=0.005) and lower mean cortical thickness than control offspring (d=-0.23, p<0.001). Offspring of parents with schizophrenia showed differential age trajectories of mean cortical thickness and cerebral white matter volume compared with control offspring (both p's=0.003). Regionally, offspring of parents with schizophrenia had a significantly different trajectory of cortical thickness in the middle temporal gyrus versus control offspring (p<0.001) and bipolar disorder offspring (p=0.001), which was no longer significant after correcting for mean cortical thickness. These findings suggest that particularly familial high risk of schizophrenia is related to reductions and deviating developmental trajectories of global brain structure measures, which were not driven by specific regions.

Early Life Adversity Predicts Reduced Hippocampal Volume in the Adolescent Brain Cognitive Development Study

PURPOSE

Cross-sectional studies in adults have demonstrated associations between early life adversity (ELA) and reduced hippocampal volume, but the timing of these effects is not clear. The present study sought to examine whether ELA predicts changes in hippocampal volume over time in a large sample of early adolescents.

METHODS

The Adolescent Brain Cognitive Development Study provides a large dataset of tabulated neuroimaging, youth-reported adverse experiences, and parent-reported financial adversity from a sample of children around the United States. Linear mixed effects modeling was used to determine the relationship between ELA and hippocampal volume change within youth (n = 7036) from ages 9-10 to 11-12 years.

RESULTS

Results of the models indicated that the number of early adverse events predicted bilateral hippocampal volume change (β = -0.02, t = -2.02, p < .05). Higher adversity was associated with lower hippocampal volume at Baseline (t = 5.55, p < .01) and at Year 2 (t = 6.14, p < .001).

DISCUSSION

These findings suggest that ELA may affect hippocampal development during early adolescence. Prevention and early intervention are needed to alter the course of this trajectory. Future work should examine associations between ELA, hippocampal development, and educational and socioemotional outcomes.

Development of human visual cortical function: A scoping review of task- and naturalistic-fMRI studies through the interactive specialization and maturational frameworks

Overarching theories such as the interactive specialization and maturational frameworks have been proposed to describe human functional brain development. However, these frameworks have not yet been systematically examined across the fMRI literature. Visual processing is one of the most well-studied fields in neuroimaging, and research in this area has recently expanded to include naturalistic paradigms that facilitate study in younger age ranges, allowing for an in-depth critical appraisal of these frameworks across childhood. To this end, we conducted a scoping review of 94 developmental visual fMRI studies, including both traditional experimental task and naturalistic studies, across multiple sub-domains (early visual processing, category-specific higher order processing, naturalistic visual processing). We found that across domains, many studies reported progressive development, but few studies describe regressive or emergent changes necessary to fit the maturational or interactive specialization frameworks. Our findings suggest a need for the expansion of developmental frameworks and clearer reporting of both progressive and regressive changes, along with well-powered, longitudinal studies.

Gray and White Matter Metrics Demonstrate Distinct and Complementary Prediction of Differences in Cognitive Performance in Children: Findings from ABCD (N = 11,876)

Individual differences in cognitive performance in childhood are a key predictor of significant life outcomes such as educational attainment and mental health. Differences in cognitive ability are governed in part by variations in brain structure. However, studies commonly focus on either gray or white matter metrics in humans, leaving open the key question as to whether gray or white matter microstructure plays distinct or complementary roles supporting cognitive performance. To compare the role of gray and white matter in supporting cognitive performance, we used regularized structural equation models to predict cognitive performance with gray and white matter measures. Specifically, we compared how gray matter (volume, cortical thickness, and surface area) and white matter measures (volume, fractional anisotropy, and mean diffusivity) predicted individual differences in cognitive performance. The models were tested in 11,876 children (ABCD Study; 5,680 female, 6,196 male) at 10 years old. We found that gray and white matter metrics bring partly nonoverlapping information to predict cognitive performance. The models with only gray or white matter explained respectively 15.4 and 12.4% of the variance in cognitive performance, while the combined model explained 19.0%. Zooming in, we additionally found that different metrics within gray and white matter had different predictive power and that the tracts/regions that were most predictive of cognitive performance differed across metrics. These results show that studies focusing on a single metric in either gray or white matter to study the link between brain structure and cognitive performance are missing a key part of the equation.

White matter microstructural plasticity associated with educational intervention in reading disability

Children's reading progress typically slows during extended breaks in formal education, such as summer vacations. This stagnation can be especially concerning for children with reading difficulties or disabilities, such as dyslexia, because of the potential to exacerbate the skills gap between them and their peers. Reading interventions can prevent skill loss and even lead to appreciable gains in reading ability during the summer. Longitudinal studies relating intervention response to brain changes can reveal educationally relevant insights into rapid learning-driven brain plasticity. The current work focused on reading outcomes and white matter connections, which enable communication among the brain regions required for proficient reading. We collected reading scores and diffusion-weighted images at the beginning and end of summer for 41 children with reading difficulties who had completed either 1st or 2nd grade. Children were randomly assigned to either receive an intensive reading intervention (n = 26; Seeing Stars from Lindamood-Bell which emphasizes orthographic fluency) or be deferred to a wait-list group (n = 15), enabling us to analyze how white matter properties varied across a wide spectrum of skill development and regression trajectories. On average, the intervention group had larger gains in reading compared to the non-intervention group, who declined in reading scores. Improvements on a proximal measure of orthographic processing (but not other more distal reading measures) were associated with decreases in mean diffusivity within core reading brain circuitry (left arcuate fasciculus and left inferior longitudinal fasciculus) and increases in fractional anisotropy in the left corticospinal tract. Our findings suggest that responses to intensive reading instruction are related predominantly to white matter plasticity in tracts most associated with reading.

Cerebrovascular reactivity increases across development in multiple networks as revealed by a breath-holding task: A longitudinal fMRI study

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold (BH) task is commonly used to understand cerebrovascular reactivity (CVR) in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal children's BH data set from the Nathan Kline Institute (NKI) Rockland Sample (aged 6-18 years old at enrollment). A general linear model approach was applied to derive CVR from BH data. To model both the longitudinal and cross-sectional effects of age on BH response, we used mixed-effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased BH BOLD signals in multiple networks across age, in which linear and logarithmic mixed-effects models provided the best fit with the lowest Akaike information criterion scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes that occur with age.

