Oscillatory gamma activity mediates the pathway from socioeconomic status to language acquisition in infancy

Interconnected pathways link faecal microbiota plasma lipids and brain activity to childhood malnutrition related cognition

Malnutrition affects over 30 million children annually and has profound immediate and enduring repercussions. Survivors often suffer lasting neurocognitive consequences that impact academic performance and socioeconomic outcomes. Mechanistic understanding of the emergence of these consequences is poorly understood. Using multi-system SHAP interpreted random forest models and network analysis, we show that Moderate Acute Malnutrition (MAM) associates with enrichment of faecal Rothia mucilaginosa, Streptococcus salivarius and depletion of Bacteroides fragilis in a cohort of one-year-old children in Dhaka, Bangladesh. These microbiome changes form interconnected pathways that involve reduced plasma odd-chain fatty acid levels, decreased gamma and beta electroencephalogram power in temporal and frontal brain regions, and reduced vocalization. These findings support the hypothesis that prolonged colonization by oral commensal species delay gut microbiome and brain development. While causal links require empirical validation, this study provides insights to improve interventions targeting MAM-associated neurodevelopmental deficits.

Looking for social pragmatic communication disorder in the complex world of Italian special needs: an exploratory study

Social Pragmatic Communication Disorder (SPCD) is characterised by a number of pragmatic difficulties and may lead to obstacles in school readiness. These difficulties also apply to children with Special Needs. Several authors pointed out the difficulty to detect SPCD, also considering the lack of sensitive assessment tools. The aim of this study is to investigate the pragmatic ability of children with BES not otherwise specified (BES-NOS), compared to a control group of children with Typical Development (TD) using the Assessment Battery for Communication (ABaCo). Our expectation is that BES-NOS perform worse than children with TD. Furthermore, for exploratory purposes, we investigate whether it is possible to identify a subgroup of children with undiagnosed SPCD within the BES-NOS group, by performing a cluster analysis. Our results show that children with BES have a significantly lower pragmatic performance than the TD group and suggest the sensitivity of ABaCo in identifying individuals with undiagnosed SPCD among children and adolescents with BES-NOS.

Socioeconomic status (SES) and cognitive outcomes are predicted by resting-state EEG in school-aged children

Children's socioeconomic status (SES) is related to patterns of intrinsic resting-state brain function that subserve relevant cognitive processes over the course of development. Although infant research has demonstrated the association between children's environments, cognitive outcomes, and resting-state electroencephalography (rsEEG), it remains unknown how these aspects of their environment, tied to SES, impact neural and cognitive development throughout the school years. To address this gap, we applied a multivariate pattern analysis (MVPA) to rsEEG data to identify which neural frequencies at rest are differentially associated with unique aspects of socioeconomic status (SES; income and maternal education) and cognitive (vocabulary, working memory) outcomes among school-aged children (8-15 years). We find that the alpha frequency is associated with both income and maternal education, while lower gamma and theta fluctuations are tied to dissociable aspects of SES and cognitive outcomes. Specifically, changes in the gamma frequency are predictive of both maternal education and vocabulary outcome, while changes in the theta frequency are related to both income and working memory ability. The current findings extend our understanding of unique pathways by which SES influences cognitive and neural development in school-aged children.

Ear to the ground! socioeconomic status, environmental stress, and the neural substrate of selective attention

We reanalyzed data originally published by Berman and Friedman (1995), who recorded event related potentials (ERPs) while children and adults with low, medium, and high socioeconomic status (SES) detected oddball auditory targets (tones and consonant-vowel sequences) among distractors. The ERP differential measuring how much attention was allocated to the targets vs. distractors increased significantly with SES, independently of age. To explain these findings, we integrate the ear to the ground hypothesis and the socioenvironmental epigenetic stress approach. According to the ear to the ground hypothesis, frequent and prolonged environmental uncertainty and hazard induce low-SES children to learn adaptive over-vigilance, attending disproportionately to stimuli that are currently irrelevant but may quickly become relevant and thus require an immediate survival response. Socioenvironmental epigenetic stress refers to the bidirectional interaction between a stress-inducing environment and the impact and expression of transgenerational gene selections in low-SES contexts. Because low-SES individuals are historically under and misrepresented in research, the proposed framework contributes to increase our understanding of how socioeconomic and environmental conditions may affect neurocognitive development. This offers significant points of entry for future interventions and policies targeting macrosocial settings (i.e., education and the justice system) and microsocial ontogenetic settings (i.e., individuals and families).

