Neonatal Physical Growth Predicts Electroencephalography Power in Rural South African Children.

Anthropometric measures at birth, indexing prenatal growth, are associated with later cognitive development. Children in low- and middle-income countries (LMIC) are at elevated risk for impaired prenatal and early postnatal growth and enduring cognitive deficits. However, the associations of neonatal physical growth with neural activity are not well-characterized in LMIC contexts, given the dearth of early childhood neuroimaging research in these settings. The current study examined birth length, weight, and head circumference as predictors of EEG relative power over the first three years of life in rural Limpopo Province, South Africa, controlling for postnatal growth and socioeconomic status (SES). A larger head circumference at birth predicted lower relative gamma power, lower right hemisphere relative beta power, and higher relative alpha and theta power. A greater birth length also predicted lower relative gamma power. There were interactions with timepoints such that the associations of birth head circumference and length with EEG power were most pronounced at the 7-month assessment and were attenuated at the 17- and 36-month assessments. The results identify birth head circumference and length as specific predictors of infant neural activity within an under-resourced context.

Neurodevelopment of children exposed to prolonged anesthesia in infancy: GABA study interim analysis of resting-state brain networks at 2, 4, and 10-months old.

BACKGROUND: Previous studies have raised concerns regarding neurodevelopmental impacts of early exposures to general anesthesia and surgery. Electroencephalography (EEG) can be used to study ontogeny of brain networks during infancy. As a substudy of an ongoing study, we examined measures of functional connectivity in awake infants with prior early and prolonged anesthetic exposures and in control infants. METHODS: EEG functional connectivity was assessed using debiased weighted phase lag index at source and sensor levels and graph theoretical measures for resting state activity in awake infants in the early anesthesia (n = 26 at 10 month visit, median duration of anesthesia = 4 [2, 7 h]) and control (n = 38 at 10 month visit) groups at ages approximately 2, 4 and 10 months. Theta and low alpha frequency bands were of primary interest. Linear mixed models incorporated impact of age and cumulative hours of general anesthesia exposure. RESULTS: Models showed no significant impact of cumulative hours of general anesthesia exposure on debiased weighted phase lag index, characteristic path length, clustering coefficient or small-worldness (conditional R2 0.05-0.34). An effect of age was apparent in many of these measures. CONCLUSIONS: We could not demonstrate significant impact of general anesthesia in the first months of life on early development of resting state brain networks over the first postnatal year. Future studies will explore these networks as these infants grow older.

Evaluating a novel high-density EEG sensor net structure for improving inclusivity in infants with curly or tightly coiled hair.

Electroencephalography (EEG) is an important tool in the field of developmental cognitive neuroscience for indexing neural activity. However, racial biases persist in EEG research that limit the utility of this tool. One bias comes from the structure of EEG nets/caps that do not facilitate equitable data collection across hair textures and types. Recent efforts have improved EEG net/cap design, but these solutions can be time-intensive, reduce sensor density, and are more difficult to implement in younger populations. The present study focused on testing EEG sensor net designs over infancy. Specifically, we compared EEG data quality and retention between two high-density saline-based EEG sensor net designs from the same company (Magstim EGI, Whitland, UK) within the same infants during a baseline EEG paradigm. We found that within infants, the tall sensor nets resulted in lower impedances during collection, including lower impedances in the key online reference electrode for those with greater hair heights and resulted in a greater number of usable EEG channels and data segments retained during pre-processing. These results suggest that along with other best practices, the modified tall sensor net design is useful for improving data quality and retention in infant participants with curly or tightly-coiled hair.

Slowing of Parameterized Resting-State Electroencephalography After Mild Traumatic Brain Injury.