Early nap cessation in young children as a correlate of language and psychosocial outcomes: Evidence from a large Canadian sample

OBJECTIVES

Most children stop napping between 2 and 5years old. We tested the association of early nap cessation (ie, children who stopped before their third birthday) and language, cognition functioning and psychosocial outcomes.

METHODS

Data were from a national, longitudinal sample of Canadian children, with three timepoints. Children were 0-to-1 year old at T1, 2-to-3 years old at T2, and 4-to-5 years old at T3. Early nap cessation was tested as a correlate of children's psychosocial functioning (cross-sectionally and longitudinally), cognitive function (longitudinally), and language skills (longitudinally). There were 4923 children (50.9% male; 90.0% White) and their parents in this study who were included in the main analyses. Parents reported on demographics, perinatal and developmental variables, child functioning, and child sleep. Children completed direct assessments of receptive language and cognitive ability. Nap cessation, demographic, and developmental-control variables were tested as correlates of cross-sectional and longitudinal outcomes using linear regression (with a model-building approach).

RESULTS

Early nap cessation correlated with higher receptive language ability (β = 0.059 ± 0.028) and lower anxiety (β = -0.039 ± 0.028) at T3, after controlling for known correlates of nap cessation, nighttime sleep, and other sociodemographic correlates of the outcomes. Cognitive ability, hyperactivity-inattention, and aggression were not correlated with nap cessation.

CONCLUSIONS

Early nap cessation is related to specific benefits (ie, better receptive language and lower anxiety symptoms). These findings align with previous research. Future research should investigate differences associated with late nap cessation and in nap-encouraging cultures, and by ethnicity.

The Hitchhiker's guide to longitudinal models: A primer on model selection for repeated-measures methods

Longitudinal data are becoming increasingly available in developmental neuroimaging. To maximize the promise of this wealth of information on how biology, behavior, and cognition change over time, there is a need to incorporate broad and rigorous training in longitudinal methods into the repertoire of developmental neuroscientists. Fortunately, these models have an incredibly rich tradition in the broader developmental sciences that we can draw from. Here, we provide a primer on longitudinal models, written in a beginner-friendly (and slightly irreverent) manner, with a particular focus on selecting among different modeling frameworks (e.g., multilevel versus latent curve models) to build the theoretical model of development a researcher wishes to test. Our aims are three-fold: (1) lay out a heuristic framework for longitudinal model selection, (2) build a repository of references that ground each model in its tradition of methodological development and practical implementation with a focus on connecting researchers to resources outside traditional neuroimaging journals, and (3) provide practical resources in the form of a codebook companion demonstrating how to fit these models. These resources together aim to enhance training for the next generation of developmental neuroscientists by providing a solid foundation for future forays into advanced modeling applications.

Cerebrovascular reactivity increases across development in multiple networks as revealed by a breath-holding task: a longitudinal fMRI study

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold task is commonly used to understand cerebrovascular reactivity in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal children's breath-hold dataset from the Nathan Kline Institute (NKI) Rockland Sample (ages 6 to 18 years old at enrollment). A general linear model (GLM) approach was applied to derive cerebrovascular reactivity from breath-hold data. To model both the longitudinal and cross-sectional effects of age on breath-hold response, we used mixed effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased breath-hold BOLD signal in multiple networks across age, in which linear and logarithmic mixed effects models provided the best fit with the lowest Akaike Information Criterion (AIC) scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes which occur with age.

History of Low Hourly Wage and All-Cause Mortality Among Middle-aged Workers

Importance

Earning a low wage is an increasingly recognized public health concern, yet little research exists on the long-term health consequences of sustained low-wage earning.

Objective

To examine the association of sustained low-wage earning and mortality in a sample of workers with hourly wage reported biennially during peak midlife earning years.

Design, Setting, and Participants

This longitudinal study included 4002 US participants, aged 50 years or older, from 2 subcohorts of the Health and Retirement Study (1992-2018) who worked for pay and reported earning hourly wages at 3 or more time points during a 12-year period during their midlife (1992-2004 or 1998-2010). Outcome follow-up occurred from the end of the respective exposure periods until 2018.

Exposures

Low-wage-less than the hourly wage for full-time, full-year work at the federal poverty line-earning history was categorized as never earning a low wage, intermittently earning a low wage, and sustained earning a low wage.

Main Outcomes and Measures

Cox proportional hazards and additive hazards regression models sequentially adjusted for sociodemographics, and economic and health covariates were used to estimate associations between low-wage history and all-cause mortality. We examined interaction with sex or employment stability on multiplicative and additive scales.

Results

Of the 4002 workers (aged 50-57 years at the beginning of exposure period and 61-69 years at the end), 1854 (46.3%) were female; 718 (17.9%) experienced employment instability; 366 (9.1%) had a history of sustained low-wage earning; 1288 (32.2%) had intermittent low-wage earning periods; and 2348 (58.7%) had never earned a low wage. In unadjusted analyses, those who had never earned low wages experienced 199 deaths per 10 000 person-years, those with intermittent low wages, 208 deaths per 10 000 person-years, and those with sustained low wages, 275 deaths per 10 000 person-years. In models adjusted for key sociodemographic variables, sustained low-wage earning was associated with mortality (hazard ratio [HR], 1.35; 95% CI, 1.07-1.71) and excess deaths (66; 95% CI, 6.6-125); these findings were attenuated with additional adjustments for economic and health covariates. Significant excess death and elevated mortality risk were observed for workers with sustained low-wage exposure and employment fluctuations (eg, for sustained low-wage × employment fluctuated, HR, 2.18; 95% CI, 1.35-3.53; for sustained low-wage × stable employment, HR, 1.17; 95% CI, 0.89,-1.54; P for interaction = .003).

Conclusions and Relevance

Sustained low-wage earning may be associated with elevated mortality risk and excess deaths, especially when experienced alongside unstable employment. If causal, our findings suggest that social and economic policies that improve the financial standing of low-wage workers (eg, minimum wage laws) could improve mortality outcomes.