Structural inequality and temporal brain dynamics across diverse samples

BACKGROUND

Structural income inequality - the uneven income distribution across regions or countries - could affect brain structure and function, beyond individual differences. However, the impact of structural income inequality on the brain dynamics and the roles of demographics and cognition in these associations remains unexplored.

METHODS

Here, we assessed the impact of structural income inequality, as measured by the Gini coefficient on multiple EEG metrics, while considering the subject-level effects of demographic (age, sex, education) and cognitive factors. Resting-state EEG signals were collected from a diverse sample (countries = 10; healthy individuals = 1394 from Argentina, Brazil, Colombia, Chile, Cuba, Greece, Ireland, Italy, Turkey and United Kingdom). Complexity (fractal dimension, permutation entropy, Wiener entropy, spectral structure variability), power spectral and aperiodic components (1/f slope, knee, offset), as well as graph-theoretic measures were analysed.

FINDINGS

Despite variability in samples, data collection methods, and EEG acquisition parameters, structural inequality systematically predicted electrophysiological brain dynamics, proving to be a more crucial determinant of brain dynamics than individual-level factors. Complexity and aperiodic activity metrics captured better the effects of structural inequality on brain function. Following inequality, age and cognition emerged as the most influential predictors. The overall results provided convergent multimodal metrics of biologic embedding of structural income inequality characterised by less complex signals, increased random asynchronous neural activity, and reduced alpha and beta power, particularly over temporoposterior regions.

CONCLUSION

These findings might challenge conventional neuroscience approaches that tend to overemphasise the influence of individual-level factors, while neglecting structural factors. Results pave the way for neuroscience-informed public policies aimed at tackling structural inequalities in diverse populations.

Is frontal EEG gamma power a neural correlate of language in toddlerhood? An examination of late talking and expressive language ability

Few studies have examined neural correlates of late talking in toddlers, which could aid in understanding etiology and improving diagnosis of developmental language disorder (DLD). Greater frontal gamma activity has been linked to better language skills, but findings vary by risk for developmental disorders, and this has not been investigated in late talkers. This study examined whether frontal gamma power (30-50 Hz), from baseline-state electroencephalography (EEG), was related to DLD risk (categorical late talking status) and a continuous measure of expressive language in n = 124 toddlers. Frontal gamma power was significantly associated with late talker status when controlling for demographic factors and concurrent receptive language (β = 1.96, McFadden's Pseudo R2 = 0.21). Demographic factors and receptive language did not significantly moderate the association between frontal gamma power and late talker status. A continuous measure of expressive language ability was not significantly associated with gamma (r = -0.07). Findings suggest that frontal gamma power may be useful in discriminating between groups of children that differ in DLD risk, but not for expressive language along a continuous spectrum of ability.

Early Family Experiences and Neural Activity in Rural Pakistani Children: The Differential Role of Gender

Adversity within low- and middle-income countries (LMICs) poses severe threats to neurocognitive development, which can be partially mitigated by high-quality early family experiences. Specifically, maternal scaffolding and home stimulation can buffer cognitive development in LMIC, possibly by protecting underlying neural functioning. However, the association between family experiences and neural activity remains largely unexplored in LMIC contexts. This study explored the relation of early family experiences to later cognitive skills and absolute gamma power (21-45 Hz), a neural marker linked to higher-order cognitive skills. Drawing data from the PEDS trial, a longitudinal study in rural Pakistan, we examined maternal scaffolding at 24 months and home stimulation quality at 18 months as predictors of verbal IQ, executive functions, and absolute gamma at 48 months for 105 mother-child dyads (52 girls). Maternal scaffolding interacted with gender to predict absolute gamma power, such that higher maternal scaffolding was related to higher gamma more strongly for girls. Maternal scaffolding also interacted with absolute gamma to predict executive functions, such that higher gamma was related to better executive functions only when maternal scaffolding was average to high. Individual differences in early family experiences may partially buffer the neural underpinnings of cognitive skills from adversity in LMIC.