Reported changes in electroencephalography (EEG)-derived spectral power after mild traumatic brain injury (mTBI) remains inconsistent across existing literature. However, this may be a result of previous analyses depending solely on observing spectral power within traditional canonical frequency bands rather than accounting for the aperiodic activity within the collected neural signal. Therefore, the aim of this study was to test for differences in rhythmic and arrhythmic time series across the brain, and in the cognitively relevant frontoparietal (FP) network, and observe whether those differences were associated with cognitive recovery post-mTBI. Resting-state electroencephalography (rs-EEG) was collected from 88 participants (56 mTBI and 32 age- and sex-matched healthy controls) within 14 days of injury for the mTBI participants. A battery of executive function (EF) tests was collected at the first session with follow-up metrics collected approximately 2 and 4 months after the initial visit. After spectral parameterization, a significant between-group difference in aperiodic-adjusted alpha center peak frequency within the FP network was observed, where a slowing of alpha peak frequency was found in the mTBI group in comparison to the healthy controls. This slowing of week 2 (collected within 2 weeks of injury) aperiodic-adjusted alpha center peak frequency within the FP network was associated with increased EF over time (evaluated using executive composite scores) post-mTBI. These findings suggest alpha center peak frequency within the FP network as a candidate prognostic marker of EF recovery and may inform clinical rehabilitative methods post-mTBI.

Prenatal influences on postnatal neuroplasticity: Integrating DOHaD and sensitive/critical period frameworks to understand biological embedding in early development.

Early environments can have significant and lasting effects on brain, body, and behavior across the lifecourse. Here, we address current research efforts to understand how experiences impact neurodevelopment with a new perspective integrating two well-known conceptual frameworks - the Developmental Origins of Health and Disease (DOHaD) and sensitive/critical period frameworks. Specifically, we consider how prenatal experiences characterized in the DOHaD model impact two key neurobiological mechanisms of sensitive/critical periods for adapting to and learning from the postnatal environment. We draw from both animal and human research to summarize the current state of knowledge on how particular prenatal substance exposures (psychoactive substances and heavy metals) and nutritional profiles (protein-energy malnutrition and iron deficiency) each differentially impact brain circuits' excitation/GABAergic inhibition balance and myelination. Finally, we highlight new research directions that emerge from this integrated framework, including testing how prenatal environments alter sensitive/critical period timing and learning and identifying potential promotional/buffering prenatal exposures to impact postnatal sensitive/critical periods. We hope this integrative framework considering prenatal influences on postnatal neuroplasticity will stimulate new research to understand how early environments have lasting consequences on our brains, behavior, and health.

Longitudinal effects of prenatal alcohol exposure on visual neurodevelopment over infancy.

Prenatal alcohol exposure (PAE) affects neurodevelopment in over 59 million individuals globally. Prior studies using dichotomous categorization of alcohol use and comorbid substance exposures provide limited knowledge of how prenatal alcohol specifically impacts early human neurodevelopment. In this longitudinal cohort study from Cape Town, South Africa, PAE is measured continuously-characterizing timing, dose, and drinking patterns (i.e., binge drinking). High-density electroencephalography (EEG) during a visual-evoked potential (VEP) task was collected from infants aged 8 to 52 weeks with prenatal exposure exclusively to alcohol and matched on sociodemographic factors to infants with no substance exposure in utero. First trimester alcohol exposure related to altered timing of the P1 VEP component over the first 6 months postnatally, and first trimester binge drinking exposure altered timing of the P1 VEP components such that increased exposure was associated with longer VEP latencies while increasing age was related to shorter VEP latencies (n = 108). These results suggest alcohol exposure in the first trimester may alter visual neurodevelopmental timing in early infancy. Exploratory individual-difference analysis across infants with and without PAE tested the relation between VEP latencies and myelination for a subsample of infants with usable magnetic resonance imaging (MRI) T1w and T2w scans collected at the same time point as EEG (n = 47). Decreased MRI T1w/T2w ratios (an indicator of myelin) in the primary visual cortex (n = 47) were linked to longer P1 VEP latencies. Results from these two sets of analyses suggest that prenatal alcohol and postnatal myelination may both separately impact VEP latency over infancy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Telomere Erosion and Depressive Symptoms Across Development Following Institutional Care.