An Intensive Longitudinal Assessment Approach to Surveilling Trajectories of Burnout over the First Year of the COVID Pandemic

Frontline clinicians responding to the COVID-19 pandemic are at increased risk of burnout, but less is known about the trajectory of clinician burnout as caseloads increase and decrease. Personal and professional resources, including self-efficacy and hospital support, can attenuate the risk of burnout. Yet, empirical data documenting how burnout and resources changed as the pandemic waxed and waned are limited. This intensive longitudinal prospective study employed ecological momentary assessment methods to examine trajectories of burnout and resources over the pandemic's first year in a New York City hospital. A 10-item survey was emailed every 5 days to frontline clinicians (physicians, nurses, and physician assistants). The primary outcome was a single-item validated measure of burnout; predictors included daily hospital COVID-19-related caseloads and personal and professional resources. Clinicians (n = 398) completed the initial survey and an average of 12 surveys over the year. Initially, 45.3% of staff reported burnout; over the year, 58.7% reported burnout. Following the initial COVID peak, caseloads declined, and burnout levels declined. During the second wave of COVID, as caseloads increased and remained elevated and personal and professional resource levels decreased, burnout increased. This novel application of intensive longitudinal assessment enabled ongoing surveillance of burnout and permitted us to evaluate how fluctuations in caseload intensity and personal and professional resources related to burnout over time. The surveillance data support the need for intensified resource allocation during prolonged pandemics.

Conceptualizing and Examining Change in Communication Research

Communication research often focuses on processes of communication, such as how messages impact individuals over time or how interpersonal relationships develop and change. Despite their importance, these change processes are often implicit in much theoretical and empirical work in communication. Intensive longitudinal data are becoming increasingly feasible to collect and, when coupled with appropriate analytic frameworks, enable researchers to better explore and articulate the types of change underlying communication processes. To facilitate the study of change processes, we (a) describe advances in data collection and analytic methods that allow researchers to articulate complex change processes of phenomena in communication research, (b) provide an overview of change processes and how they may be captured with intensive longitudinal methods, and (c) discuss considerations of capturing change when designing and implementing studies. We are excited about the future of studying processes of change in communication research, and we look forward to the iterations between empirical tests and theory revision that will occur as researchers delve into studying change within communication processes.

Real-World Intake of Dietary Sugars Is Associated with Reduced Cortisol Reactivity Following an Acute Physiological Stressor

There is increasing academic and clinical interest in understanding the nature of the relation between diet and response to stress exposure as a risk factor for mental illness. Cross-species evidence shows that conditions of chronic and acute stress increase the intake of, and preference for, caloric-dense palatable foods, a phenomenon thought to be explained by the mitigating effects of comfort foods on the activity of the stress-response network. It is largely unknown whether and how real-world dietary intake of saturated fat and sugars impacts stress responsivity in humans. Therefore, here we examined whether real-world dietary intake of saturated fat and sugars predicted salivary cortisol reactivity following an acute physiological stressor. Multilevel modelling of four salivary cortisol measures collected up to 65 min after the stressor on 54 participants (18-49 years old) were analyzed using a quadratic growth curve model. Sugar intake significantly predicted a weaker cortisol response following the Cold Pressor Test (CPT) controlling for BMI and gender, revealing an inhibitory effect of caloric-dense diets on cortisol reactivity to stress. As the consumption of sugar rose individuals had lower post-stressor cortisol levels, a smaller rate of increase in cortisol 20 and 35 min after the CPT, a lower cortisol peak, and an overall weaker quadratic effect. These observations add to a growing body of evidence reporting suppressive effects of high-energy foods on stress-associated glucocorticoids reactivity and are consistent with the comfort food hypothesis, where people are seen as motivated to eat palatable foods to alleviate the detrimental repercussions of stressor exposure.

Data management strategy for a collaborative research center

The importance of effective research data management (RDM) strategies to support the generation of Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience data grows with each advance in data acquisition techniques and research methods. To maximize the impact of diverse research strategies, multidisciplinary, large-scale neuroscience research consortia face a number of unsolved challenges in RDM. While open science principles are largely accepted, it is practically difficult for researchers to prioritize RDM over other pressing demands. The implementation of a coherent, executable RDM plan for consortia spanning animal, human, and clinical studies is becoming increasingly challenging. Here, we present an RDM strategy implemented for the Heidelberg Collaborative Research Consortium. Our consortium combines basic and clinical research in diverse populations (animals and humans) and produces highly heterogeneous and multimodal research data (e.g., neurophysiology, neuroimaging, genetics, behavior). We present a concrete strategy for initiating early-stage RDM and FAIR data generation for large-scale collaborative research consortia, with a focus on sustainable solutions that incentivize incremental RDM while respecting research-specific requirements.

Developmental trajectories of delay discounting from childhood to young adulthood: longitudinal associations and test-retest reliability

Delay discounting (DD) indexes an individual's preference for smaller immediate rewards over larger delayed rewards, and is considered a form of cognitive impulsivity. Cross-sectional studies have demonstrated that DD peaks in adolescence; longitudinal studies are needed to validate this putative developmental trend, and to determine whether DD assesses a temporary state, or reflects a more stable behavioral trait. In this study, 140 individuals aged 9-23 completed a delay discounting (DD) task and cognitive battery at baseline and every-two years thereafter, yielding five assessments over approximately 10 years. Models fit with the inverse effect of age best approximated the longitudinal trajectory of two DD measures, hyperbolic discounting (log[k]) and area under the indifference-point curve (AUC). Discounting of future rewards increased rapidly from childhood to adolescence and appeared to plateau in late adolescence for both models of DD. Participants with greater verbal intelligence and working memory displayed reduced DD across the duration of the study, suggesting a functional interrelationship between these domains and DD from early adolescence to adulthood. Furthermore, AUC demonstrated good to excellent reliability across assessment points that was superior to log(k), with both measures demonstrating acceptable stability once participants reached late adolescence. The developmental trajectories of DD we observed from childhood through young adulthood suggest that DD may index cognitive control more than reward sensitivity, and that despite modest developmental changes with maturation, AUC may be conceptualized as a trait variable related to cognitive control vs impulsivity.