EEG Functional Connectivity Analysis for the Study of the Brain Maturation in the First Year of Life

Brain networks are hypothesized to undergo significant changes over development, particularly during infancy. Thus, the aim of this study is to evaluate brain maturation in the first year of life in terms of electrophysiological (EEG) functional connectivity (FC). Whole-brain FC metrics (i.e., magnitude-squared coherence, phase lag index, and parameters derived from graph theory) were extracted, for multiple frequency bands, from baseline EEG data recorded from 146 typically developing infants at 6 (T6) and 12 (T12) months of age. Generalized linear mixed models were used to test for significant differences in the computed metrics considering time point and sex as fixed effects. Correlational analyses were performed to ascertain the potential relationship between FC and subjects' cognitive and language level, assessed with the Bayley-III scale at 24 (T24) months of age. The results obtained highlighted an increased FC, for all the analyzed frequency bands, at T12 with respect to T6. Correlational analyses yielded evidence of the relationship between FC metrics at T12 and cognition. Despite some limitations, our study represents one of the first attempts to evaluate brain network evolution during the first year of life while accounting for correspondence between functional maturation and cognitive improvement.

Prenatal family income, but not parental education, is associated with resting brain activity in 1-month-old infants

Childhood socioeconomic disadvantage is associated with disparities in development and health, possibly through adaptations in children's brain function. However, it is not clear how early in development such neural adaptations might emerge. This study examined whether prenatal family socioeconomic status, operationalized as family income and average years of parental education, prospectively predicts individual differences in infant resting electroencephalography (EEG; theta, alpha, beta, and gamma power) at approximately 1 month of age (N = 160). Infants of mothers reporting lower family income showed more lower-frequency (theta) and less higher-frequency (beta and gamma) power. These associations held when adjusting for other prenatal and postnatal experiences, as well as infant demographic and health-related factors. In contrast, parental education was not significantly associated with infant EEG power in any frequency band. These data suggest that lower prenatal family income is associated with developmental differences in brain function that are detectable within the first month of life.

Visual statistical learning in preverbal infants at a higher likelihood of autism and its association with later social communication skills

Visual statistical Learning (SL) allows infants to extract the statistical relationships embedded in a sequence of elements. SL plays a crucial role in language and communication competencies and has been found to be impacted in Autism Spectrum Disorder (ASD). This study aims to investigate visual SL in infants at higher likelihood of developing ASD (HL-ASD) and its predictive value on autistic-related traits at 24-36 months. At 6 months of age, SL was tested using a visual habituation task in HL-ASD and neurotypical (NT) infants. All infants were habituated to a visual sequence of shapes containing statistically predictable patterns. In the test phase, infants viewed the statistically structured, familiar sequence in alternation with a novel sequence that did not contain any statistical information. HL-ASD infants were then evaluated at 24-36 months to investigate the associations between visual SL and ASD-related traits. Our results showed that NT infants were able to learn the statistical structure embedded in the visual sequences, while HL-ASD infants showed different learning patterns. A regression analysis revealed that SL ability in 6-month-old HL-ASD infants was related to social communication and interaction abilities at 24-36 months of age. These findings indicate that early differences in learning visual statistical patterns might contribute to later social communication skills.

The Necessity of Taking Culture and Context into Account When Studying the Relationship between Socioeconomic Status and Brain Development

Decades of research has revealed a relationship between childhood socioeconomic status (SES) and brain development at the structural and functional levels. Of particular note is the distinction between income and maternal education, two highly correlated factors which seem to influence brain development through distinct pathways. Specifically, while a families' income-to-needs ratio is linked with physiological stress and household chaos, caregiver education influences the day-to-day language environment a child is exposed to. Variability in either one of these environmental experiences is related to subsequent brain development. While this work has the potential to inform public policies in a way that benefits children, it can also oversimplify complex factors, unjustly blame low-SES parents, and perpetuate a harmful deficit perspective. To counteract these shortcomings, researchers must consider sociodemographic differences in the broader cultural context that underlie SES-based differences in brain development. This review aims to address these issues by (a) identifying how sociodemographic mechanisms associated with SES influence the day-to-day experiences of children, in turn, impacting brain development, while (b) considering the broader cultural contexts that may differentially impact this relationship.