OBJECTIVE: A large literature has identified exposure to early caregiving adversities as a potent risk for developing affective psychopathology, with depression, in particular, increasing across childhood into adolescence. Evidence suggests telomere erosion, a marker of biological aging, may underlie associations between adverse early-life experiences and later depressive behavior; yet, little is understood about this association during development. METHOD: The current accelerated longitudinal study examined concurrent telomere length and depressive symptoms concurrently, 2 and 4 years later, from the preschool period through adolescence among children exposed (n =116) and not exposed (n = 242) to early previous institutional (PI) care. RESULTS: PI care was associated with shorter telomeres on average and with quadratic age-related growth in depressive symptoms, indicating a steeper association between PI care and depressive symptoms in younger age groups that leveled off in adolescence. Contrary to studies in adult samples, telomere length was not associated with depressive symptoms, and it did not predict future symptoms. CONCLUSION: These findings indicate that early caregiving disruptions increase the risk for both accelerated biological aging and depressive symptoms, although these variables did not correlate with each other during this age range.

Associations Between Infant Screen Use, Electroencephalography Markers, and Cognitive Outcomes.

Importance: Research evidence is mounting for the association between infant screen use and negative cognitive outcomes related to attention and executive functions. The nature, timing, and persistence of screen time exposure on neural functions are currently unknown. Electroencephalography (EEG) permits elucidation of the neural correlates associated with cognitive impairments. Objective: To examine the associations between infant screen time, EEG markers, and school-age cognitive outcomes using mediation analysis with structural equation modeling. Design, Setting, and Participants: This prospective maternal-child dyad cohort study included participants from the population-based study Growing Up in Singapore Toward Healthy Outcomes (GUSTO). Pregnant mothers were enrolled in their first trimester from June 2009 through December 2010. A subset of children who completed neurodevelopmental visits at ages 12 months and 9 years had EEG performed at age 18 months. Data were reported from 3 time points at ages 12 months, 18 months, and 9 years. Mediation analyses were used to investigate how neural correlates were involved in the paths from infant screen time to the latent construct of attention and executive functioning. Data for this study were collected from November 2010 to March 2020 and were analyzed between October 2021 and May 2022. Exposures: Parent-reported screen time at age 12 months. Main Outcomes and Measures: Power spectral density from EEG was collected at age 18 months. Child attention and executive functions were measured with teacher-reported questionnaires and objective laboratory-based tasks at age 9 years. Results: In this sample of 437 children, the mean (SD) age at follow-up was 8.84 (0.07) years, and 227 children (51.9%) were male. The mean (SD) amount of daily screen time at age 12 months was 2.01 (1.86) hours. Screen time at age 12 months contributed to multiple 9-year attention and executive functioning measures (η2, 0.03-0.16; Cohen d, 0.35-0.87). A subset of 157 children had EEG performed at age 18 months; EEG relative theta power and theta/beta ratio at the frontocentral and parietal regions showed a graded correlation with 12-month screen use (r = 0.35-0.37). In the structural equation model accounting for household income, frontocentral and parietal theta/beta ratios partially mediated the association between infant screen time and executive functioning at school age (exposure-mediator ß, 0.41; 95% CI, 0.22 to 0.59; mediator-outcome ß, -0.38; 95% CI, -0.64 to -0.11), forming an indirect path that accounted for 39.4% of the association. Conclusions and Relevance: In this study, infant screen use was associated with altered cortical EEG activity before age 2 years; the identified EEG markers mediated the association between infant screen time and executive functions. Further efforts are urgently needed to distinguish the direct association of infant screen use compared with family factors that predispose early screen use on executive function impairments.

Cross-sectional analysis reveals COVID-19 pandemic community lockdown was linked to dysregulated cortisol and salivary alpha amylase in children.