Vulnerability of the Neonatal Connectome following Postnatal Stress

Stress following preterm birth can disrupt the emerging foundation of the neonatal brain. The current study examined how structural brain development is affected by a stressful early environment and whether changes in topological architecture at term-equivalent age could explain the increased vulnerability for behavioral symptoms during early childhood. Longitudinal changes in structural brain connectivity were quantified using diffusion-weighted imaging (DWI) and tractography in preterm born infants (gestational age <28 weeks), imaged at 30 and/or 40 weeks of gestation (N = 145, 43.5% female). A global index of postnatal stress was determined based on the number of invasive procedures during hospitalization (e.g., heel lance). Higher stress levels impaired structural connectivity growth in a subnetwork of 48 connections (p = 0.003), including the amygdala, insula, hippocampus, and posterior cingulate cortex. Findings were replicated in an independent validation sample (N = 123, 39.8% female, n = 91 with follow-up). Classifying infants into vulnerable and resilient based on having more or less internalizing symptoms at two to five years of age (n = 71) revealed lower connectivity in the hippocampus and amygdala for vulnerable relative to resilient infants (p < 0.001). Our findings suggest that higher stress exposure during hospital admission is associated with slower growth of structural connectivity. The preservation of global connectivity of the amygdala and hippocampus might reflect a stress-buffering or resilience-enhancing factor against a stressful early environment and early-childhood internalizing symptoms.SIGNIFICANCE STATEMENT The preterm brain is exposed to various external stimuli following birth. The effects of early chronic stress on neonatal brain networks and the remarkable degree of resilience are not well understood. The current study aims to provide an increased understanding of the impact of postnatal stress on third-trimester brain development and describe the topological architecture of a resilient brain. We observed a sparser neonatal brain network in infants exposed to higher postnatal stress. Limbic regulatory regions, including the hippocampus and amygdala, may play a key role as crucial convergence sites of protective factors. Understanding how stress-induced alterations in early brain development might lead to brain (re)organization may provide essential insights into resilient functioning.

Mapping brain mechanical property maturation from childhood to adulthood

Magnetic resonance elastography (MRE) is a phase contrast MRI technique which uses external palpation to create maps of brain mechanical properties noninvasively and in vivo. These mechanical properties are sensitive to tissue microstructure and reflect tissue integrity. MRE has been used extensively to study aging and neurodegeneration, and to assess individual cognitive differences in adults, but little is known about mechanical properties of the pediatric brain. Here we use high-resolution MRE imaging in participants of ages ranging from childhood to adulthood to understand brain mechanical properties across brain maturation. We find that brain mechanical properties differ considerably between childhood and adulthood, and that neuroanatomical subregions have differing maturational trajectories. Overall, we observe lower brain stiffness and greater brain damping ratio with increasing age from 5 to 35 years. Gray and white matter change differently during maturation, with larger changes occurring in gray matter for both stiffness and damping ratio. We also found that subregions of cortical and subcortical gray matter change differently, with the caudate and thalamus changing the most with age in both stiffness and damping ratio, while cortical subregions have different relationships with age, even between neighboring regions. Understanding how brain mechanical properties mature using high-resolution MRE will allow for a deeper understanding of the neural substrates supporting brain function at this age and can inform future studies of atypical maturation.

The development of cortical functional hierarchy is associated with the molecular organization of prenatal/postnatal periods

The human cerebral cortex conforms to specific functional hierarchies facilitating information processing and higher-order cognition. Prior studies in adults have unveiled a dominant functional hierarchy spanning from sensorimotor regions to transmodal regions, which is also present in younger cohorts. However, how the functional hierarchy develops and the underlying molecular mechanisms remain to be investigated. Here, we set out to investigate the developmental patterns of the functional hierarchy for preschool children (#scans = 141, age = 2.41-6.90 years) using a parsimonious general linear model and the underlying biological mechanisms by combining the neuroimaging developmental pattern with two separate transcriptomic datasets (i.e. Allen Human Brain Atlas and BrainSpan Atlas). Our results indicated that transmodal regions were further segregated from sensorimotor regions and that such changes were potentially driven by two gene clusters with distinct enrichment profiles, namely prenatal gene cluster and postnatal gene cluster. Additionally, we found similar developmental profiles manifested in subsequent developmental periods by conducting identical analyses on the Human Connectome Projects in Development (#scans = 638, age = 5.58-21.92 years) and Philadelphia Neurodevelopment Cohort datasets (#scans = 795, age = 8-21 years), driven by concordant two gene clusters. Together, these findings illuminate a comprehensive developmental principle of the functional hierarchy and the underpinning molecular factors, and thus may shed light on the potential pathobiology of neurodevelopmental disorders.

Maturing out of alcohol and cannabis co-use: A test of patterns and personality predictors

OBJECTIVE

Reductions in substance involvement into adulthood are thought to represent a normative maturing out of substance use. However, patterns and predictors of maturing out of alcohol and cannabis co-use remain largely unstudied. Therefore, the current study tested developmental trajectories of alcohol and cannabis use from late adolescence into adulthood and whether late adolescent personality traits predicted trajectory class membership.

METHODS

Data come from a longitudinal study of family history of alcohol disorder (N = 458). Age bands were created to model trajectories of drinking quantity, negative alcohol consequences, and cannabis use frequency from late adolescence (age 18-22) to young adulthood (age 23-28) and adulthood (age 29-36). Participants reported on their sensation seeking, conscientiousness, and neuroticism during late adolescence and their typical drinking quantity, negative alcohol consequences, and cannabis use frequency at each age band.

RESULTS

Three trajectory classes were derived from an initial Parallel Process Growth Mixture Model: (1) low-risk maturing out of alcohol-only use, (2) high-risk maturing out of co-use, and (3) high-risk switchers who increased their cannabis use into adulthood. Late adolescent sensation seeking was associated with higher odds of being in both co-use trajectories, whereas a lack of conscientiousness was associated with higher odds of being a co-use switcher.

CONCLUSIONS

We identified heterogeneity in trajectories of co-use, which suggests that a lack of maturing out of alcohol involvement may be accompanied by increased cannabis use. Moreover, late adolescent personality traits may predispose individuals toward riskier developmental trajectories of substance use into adulthood.

Does group-based trajectory modeling estimate spurious trajectories?

BACKGROUND

Group-based trajectory modelling (GBTM) is increasingly used to identify subgroups of individuals with similar patterns. In this paper, we use simulated and real-life data to illustrate that GBTM is susceptible to generating spurious findings in some circumstances.

METHODS

Six plausible scenarios, two of which mimicked published analyses, were simulated. Models with 1 to 10 trajectory subgroups were estimated and the model that minimized the Bayes criterion was selected. For each scenario, we assessed whether the method identified the correct number of trajectories, the correct shapes of the trajectories, and the mean number of participants of each trajectory subgroup. The performance of the average posterior probabilities, relative entropy and mismatch criteria to assess classification adequacy were compared.

RESULTS

Among the six scenarios, the correct number of trajectories was identified in two, the correct shapes in four and the mean number of participants of each trajectory subgroup in only one. Relative entropy and mismatch outperformed the average posterior probability in detecting spurious trajectories.