Resting EEG correlates of neurodevelopment in a socioeconomically and linguistically diverse sample of toddlers: Wave 1 of the Kia Tīmata Pai best start New Zealand study

Development of communication and self-regulation skills is fundamental to psychosocial maturation in childhood. The Kia Tīmata Pai Best Start (KTP) longitudinal study aims to promote these skills through interventions delivered at early childcare centers across New Zealand. In addition to evaluating effects of the interventions on behavioral and cognitive outcomes, the study utilizes electroencephalography (EEG) to characterize cortical development in a subsample of participating children. Here, we present results of the baseline resting EEG assessment with 193 children aged 15 to 33 months. We identified EEG correlates of individual differences in demographics, communication abilities, and temperament. We obtained communication and behavior ratings from multiple informants, and we applied contemporary analytic methods to the EEG data. Periodic spectral power adjusted for aperiodic activity was most closely associated with demographic, language, and behavioral measures. As in previous studies, gamma power was positively associated with verbal language. Alpha power was positively associated with effortful control. Nonverbal and verbal language measures showed distinct associations with EEG indices, as did the three temperament domains. Our results identified a number of candidate EEG measurements for use as longitudinal markers of optimal cortical development and response to interventions in the KTP cohort.

Development of Gamma Oscillation during Sentence Processing in Early Adolescence: Insights into the Maturation of Semantic Processing

Children's ability to retrieve word meanings and incorporate them into sentences, along with the neural structures that support these skills, continues to evolve throughout adolescence. Theta (4-8 Hz) activity that corresponds to word retrieval in children decreases in power and becomes more localized with age. This bottom-up word retrieval is often paired with changes in gamma (31-70 Hz), which are thought to reflect semantic unification in adults. Here, we studied gamma engagement during sentence processing using EEG time-frequency in children (ages 8-15) to unravel the developmental trajectory of the gamma network during sentence processing. Children heavily rely on semantic integration for sentence comprehension, but as they mature, semantic and syntactic processing units become distinct and localized. We observed a similar developmental shift in gamma oscillation around age 11, with younger groups (8-9 and 10-11) exhibiting broadly distributed gamma activity with higher amplitudes, while older groups (12-13 and 14-15) exhibited smaller and more localized gamma activity, especially over the left central and posterior regions. We interpret these findings as support for the argument that younger children rely more heavily on semantic processes for sentence comprehension than older children. And like adults, semantic processing in children is associated with gamma activity.

Baseline EEG in the first year of life: Preliminary insights into the development of autism spectrum disorder and language impairments

Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping symptoms. This study aims to characterize baseline electroencephalography (EEG) spectral power in 6- and 12-month-old infants at higher likelihood of developing ASD and LLI, compared to typically developing infants, and to preliminarily verify if spectral power components associated with the risk status are also linked with the later ASD or LLI diagnosis. We found risk status for ASD to be associated with reduced power in the low-frequency bands and risk status for LLI with increased power in the high-frequency bands. Interestingly, later diagnosis shared similar associations, thus supporting the potential role of EEG spectral power as a biomarker useful for understanding pathophysiology and classifying diagnostic outcomes.

Neural mechanisms of language development in infancy

Understanding the neural processes underpinning individual differences in early language development is of increasing interest, as it is known to vary in typical development and to be quite heterogeneous in neurodevelopmental conditions. However, few studies to date have tested whether early brain measures are indicative of the developmental trajectory of language, as opposed to language outcomes at specific ages. We combined recordings from two longitudinal studies, including typically developing infants without a family history of autism, and infants with increased likelihood of developing autism (infant-siblings) (N = 191). Electroencephalograms (EEG) were recorded at 6 months, and behavioral assessments at 6, 12, 18, 24 and 36 months of age. Using a growth curve model, we tested whether absolute EEG spectral power at 6 months was associated with concurrent language abilities, and developmental change in language between 6 and 36 months. We found evidence of an association between 6-month alpha-band power and concurrent, but not developmental change in, expressive language ability in both infant-siblings and control infants. The observed association between 6-month alpha-band power and 6-month expressive language was not moderated by group status, suggesting some continuity in neural mechanisms.

Infants aged 12 months use the gender feature in determiners to anticipate upcoming words: an eye-tracking study

We investigated online early comprehension in Italian children aged 12 and 20 months, focusing on the role of morphosyntactic features (i.e., gender) carried by determiners in facilitating comprehension and anticipating upcoming words. A naturalistic eye-tracking procedure was employed, recording looking behaviours during a classical Looking-While-Listening task. Children were presented with sentences and pictures of two objects representing nouns characterised by either the same gender (determiner was uninformative) or a different gender (determiner was informative). As expected, 20-month-old children recognised the target picture when this was named, and they were faster in the different-gender condition. Interestingly, 12-month-old infants identified the target picture only when presented with an informative determiner (different-gender condition). These results suggest that, as early as 12 months of age and with an improvement seen at 20 months of age, toddlers can extract and use determiner gender features to enhance comprehension and make predictions about upcoming words.