The COVID-19 pandemic altered everyday life starting in March 2020. These alterations extended to the lives of children as their normal routines were disrupted by community lockdowns, online learning, limited in-person social contact, increased screen time, and reduced physical activity. Considerable research has investigated the physical health impact of COVID-19 infection, but far fewer studies have investigated the physiological impact of stressful pandemic-related changes to daily life, especially in children. The purpose of this study was to leverage an ongoing clinical trial to investigate physiological consequences associated with chronic stress of pandemic community lockdown on children. As a part of the clinical trial, children provided saliva samples. Saliva samples were analyzed for cortisol and salivary alpha amylase (sAA) content. This secondary cross-sectional analysis included 94 preadolescent children located within the Greater Boston, Massachusetts community. Children participated in the study either before, during, or following the pandemic community lockdown to form three groups for comparison. In response to chronic stress caused by the pandemic community lockdown, participants demonstrated dysregulation of fast-acting catecholamine response of the locus-coeruleus-norepinephrine system and slower-acting glucocorticoid response, resulting in an asymmetrical relationship of hypocortisolism (M = 0.78 ± 0.19 µg/mL, p < 0.001) paired with higher sAA (M = 12.73 ± 4.06 U/mL, p = 0.01). Results suggest that the abrupt COVID-19 disruption to daily life, including the stressful experience of community lockdown, had physiological effects on typically developing children. Further research is required to investigate mental health outcomes of children following the chronic stress of the pandemic community lockdown.

Tactile sensitivity and motor coordination in infancy: Effect of age, prior surgery, anaesthesia & critical illness.

BACKGROUND: Tactile sensitivity in the infant period is poorly characterized, particularly among children with prior surgery, anaesthesia or critical illness. The study aims were to investigate tactile sensitivity of the foot and the associated coordination of lower limb motor movement in typically developing infants with and without prior hospital experience, and to develop feasible bedside sensory testing protocols. MATERIALS AND METHODS: A prospective, longitudinal study in 69 infants at 2 and 4 months-old, with and without prior hospital admission. Mechanical stimuli were applied to the foot at graded innocuous and noxious intensities. Primary outcome measures were tactile and nociceptive threshold (lowest force required to evoke any leg movement, or brisk leg withdrawal, respectively), and specific motor flexion threshold (ankle-, knee-, hip-flexion). Secondary analysis investigated (i) single vs multiple trials reliability, and (ii) the effect of age and prior surgery, anaesthesia, or critical illness on mechanical threshold. RESULTS: Magnitude of evoked motor activity increased with stimulus intensity. Single trials had excellent reliability for knee and hip flexion at age 1-3m and 4-7m (ICC range: 0.8 to 0.98, p >0.05). Nociceptive threshold varied as a function of age. Tactile sensitivity was independent of age, number of surgeries, general anaesthesia and ICU stay. CONCLUSIONS: This brief sensory testing protocol may reliably measure tactile and nociceptive reactivity in human infants. Age predicts nociceptive threshold which likely reflects ongoing maturation of spinal and supraspinal circuits. Prior hospital experience has a negligible global effect on sensory processing demonstrating the resilience of the CNS in adverse environments.

Experience-driven plasticity and the emergence of psychopathology: A mechanistic framework integrating development and the environment into the Research Domain Criteria (RDoC) model.