CONCLUSION

Researchers should be aware that GBTM can generate spurious findings, especially when the average posterior probability is used as the sole criterion to evaluate model fit. Several model adequacy criteria should be used to assess classification adequacy.

A meta-analysis on the affect regulation function of real-time self-injurious thoughts and behaviours

Prominent theories suggest that self-injurious thoughts and behaviours are negatively reinforced by decreased negative affect. The present meta-analysis quantifies effects from intensive longitudinal studies measuring negative affect and self-injurious thoughts and behaviours. We obtained data from 38 of the 79 studies (48%, 22 unique datasets) involving N = 1,644 participants (80% female, 75% white). Individual-participant data meta-analyses revealed changes in affect pre/post self-injurious thoughts and behaviours. In antecedent models, results supported increased negative affect before nonsuicidal self-injurious behaviour (k = 14, 95% CI 0.09 to 0.31) and suicidal thoughts (k = 14, 95% CI 0.03 to 0.19). For consequence models, negative affect was reduced following nonsuicidal self-injurious thoughts (k = 6, 95% CI -0.79 to -0.44), nonsuicidal self-injurious behaviours (k = 14, 95% CI -0.73 to -0.19) and suicidal thoughts (k = 13, 95% CI -0.79 to -0.23). Findings, which were not moderated by sampling strategies or sample composition, support the affect regulation function of self-injurious thoughts and behaviours.

Age-related change in task-evoked amygdala-prefrontal circuitry: A multiverse approach with an accelerated longitudinal cohort aged 4-22 years

The amygdala and its connections with medial prefrontal cortex (mPFC) play central roles in the development of emotional processes. While several studies have suggested that this circuitry exhibits functional changes across the first two decades of life, findings have been mixed - perhaps resulting from differences in analytic choices across studies. Here we used multiverse analyses to examine the robustness of task-based amygdala-mPFC function findings to analytic choices within the context of an accelerated longitudinal design (4-22 years-old; N = 98; 183 scans; 1-3 scans/participant). Participants recruited from the greater Los Angeles area completed an event-related emotional face (fear, neutral) task. Parallel analyses varying in preprocessing and modeling choices found that age-related change estimates for amygdala reactivity were more robust than task-evoked amygdala-mPFC functional connectivity to varied analytical choices. Specification curves indicated evidence for age-related decreases in amygdala reactivity to faces, though within-participant changes in amygdala reactivity could not be differentiated from between-participant differences. In contrast, amygdala-mPFC functional connectivity results varied across methods much more, and evidence for age-related change in amygdala-mPFC connectivity was not consistent. Generalized psychophysiological interaction (gPPI) measurements of connectivity were especially sensitive to whether a deconvolution step was applied. Our findings demonstrate the importance of assessing the robustness of findings to analysis choices, although the age-related changes in our current work cannot be overinterpreted given low test-retest reliability. Together, these findings highlight both the challenges in estimating developmental change in longitudinal cohorts and the value of multiverse approaches in developmental neuroimaging for assessing robustness of results.

A practical guide for researchers and reviewers using the ABCD Study and other large longitudinal datasets

As the largest longitudinal study of adolescent brain development and behavior to date, the Adolescent Brain Cognitive Development (ABCD) Study® has provided immense opportunities for researchers across disciplines since its first data release in 2018. The size and scope of the study also present a number of hurdles, which range from becoming familiar with the study design and data structure to employing rigorous and reproducible analyses. The current paper is intended as a guide for researchers and reviewers working with ABCD data, highlighting the features of the data (and the strengths and limitations therein) as well as relevant analytical and methodological considerations. Additionally, we explore justice, equity, diversity, and inclusion efforts as they pertain to the ABCD Study and other large-scale datasets. In doing so, we hope to increase both accessibility of the ABCD Study and transparency within the field of developmental cognitive neuroscience.

Maternal Responsive Parenting Trajectories From Birth to Age 3 and Children's Self-Esteem at First Grade

This paper examines the quality and stability of the responsive parenting practices of mothers with infants and the longitudinal links between these practices and children’s self-esteem. Using data presented by the Panel Study on Korean Children, this study identified Korean mothers’ responsive parenting trajectories from birth to age three and examined their associations with children’s self-esteem at first grade. Korean mothers developed one of three responsive parenting patterns from birth to age three: low (19.0%), moderate (66.0%), or high (15.0%). Children’s self-esteem differed according to their mother’s responsive parenting trajectory. First-graders with mothers displaying the low responsive parenting trajectory were more likely to have lower self-esteem than children of mothers with the moderate responsive parenting trajectory and children of mothers with the high responsive parenting trajectory. The longitudinal link between mother-reported responsive parenting patterns during infancy and child-reported self-esteem at first grade was verified. This finding highlights the significance of early responsive parenting from mothers as a predictor of the self-esteem of children in later developmental stages.

lcsm: An R package and tutorial on latent change score modelling

Latent change score models (LCSMs) are used across disciplines in behavioural sciences to study how constructs change over time. LCSMs can be used to estimate the trajectory of one construct (univariate) and allow the investigation of how changes between two constructs (bivariate) are associated with each other over time. This paper introduces the R package lcsm, a tool that aims to help users understand, analyse, and visualise different latent change score models. The lcsm package provides functions to generate model syntax for basic univariate and bivariate latent change score models with different model specifications. It is also possible to visualise different model specifications in simplified path diagrams. An interactive application illustrates the main functions of the package and demonstrates how the model syntax and path diagrams change based on different model specifications. This R package aims to increase the transparency of reporting analyses and to provide an additional resource to learn latent change score modelling.

Limitations of cross-lagged panel models in addiction research and alternative models: An empirical example using project MATCH

OBJECTIVE

Models of addiction often posit bidirectional and dynamic associations between constructs relevant to the etiology and maintenance of addictive behaviors. The cross-lagged panel model (CLPM) is commonly used in addiction research but has been critiqued for not appropriately adjusting for between-person variance. Alternatives to the CLPM have been suggested but remain underutilized. The primary purpose of this article is to highlight interpretational limitations of the CLPM and to provide examples of alternative models.

METHOD

We specified CLPM, Random-Intercept CLPM, and a Latent Curve Model with Structured Residuals using four waves of data from Project MATCH (n = 1,201). We modeled prospective relations among depression symptoms and temptation to drink. Substantive inferences and assumptions across models were compared.