Associations between EEG trajectories, family income, and cognitive abilities over the first two years of life

We sought to characterize developmental trajectories of EEG spectral power over the first 2 years after birth and examine whether family income or maternal education alter those trajectories. We analyzed EEGs (n = 161 infants, 534 EEGs) collected longitudinally between 2 and 24 months of age, and calculated frontal absolute power across 7 canonical frequency bands. For each frequency band, a piecewise growth curve model was fit, resulting in an estimated intercept and two slope parameters from 2 to 9 months and 9-24 months of age. Across 6/7 frequency bands, absolute power significantly increased over age, with steeper slopes in the 2-9 month period compared to 9-24 months. Increased family income, but not maternal education, was associated with higher intercept (2-3 month power) across delta-gamma bands (p range = 0.002-0.04), and reduced change in power between 2 and 9 months of age in lower frequency bands (delta-alpha, p range = 0.01-0.02). There was no significant effect of income on slope between 9 and 24 months. EEG intercept and slope measures did not mediate relationships between income and 24-month verbal and nonverbal development. These results add to growing literature concerning the role of socioeconomic factors in shaping brain trajectories.

Prenatal Stress and the Developing Brain: Postnatal Environments Promoting Resilience

Heightened maternal stress during pregnancy is associated with atypical brain development and an elevated risk for psychopathology in offspring. Supportive environments during early postnatal life may promote brain development and reverse atypical developmental trajectories induced by prenatal stress. We reviewed studies focused on the role of key early environmental factors in moderating associations between prenatal stress exposure and infant brain and neurocognitive outcomes. Specifically, we focused on the associations between parental caregiving quality, environmental enrichment, social support, and socioeconomic status with infant brain and neurocognitive outcomes. We examined the evidence that these factors may moderate the effects of prenatal stress on the developing brain. Complementing findings from translational models, human research suggests that high-quality early postnatal environments are associated with indices of infant neurodevelopment that have also been associated with prenatal stress, such as hippocampal volume and frontolimbic connectivity. Human studies also suggest that maternal sensitivity and higher socioeconomic status may attenuate the effects of prenatal stress on established neurocognitive and neuroendocrine mediators of risk for psychopathology, such as hypothalamic-pituitary-adrenal axis functioning. Biological pathways that may underlie the effects of positive early environments on the infant brain, including the epigenome, oxytocin, and inflammation, are also discussed. Future research in humans should examine resilience-promoting processes in relation to infant brain development using large sample sizes and longitudinal designs. The findings from this review could be incorporated into clinical models of risk and resilience during the perinatal period and used to design more effective early programs that reduce risk for psychopathology.

Perinatal and early childhood biomarkers of psychosocial stress and adverse experiences

The human brain develops through a complex interplay of genetic and environmental influences. During critical periods of development, experiences shape brain architecture, often with long-lasting effects. If experiences are adverse, the effects may include the risk of mental and physical disease, whereas positive environments may increase the likelihood of healthy outcomes. Understanding how psychosocial stress and adverse experiences are embedded in biological systems and how we can identify markers of risk may lead to discovering new approaches to improve patient care and outcomes. Biomarkers can be used to identify specific intervention targets and at-risk children early when physiological system malleability increases the likelihood of intervention success. However, identifying reliable biomarkers has been challenging, particularly in the perinatal period and the first years of life, including in preterm infants. This review explores the landscape of psychosocial stress and adverse experience biomarkers. We highlight potential benefits and challenges of identifying risk clinically and different sub-signatures of stress, and in their ability to inform targeted interventions. Finally, we propose that the combination of preterm birth and adversity amplifies the risk for abnormal development and calls for a focus on this group of infants within the field of psychosocial stress and adverse experience biomarkers. IMPACT: Reviews the landscape of biomarkers of psychosocial stress and adverse experiences in the perinatal period and early childhood and highlights the potential benefits and challenges of their clinical utility in identifying risk status in children, and in developing targeted interventions. Explores associations between psychosocial stress and adverse experiences in childhood with prematurity and identifies potential areas of assessment and intervention to improve outcomes in this at-risk group.