Despite the clear importance of a developmental perspective for understanding the emergence of psychopathology across the life-course, such a perspective has yet to be integrated into the Research Domain Criteria (RDoC) model. In this paper, we articulate a framework that incorporates developmentally specific learning mechanisms that reflect experience-driven plasticity as additional units of analysis in the existing RDoC matrix. These include both experience-expectant learning mechanisms that occur during sensitive periods of development and experience-dependent learning mechanisms that may exhibit substantial variation across development. Incorporating these learning mechanisms allows for clear integration not only of development but also environmental experience into the RDoC model. We demonstrate how individual differences in environmental experiences-such as early life adversity-can be leveraged to identify experience-driven plasticity patterns across development and apply this framework to consider how environmental experience shapes key biobehavioral processes that comprise the RDoC model. This framework provides a structure for understanding how affective, cognitive, social, and neurobiological processes are shaped by experience across development and ultimately contribute to the emergence of psychopathology. We demonstrate how incorporating an experience-driven plasticity framework is critical for understanding the development of many processes subsumed within the RDoC model, which will contribute to greater understanding of developmental variation in the etiology of psychopathology and can be leveraged to identify potential windows of heightened developmental plasticity when clinical interventions might be maximally efficacious. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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.

Neural correlates of face processing associated with development of social communication in 12-month infants with familial risk of autism spectrum disorder.

BACKGROUND: Differences in face processing in individuals with ASD is hypothesized to impact the development of social communication skills. This study aimed to characterize the neural correlates of face processing in 12-month-old infants at familial risk of developing ASD by (1) comparing face-sensitive event-related potentials (ERP) (Nc, N290, P400) between high-familial-risk infants who develop ASD (HR-ASD), high-familial-risk infants without ASD (HR-NoASD), and low-familial-risk infants (LR), and (2) evaluating how face-sensitive ERP components are associated with development of social communication skills. METHODS: 12-month-old infants participated in a study in which they were presented with alternating images of their mother's face and the face of a stranger (LR = 45, HR-NoASD = 41, HR-ASD = 24) as EEG data were collected. Parent-reported and laboratory-observed social communication measures were obtained at 12 and 18 months. Group differences in ERP responses were evaluated using ANOVA, and multiple linear regressions were conducted with maternal education and outcome groups as covariates to assess relationships between ERP and behavioral measures. RESULTS: For each of the ERP components (Nc [negative-central], N290, and P400), the amplitude difference between mother and stranger (Mother-Stranger) trials was not statistically different between the three outcome groups (Nc p = 0.72, N290 p = 0.88, P400 p = 0.91). Marginal effects analyses found that within the LR group, a greater Nc Mother-Stranger response was associated with better expressive language skills on the Mullen Scales of Early Learning, controlling for maternal education and outcome group effects (marginal effects dy/dx = 1.15; p < 0.01). No significant associations were observed between the Nc and language or social measures in HR-NoASD or HR-ASD groups. In contrast, specific to the HR-ASD group, amplitude difference between the Mother versus Stranger P400 response was positively associated with expressive (dy/dx = 2.1, p < 0.001) and receptive language skills at 12 months (dy/dx = 1.68, p < 0.005), and negatively associated with social affect scores on the Autism Diagnostic Observation Schedule (dy/dx = - 1.22, p < 0.001) at 18 months. CONCLUSIONS: In 12-month-old infant siblings with subsequent ASD, increased P400 response to Mother over Stranger faces is positively associated with concurrent language and future social skills.

Experimental evidence for a child-to-adolescent switch in human amygdala-prefrontal cortex communication: A cross-sectional pilot study.

Interactions between the amygdala and prefrontal cortex are fundamental to human emotion. Despite the central role of frontoamygdala communication in adult emotional learning and regulation, little is known about how top-down control emerges during human development. In the present cross-sectional pilot study, we experimentally manipulated prefrontal engagement to test its effects on the amygdala during development. Inducing dorsal anterior cingulate cortex (dACC) activation resulted in developmentally-opposite effects on amygdala reactivity during childhood versus adolescence, such that dACC activation was followed by increased amygdala reactivity in childhood but reduced amygdala reactivity in adolescence. Bayesian network analyses revealed an age-related switch between childhood and adolescence in the nature of amygdala connectivity with the dACC and ventromedial PFC (vmPFC). Whereas adolescence was marked by information flow from dACC and vmPFC to amygdala (consistent with that observed in adults), the reverse information flow, from the amygdala to dACC and vmPFC, was dominant in childhood. The age-related switch in information flow suggests a potential shift from bottom-up co-excitatory to top-down regulatory frontoamygdala connectivity and may indicate a profound change in the circuitry supporting maturation of emotional behavior. These findings provide novel insight into the developmental construction of amygdala-cortical connections and implications for the ways in which childhood experiences may influence subsequent prefrontal function.