RESULTS

The CLPM provided the most evidence of significant cross-lagged paths but the poorest fit to the data compared to other models. Alternative models found little evidence of prospective within-person associations, and more evidence for between-person associations and wave-specific within-person relations between depression symptoms and temptation to drink.

CONCLUSIONS

This study highlights shortcomings of the CLPM and details alternative models to consider. Addiction researchers should consider alternatives to the CLPM to more optimally delineate relations among constructs across time. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Using large, publicly available data sets to study adolescent development: opportunities and challenges

Adolescence is a period of rapid change, with cognitive, mental wellbeing, environmental biological factors interacting to shape lifelong outcomes. Large, longitudinal phenotypically rich data sets available for reuse (secondary data) have revolutionized the way we study adolescence, allowing the field to examine these unfolding processes across hundreds or even thousands of individuals. Here, we outline the opportunities and challenges associated with such secondary data sets, provide an overview of particularly valuable resources available to the field, and recommend best practices to improve the rigor and transparency of analyses conducted on large, secondary data sets.

Longitudinal Change in Neural Response to Vocal Emotion in Adolescence

Adolescence is associated with maturation of function within neural networks supporting the processing of social information. Previous longitudinal studies have established developmental influences on youth’s neural response to facial displays of emotion. Given the increasing recognition of the importance of non-facial cues to social communication, we build on existing work by examining longitudinal change in neural response to vocal expressions of emotion in 8- to 19-year-old youth. Participants completed a vocal emotion recognition task at two timepoints (1 year apart) while undergoing functional magnetic resonance imaging. The right inferior frontal gyrus, right dorsal striatum and right precentral gyrus showed decreases in activation to emotional voices across timepoints, which may reflect focalization of response in these areas. Activation in the dorsomedial prefrontal cortex was positively associated with age but was stable across timepoints. In addition, the slope of change across visits varied as a function of participants’ age in the right temporo-parietal junction (TPJ): this pattern of activation across timepoints and age may reflect ongoing specialization of function across childhood and adolescence. Decreased activation in the striatum and TPJ across timepoints was associated with better emotion recognition accuracy. Findings suggest that specialization of function in social cognitive networks may support the growth of vocal emotion recognition skills across adolescence.

Rethinking Autism Intervention Science: A Dynamic Perspective

Recent advances in longitudinal methodologies for observational studies have contributed to a better understanding of Autism as a neurodevelopmental condition characterized by within-person and between-person variability over time across behavioral domains. However, this finer-grained approach to the study of developmental variability has yet to be applied to Autism intervention science. The widely adopted experimental designs in the field-randomized control trials and quasi-experimental designs-hold value for inferring treatment effects; at the same time, they are limited in elucidating what works for whom, why, and when, given the idiosyncrasies of neurodevelopmental disorders where predictors and outcomes are often dynamic in nature. This perspective paper aims to serve as a primer for Autism intervention scientists to rethink the way we approach predictors of treatment response and treatment-related change using a dynamic lens. We discuss several empirical gaps, and potential methodological challenges and opportunities pertaining to: (1) capturing finer-grained treatment effects in specific behavioral domains as indexed by micro-level within-person changes during and beyond intervention; and (2) examining and modeling dynamic prediction of treatment response. Addressing these issues can contribute to enhanced study designs and methodologies that generate evidence to inform the development of more personalized interventions and stepped care approaches for individuals on the heterogeneous spectrum of Autism with changing needs across development.

Associations between frailty trajectories and frailty status and adverse outcomes in community-dwelling older adults

BACKGROUND

The association between frailty and adverse outcomes has been clearly defined. Frailty is associated with age, but different frailty evolution patterns might determine the incidence of adverse outcomes at older ages. So far, few observational studies have examined how distinct frailty trajectories could be associated with differences in the risk of adverse events and assessing whether frailty trajectories could define risk of death, hospitalization, worsening, and incident disability better than one-off assessment. Our hypothesis is that prospective increases in frailty levels are associated with higher risk of adverse events compared with subjects that prospectively decreased frailty levels.

METHODS

Participants' data were taken from the Toledo Study of Healthy Ageing. Frailty was evaluated using the Frailty Trait Scale 5 (FTS5), being 0 the lower (the most robust) and 50 the highest (the frailest) score. FTS5 scores at baseline and follow-up (median 5.04 years) were used to construct frailty trajectories according to group-based trajectory modelling (GBTM). Multivariate Cox proportional hazard and logistic regression models were used to explore associations between frailty status and trajectory membership and the adverse outcomes. Deaths were ascertained through the Spanish National Death Index. Disability was evaluated through the Katz Index. Hospitalization was defined as first admission to Toledo Hospital.

RESULTS

Nine hundred and seventy-five older adults (mean age 73.14 ± 4.69; 43.38% men) were included. GBTM identified five FTS5 trajectories: worsening from non-frailty (WNF), improving to non-frailty (INF), developing frailty (DF), remaining frail (RF), and increasing frailty (IF). Subjects belonging to trajectories of increasing frailty scores or showing consistently higher frailty levels presented with an increased risk of mortality {DF [hazard ratio (HR), 95% confidence interval (CI)] = 2.01 [1.21-3.32]; RF = 1.92 [1.18-3.12]; IF = 2.67 [1.48-4.81]}, incident [DF (HR, 95% CI) = 2.06 (1.11-3.82); RF = 2.29 (1.30-4.03); IF = 3.55 (1.37-9.24)], and worsening disability [DF (HR, 95% CI) = 2.11 (1.19-3.76); RF = 2.14 (1.26-3.64); IF = 2.21 (1.06-4.62)], compared with subjects prospectively showing decreases in frailty levels or maintaining low FTS5 scores. A secondary result was a significant dose-response relationship between baseline FTS5 score and adverse events.

CONCLUSIONS

Belonging to trajectories of prospectively increasing/consistently high frailty scores over time are associated with an increased risk of adverse outcomes compared with maintaining low or reducing frailty scores. Our results support the dynamic nature of frailty and the potential benefit of interventions aimed at reducing its levels on relevant and burdensome adverse outcomes.