Resting state electroencephalography (EEG) correlates with children's language skills: Evidence from sentence repetition

Spontaneous neural oscillatory activity reflects the brain's functional architecture and has previously been shown to correlate with perceptual, motor and executive skills. The current study used resting state electroencephalography to examine the relationship between spontaneous neural oscillatory activity and children's language skills. Participants in the study were 52 English-speaking children aged around 10-years. Language was assessed using a sentence repetition task. The main analysis revealed resting state theta power negatively correlated with this task. No significant correlations were found in the other studied frequency bands (delta, alpha, beta, gamma). As part of typical brain development, spontaneous theta power declines across childhood and adolescence. The negative correlation observed in this study may therefore be indicating children's language skills are related to the maturation of theta oscillations. More generally, the study provides further evidence that oscillatory activity in the developing brain, even at rest, is reliably associated with children's language skills.

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.

The impact of a poverty reduction intervention on infant brain activity

This study demonstrates the causal impact of a poverty reduction intervention on early childhood brain activity. Data from the Baby’s First Years study, a randomized control trial, show that a predictable, monthly unconditional cash transfer given to low-income families may have a causal impact on infant brain activity. In the context of greater economic resources, children’s experiences changed, and their brain activity adapted to those experiences. The resultant brain activity patterns have been shown to be associated with the development of subsequent cognitive skills.

Early childhood poverty is a risk factor for lower school achievement, reduced earnings, and poorer health, and has been associated with differences in brain structure and function. Whether poverty causes differences in neurodevelopment, or is merely associated with factors that cause such differences, remains unclear. Here, we report estimates of the causal impact of a poverty reduction intervention on brain activity in the first year of life. We draw data from a subsample of the Baby’s First Years study, which recruited 1,000 diverse low-income mother–infant dyads. Shortly after giving birth, mothers were randomized to receive either a large or nominal monthly unconditional cash gift. Infant brain activity was assessed at approximately 1 y of age in the child’s home, using resting electroencephalography (EEG; n = 435). We hypothesized that infants in the high-cash gift group would have greater EEG power in the mid- to high-frequency bands and reduced power in a low-frequency band compared with infants in the low-cash gift group. Indeed, infants in the high-cash gift group showed more power in high-frequency bands. Effect sizes were similar in magnitude to many scalable education interventions, although the significance of estimates varied with the analytic specification. In sum, using a rigorous randomized design, we provide evidence that giving monthly unconditional cash transfers to mothers experiencing poverty in the first year of their children’s lives may change infant brain activity. Such changes reflect neuroplasticity and environmental adaptation and display a pattern that has been associated with the development of subsequent cognitive skills.

Systemic inflammation during the first year of life is associated with brain functional connectivity and future cognitive outcomes

The first years of life are a sensitive period of rapid neural and immune system development vulnerable to the impact of adverse experiences. Several studies support inflammation as a consequence of various adversities and an exposure negatively associated with developmental outcomes. The mechanism by which systemic inflammation may affect brain development and later cognitive outcomes remains unclear. In this longitudinal cohort study, we examine the associations between recurrent systemic inflammation, defined as C-reactive protein elevation on ≥ 2 of 4 measurements across the first year of life, electroencephalography (EEG) functional connectivity (FC) at 36 months, and composite cognitive outcomes at 3, 4, and 5 years among 122 children living in a limited-resource setting in Dhaka, Bangladesh. Recurrent systemic inflammation during the first year of life is significantly negatively associated with cognitive outcomes at 3, 4, and 5 years, after accounting for stunting and family care indicators (a measure of stimulation in the home environment). Recurrent systemic inflammation is significantly positively associated with parietal-occipital FC in the Beta band at 36 months, which in turn is significantly negatively associated with composite cognitive scores at 3 and 4 years. However, FC does not mediate the relationship between recurrent systemic inflammation and cognitive outcomes.