Parental Language Input Predicts Neuroscillatory Patterns Associated with Language Development in Toddlers at Risk of Autism.

In this study we investigated the impact of parental language input on language development and associated neuroscillatory patterns in toddlers at risk of Autism Spectrum Disorder (ASD). Forty-six mother-toddler dyads at either high (n = 22) or low (n = 24) familial risk of ASD completed a longitudinal, prospective study including free-play, resting electroencephalography, and standardized language assessments. Input quantity/quality at 18 months positively predicted expressive language at 24 months, and relationships were stronger for high-risk toddlers. Moderated mediations revealed that input-language relationships were explained by 24-month frontal and temporal gamma power (30-50 Hz) for high-risk toddlers who would later develop ASD. Results suggest that high-risk toddlers may be cognitively and neurally more sensitive to their language environments, which has implications for early intervention.

Prediction of autism spectrum disorder diagnosis using nonlinear measures of language-related EEG at 6 and 12 months.

BACKGROUND: Early identification of autism spectrum disorder (ASD) provides an opportunity for early intervention and improved developmental outcomes. The use of electroencephalography (EEG) in infancy has shown promise in predicting later ASD diagnoses and in identifying neural mechanisms underlying the disorder. Given the high co-morbidity with language impairment, we and others have speculated that infants who are later diagnosed with ASD have altered language learning, including phoneme discrimination. Phoneme learning occurs rapidly in infancy, so altered neural substrates during the first year of life may serve as early, accurate indicators of later autism diagnosis. METHODS: Using EEG data collected at two different ages during a passive phoneme task in infants with high familial risk for ASD, we compared the predictive accuracy of a combination of feature selection and machine learning models at 6 months (during native phoneme learning) and 12 months (after native phoneme learning), and we identified a single model with strong predictive accuracy (100%) for both ages. Samples at both ages were matched in size and diagnoses (n = 14 with later ASD; n = 40 without ASD). Features included a combination of power and nonlinear measures across the 10­20 montage electrodes and 6 frequency bands. Predictive features at each age were compared both by feature characteristics and EEG scalp location. Additional prediction analyses were performed on all EEGs collected at 12 months; this larger sample included 67 HR infants (27 HR-ASD, 40 HR-noASD). RESULTS: Using a combination of Pearson correlation feature selection and support vector machine classifier, 100% predictive diagnostic accuracy was observed at both 6 and 12 months. Predictive features differed between the models trained on 6- versus 12-month data. At 6 months, predictive features were biased to measures from central electrodes, power measures, and frequencies in the alpha range. At 12 months, predictive features were more distributed between power and nonlinear measures, and biased toward frequencies in the beta range. However, diagnosis prediction accuracy substantially decreased in the larger, more behaviorally heterogeneous 12-month sample. CONCLUSIONS: These results demonstrate that speech processing EEG measures can facilitate earlier identification of ASD but emphasize the need for age-specific predictive models with large sample sizes to develop clinically relevant classification algorithms.

EEG Phase-Amplitude Coupling Strength and Phase Preference: Association with Age over the First Three Years after Birth.