Connecting Theory to Methods in Longitudinal Research

Advances in methods for longitudinal data collection and analysis have prompted a surge of research on psychological processes. However, decisions about how to time assessments are often not explicitly tethered to theories about psychological processes but are instead justified on methodological (e.g., power) or practical (e.g., feasibility) grounds. In many cases, methodological decisions are not explicitly justified at all. The disconnect between theories about processes and the timing of assessments in longitudinal research has contributed to misspecified models, interpretive errors, mixed findings, and nonspecific conclusions. In this article, we argue that higher demands should be placed on researchers to connect theories to methods in longitudinal research. We review instances of this disconnect and offer potential solutions as they pertain to four general questions for longitudinal researchers: how time should be scaled, how many assessments are needed, how frequently assessments should occur, and when assessments should happen.

Substance use and sexual minority status: examining the mediating roles of stress and emotion dysregulation in young adult women

Sexual minority women (SMW) report higher rates of substance use and disorder across the lifespan, and greater levels of minority stress in adolescence and young adulthood. Minority stress mediation models propose that higher levels of social stressors may increase emotion dysregulation, which in turn increases the propensity toward substance misuse. Few studies, however, have prospectively examined the impact of stressors and emotion dysregulation among SMW on early and escalating substance use. This longitudinal study examined whether emotion dysregulation and social stress mediated the association between sexual minority status and developing substance use (ages 17 through 22 years) in a sample of 2,201 heterosexual and 246 SMW participants in the Pittsburgh Girls Study. Results supported serial mediation processes of marijuana use risk: SMW reported higher levels of social stress in late adolescence, which in turn predicted greater emotion dysregulation that was associated with greater marijuana use by young adulthood.

A Narrative Review of Methodological Considerations in Magnetic Resonance Imaging of Offspring Brain Development and the Influence of Parenting

Parenting has been robustly associated with offspring psychosocial development, and these effects are likely reflected in brain development. This hypothesis is being tested with increasingly rigorous methods and the use of magnetic resonance imaging, a powerful tool for characterizing human brain structure and function. The objective of this narrative review was to examine methodological issues in this field that impact the conclusions that can be drawn and to identify future directions in this field. Studies included were those that examined associations between parenting and offspring brain structure or function. Results show four thematic features in this literature that impact the hypotheses that can be tested, and the conclusions drawn. The first theme is a limited body of studies including repeated sampling of offspring brain structure and function, and therefore an over-reliance on cross-sectional or retrospective associations. The second involves a focus on extremes in early life caregiving, limiting generalizability. The third involves the nature of parenting assessment, predominantly parent- or child-report instead of observational measures which may be more ecologically valid measures of parenting. A closely related fourth consideration is the examination of detrimental versus positive parenting behaviors. While studies with one or more of these thematic limitations provide valuable information, future study design should consider addressing these limitations to determine how parenting shapes offspring brain development.

Fractional Anisotropy in Selected, Motor-Related White Matter Tracts and Its Cross-Sectional and Longitudinal Associations With Motor Function in Healthy Older Adults

Background

While it is well-known that deficits in motor performance and brain structural connectivity occur in the course of healthy aging, it is still unclear if and how these changes are related to each other. While some cross-sectional studies suggest that white matter (WM) microstructure is positively associated with motor function in healthy older adults, more evidence is needed. Moreover, longitudinal data is required to estimate whether similar associations can be found between trajectories of change in WM microstructure and motor function. The current study addresses this gap by investigating age-associations and longitudinal changes in WM microstructure and motor function, and the cross-sectional (level-level) and longitudinal (level-change, change-change) association between these two domains.

Method

We used multiple-occasion data (covering 4 years) from a large sample (N = 231) of healthy older adults from the Longitudinal Healthy Aging Brain (LHAB) database. To measure WM microstructure, we used diffusion-weighted imaging data to compute mean FA in three selected WM tracts [forceps minor (FMIN); superior longitudinal fasciculus (SLF); corticospinal tract (CST)]. Motor function was measured via two motor speed tests (grooved pegboard, finger tapping) and one motor strength test (grip force test), separately for the left and the right hand. The statistical analysis was conducted with longitudinal growth curve models in the structural equation modeling framework.

Results

The results revealed longitudinal decline and negative cross-sectional age-associations for mean WM FA in the FMIN and SLF, and for motor function in all tests, with a higher vulnerability for left than right hand motor performance. Regarding cross-domain associations, we found a significant positive level-level correlation among mean WM FA in the FMIN with motor speed. Mean FA in SLF and CST was not correlated with motor performance measures, and none of the level-change or change-change associations were significant. Overall, our results (a) provide important insights into aging-related changes of fine motor abilities and FA in selected white matter tracts associated with motor control, (b) support previous cross-sectional work showing that neural control of movement in older adults also involves brain structures outside the core motor system and (c) align with the idea that, in healthy aging, compensatory mechanisms may be in place and longer time delays may be needed to reveal level-change or change-change associations.

Beyond fingerprinting: Choosing predictive connectomes over reliable connectomes

Recent years have seen a surge of research on variability in functional brain connectivity within and between individuals, with encouraging progress toward understanding the consequences of this variability for cognition and behavior. At the same time, well-founded concerns over rigor and reproducibility in psychology and neuroscience have led many to question whether functional connectivity is sufficiently reliable, and call for methods to improve its reliability. The thesis of this opinion piece is that when studying variability in functional connectivity-both across individuals and within individuals over time-we should use behavior prediction as our benchmark rather than optimize reliability for its own sake. We discuss theoretical and empirical evidence to compel this perspective, both when the goal is to study stable, trait-level differences between people, as well as when the goal is to study state-related changes within individuals. We hope that this piece will be useful to the neuroimaging community as we continue efforts to characterize inter- and intra-subject variability in brain function and build predictive models with an eye toward eventual real-world applications.

Effect of COVID-19 disruptions on young adults' affect and substance use in daily life

OBJECTIVE

Guided by accounts of adjustment in daily life as a key indicator of health, the current study examined prospective changes in young adults' emotions and substance behaviors assessed during a normative baseline period and during the acute COVID-19 disruption period in late March/early April 2020. The COVID-19 assessment also collected psychosocial risk factors expected to moderate changes in adjustment across time.

METHOD

Participants included 295 young adults (70.8% female; ages 18-21 at baseline), drawn from an ongoing study of daily behaviors and health in college life that oversampled for recent substance behaviors, who completed both the baseline and COVID-19 assessments. Hypotheses were tested using analyses of repeated-measures data that included covariates of length of time between assessments and sampling group status.

RESULTS

Direct tests in support of hypotheses indicated an increase in negative affect (d = .67, p < .001), and greater alcohol use (d = .75, p < .001) and marijuana use (d = .58, p < .001), in daily life across time. Levels of positive affect (d = .08, p > .05), nicotine use (d = .01, p > .05), and prescription drug misuse (d = .003, p > .05) did not reliably change in tests of direct models. Moderation tests indicated several risk factors for experiencing steeper increases in negative affect, and increased likelihood of marijuana and nicotine use, in daily life across time.

CONCLUSIONS

Findings offer implications for future research and clinical efforts to improve young adult adjustment in response to the pandemic. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Environmental influences on the pace of brain development

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.

Associations of developmental imbalance between sensation seeking and premeditation in adolescence and heavy episodic drinking in emerging adulthood

BACKGROUND

Dual systems theories suggest that greater imbalance between higher reward sensitivity and lower cognitive control across adolescence conveys risk for behaviors such as heavy episodic drinking (HED). Prior research demonstrated that psychological analogues of these systems, sensation seeking and premeditation, change from childhood through emerging adulthood, and each has been independently linked with HED. However, few studies have assessed whether change over time in these developing analogues is prospectively associated with HED. Moreover, we know of no research that has shown whether within-person differences between higher sensation seeking and relatively lower premeditation across the adolescent period predict HED in emerging adulthood.

METHODS

Prospective data from the National Consortium on Alcohol and NeuroDevelopment in Adolescence study (n = 715) were used to examine the association of sensation seeking and premeditation with HED among adolescents ages 16 to 20 years. We used novel applications of latent difference score modeling and growth curve analysis to test whether increasing sensation seeking, premeditation, and their imbalance over time are associated with HED across the study period, and whether these associations differed by sex.

RESULTS

Whereas premeditation increased linearly from adolescence through emerging adulthood across sexes, males reported growth and females reported decline in sensation seeking. Sensation seeking in adolescence (and not premeditation) was associated with higher levels of HED by emerging adulthood. Importantly, greater imbalance between sensation seeking and premeditation was associated with higher levels of HED by emerging adulthood though we note that variability capturing this imbalance correlated highly (r = 0.86) with baseline levels of sensation seeking.

CONCLUSIONS

Developmental imbalance between higher sensation seeking and lower premeditation in late adolescence may be a risk factor for greater HED in emerging adulthood.

A three-time point longitudinal investigation of the arcuate fasciculus throughout reading acquisition in children developing dyslexia

Although the neural basis of dyslexia has intensively been investigated, results are still unclear about the existence of a white matter deficit in the arcuate fasciculus (AF) throughout development. To unravel this ambiguity, we examined the difference in fractional anisotropy (FA) of the AF between children developing dyslexia and children developing typical reading skills in a longitudinal sample with three MRI time points throughout reading development: the pre-reading stage (5-6 years old), the early reading stage (7-8 years old) and the advanced reading stage (9-10 years old). Applying along-the-tract analyses of white matter organization, our results confirmed that a white matter deficit existed in the left AF prior to the onset of formal reading instruction in children who developed dyslexia later on. This deficit was consistently present throughout the course of reading development. Additionally, we evaluated the use of applying a continuous approach on the participants' reading skills rather than the arbitrary categorization in individuals with or without dyslexia. Our results confirmed the predictive relation between FA and word reading measurements later in development. This study supports the use of longitudinal approaches to investigate the neural basis of the developmental process of learning to read and the application of triangulation, i.e. using multiple research approaches to help gain more insight and aiding the interpretation of obtained results.

Modeling longitudinal changes in hippocampal subfields and relations with memory from early- to mid-childhood

The hippocampus has been suggested to show protracted postnatal developmental growth across childhood. Most previous studies during this developmental period have been cross-sectional in nature and have focused on age-related differences in either hippocampal subregions or subfields, but not both, potentially missing localized changes. This study capitalized on a latent structural equation modeling approach to examine the longitudinal development of hippocampal subfields (cornu ammonis (CA) 2-4/dentate gyrus (DG), CA1, subiculum) in both the head and the body of the hippocampus, separately, in 165 typically developing 4- to 8-year-old children. Our findings document differential development of subfields within hippocampal head and body. Specifically, within hippocampal head, CA1 volume increased between 4-5 years and within hippocampal body, CA2-4/DG and subiculum volume increased between 5-6 years. Additionally, changes in CA1 volume in the head and changes in subiculum in the body between 4-5 years related to improvements in memory between 4-5 years. These findings demonstrate the protracted development of subfields in vivo during early- to mid-childhood, illustrate the importance of considering subfields separately in the head and body of the hippocampus, document co-occurring development of brain and behavior, and highlight the strength of longitudinal data and latent modeling when examining brain development.

Delineating Developmental Periods in Adulthood Suggests Age-Related Shifts in the Correlates of Alcohol Use and Problems

BACKGROUND

Developmental context is related to the propensity to engage in alcohol use, the rate at which alcohol use changes, and the relevance of different risk factors to alcohol use disorder (AUD). Therefore, studies of change should consider developmental nuances, but change is often modeled to follow a uniform pattern, even across distinct developmental periods.

METHODS

This study implemented a novel analytic approach to delineate developmental periods of alcohol behavior (n = 478, ages 18 to 35). This approach was further leveraged to examine age-related shifts in the association of impulsivity risk factors (lack of planning, general sensation seeking, alcohol enhancement expectancies) with alcohol behavior (alcohol quantity*frequency, heavy drinking, AUD).

RESULTS

A sequence of exploratory and confirmatory latent growth models (LGMs) suggested modeling separate linear change factors for alcohol behavior during the primary college (ages 18 to 21) and postcollege years (21 to 35). Bivariate LGMs estimated correlations for alcohol behavior changes with lack of planning, sensation seeking, and enhancement expectancies during these periods. The rate at which heavy drinking changed during the college years was positively correlated with general sensation seeking and lack of planning during this period (rs = 0.61 to 0.63). These correlations were significantly weaker during the postcollege years (rs = 0.29 to 0.34). Notably, the rate of change in alcohol behavior was strongly correlated with enhancement expectancies during the college (r = 0.45 to 0.70) and postcollege years (r = 0.45 to 0.61).

CONCLUSIONS

These findings highlight the importance of sensation seeking and lack of planning with regard to adult alcohol use, particularly in a college environment. There was also a strong link between the rates of change in alcohol behavior and enhancement expectancies across all waves. This study supports the utility of exploratory LGMs for delineating developmental periods of alcohol behavior, which are characterized by different processes.