Phase-amplitude coupling (PAC), the coupling of the phase of slower electrophysiological oscillations with the amplitude of faster oscillations, is thought to facilitate dynamic integration of neural activity in the brain. Although the brain undergoes dramatic change and development during the first few years of life, how PAC changes through this developmental period has not been extensively studied. Here, we examined PAC through electroencephalography (EEG) data collected during an awake, eyes-open EEG collection paradigm in 98 children between the ages of three months and three years. We employed non-parametric clustering methods to identify areas of significant PAC across a range of frequency pairs and electrode locations, and examined how PAC strength and phase preference develops in these areas. We found that PAC, primarily between the α-ß and γ frequencies, was positively correlated with age from early infancy to early childhood (p = 2.035 × 10-6). Additionally, we found γ over anterior electrodes coupled with the rising phase of the α-ß waveform, while γ over posterior electrodes coupled with the falling phase of the α-ß waveform; this regionalized phase preference became more prominent with age. This opposing trend may reflect each region's specialization toward feedback or feedforward processing, respectively, suggesting opportunities for back translation in future studies.

Longitudinal changes in amygdala, hippocampus and cortisol development following early caregiving adversity.

Although decades of research have shown associations between early caregiving adversity, stress physiology and limbic brain volume (e.g., amygdala, hippocampus), the developmental trajectories of these phenotypes are not well characterized. In the current study, we used an accelerated longitudinal design to assess the development of stress physiology, amygdala, and hippocampal volume following early institutional care. Previously Institutionalized (PI; N = 93) and comparison (COMP; N = 161) youth (ages 4-20 years old) completed 1-3 waves of data collection, each spaced approximately 2 years apart, for diurnal cortisol (N = 239) and structural MRI (N = 156). We observed a developmental shift in morning cortisol in the PI group, with blunted levels in childhood and heightened levels in late adolescence. PI history was associated with reduced hippocampal volume and reduced growth rate of the amygdala, resulting in smaller volumes by adolescence. Amygdala and hippocampal volumes were also prospectively associated with future morning cortisol in both groups. These results indicate that adversity-related physiological and neural phenotypes are not stationary during development but instead exhibit dynamic and interdependent changes from early childhood to early adulthood.

Use of longitudinal EEG measures in estimating language development in infants with and without familial risk for autism spectrum disorder.

Language development in children with autism spectrum disorder (ASD) varies greatly among affected individuals and is a strong predictor of later outcomes. Younger siblings of children with ASD have increased risk of ASD, but also language delay. Identifying neural markers of language outcomes in infant siblings could facilitate earlier intervention and improved outcomes. This study aimed to determine whether EEG measures from the first 2-years of life can explain heterogeneity in language development in children at low- and high-risk for ASD, and to determine whether associations between EEG measures and language development are different depending on ASD risk status or later ASD diagnosis. In this prospective longitudinal study EEG measures collected between 3-24 months were used in a multivariate linear regression model to estimate participants' 24-month language development. Individual baseline longitudinal EEG measures included (1) the slope of EEG power across 3-12 months or 3-24 months of life for 6 canonical frequency bands, (2) estimated EEG power at age 6-months for the same frequency bands, and (3) terms representing the interaction between ASD risk status and EEG power measures. Modeled 24-month language scores using EEG data from either the first 2-years (Pearson R = 0.70, 95% CI 0.595-0.783, P=1x10-18) or the first year of life (Pearson R=0.66, 95% CI 0.540-0.761, P=2.5x10-14) were highly correlated with observed scores. All models included significant interaction effects of risk on EEG measures, suggesting that EEG-language associations are different depending on risk status, and that different brain mechanisms effect language development in low-versus high-risk infants.

Early Adversity and Critical Periods: Neurodevelopmental Consequences of Violating the Expectable Environment.

It is now widely recognized that children exposed to adverse life events in the first years of life are at increased risk for a variety of neural, behavioral, and psychological sequelae. As we discuss in this paper, adverse events represent a violation of the expectable environment. If such violations occur during a critical period of brain development, the detrimental effects of early adversity are likely to be long lasting. Here we discuss the various ways adversity becomes neurobiologically embedded, and how the timing of such adversity plays an important role in determining outcomes. We conclude our paper by offering recommendations for how to elucidate the neural mechanisms responsible for the behavioral sequelae and how best to model the effects of early adversity.