Atypical ERP responses to audiovisual speech integration and sensory responsiveness in infants at risk for autism spectrum disorder

Atypical sensory responses are included in the diagnostic criteria of autism spectrum disorder (ASD). Autistic individuals perform poorly during conditions that require integration across multiple sensory modalities such as audiovisual (AV) integration. Previous research investigated neural processing of AV integration in infancy. Yet, this has never been studied in infants at higher likelihood of later ASD (HR) using neurophysiological (EEG/ERP) techniques. In this study, we investigated whether ERP measures of AV integration differentiate HR infants from low-risk (LR) infants and whether early AV integration abilities are associated with clinical measures of sensory responsiveness. At age 12 months, AV integration in HR (n = 21) and LR infants (n = 19) was characterized in a novel ERP paradigm measuring the McGurk effect, and clinical measures of sensory responsiveness were evaluated. Different brain responses over the left temporal area emerge between HR and LR infants, specifically when AV stimuli cannot be integrated into a fusible percept. Furthermore, ERP responses related to integration of AV incongruent stimuli were found to be associated with sensory responsiveness, with reduced effects of AV incongruency being associated with reduced sensory reactivity. These data suggest that early identification of AV deficits may pave the way to innovative therapeutic strategies for the autistic symptomatology. Further replications in independent cohorts are needed for generalizability of findings.

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 10‑20 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.

Associations of socioeconomic and other environmental factors with early brain development in Bangladeshi infants and children

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Research from high-income countries shows that experiences impact neural development.

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We examine EEG in relation to wealth and psychosocial factors in 6 and 36-month-olds from Bangladesh.

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Wealth and maternal stress is associated with EEG oscillations in 36-month-olds.

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Neither wealth nor maternal stress is associated with EEG oscillations in 6-month-olds.

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Environmental influences on EEG may emerge between 6 and 36 months of age.

Studies of infants growing up in high-income countries reveal developmental changes in electroencephalography (EEG) power whereby socioeconomic factors - specifically, low SES and low income - are associated with lower EEG power in infants aged newborn to nine months. In the current paper we explore relationships of spectral EEG power across three regions (frontal, central, and parietal) and four frequency bands (theta, alpha, beta, and gamma) with socioeconomic and psychosocial factors in a cohort of n = 160 6-month-old infants and n = 187 36-month-old children living in Dhaka, Bangladesh. Household wealth is assessed as a multi-dimensional composite score encompassing income, assets, and housing materials. Psychosocial factors include maternal perceived stress and family caregiving activities. Among the 6-month-old infants we do not observe any association of household wealth or psychosocial factors with EEG power. Among the 36-month-old children, we find that household wealth is negatively associated absolute power in the beta and gamma bands across frontal, central, and parietal electrodes. We also find that higher reports of maternal perceived stress are associated with more absolute theta power in frontal and central regions in the 36-month-old children. The finding of a negative relationship of household wealth with beta and gamma power in 36-month-old children differs from findings previously observed in infants in high-income countries. Overall, findings suggest that children’s environment continues to influence the development of EEG oscillations and provide support for the utility of EEG to quantify developmental effects of early life experiences on neural functional outcomes in low income countries.

Detection without further processing or processing without automatic detection? Differential ERP responses to lexical-semantic processing in toddlers at high clinical risk for autism and language disorder

Delays in early expressive vocabulary can reflect a specific delay in language acquisition or more general impairments in social communication. The neural mechanisms underlying the (dis)ability to establish the first lexical-semantic representations remain relatively unknown. Here, we investigate the electrophysiological underpinnings of these mechanisms during the critical phase of lexical acquisition in two groups of 19-month-old toddlers at risk for neurodevelopmental disorders, i.e., children characterized by low expressive vocabulary (late talkers, N = 18) and children with early signs of Autism Spectrum Disorder (ASD, N = 18) as compared to typically developing children (N = 28), with the aim to identify similarities and specificities in lexical-semantic processing between these groups. ERPs elicited by words (either congruous or incongruous with the previous picture context) and pseudo-words are investigated within a picture-word matching paradigm. In order to further interpret ERP responses, we look at longitudinal intra-group associations with language and socio-communications skills at age 24 months. As expected, we found differences between the groups that might underlie specificities, but also similarities. On the one side, late talkers differed from the other two groups in the early component (phonological-lexical priming effect) reflecting detection of the correspondence between the heard word and the lexical representation pre-activated by the picture. On the other side, children with early symptoms of ASD differed from the other two groups in the late component (late positive component) reflecting the effortful semantic re-analysis following a violation. The functional interpretation of the two components is corroborated by significant correlations suggesting that the early component is associated with later socio-communication skills, whereas the late component is associated with linguistic skills. Results point in the direction of differential impaired mechanisms in the two populations, i.e., impaired automatic detection of incongruencies in late talkers vs. absence of high-level re-analysis of such incongruencies in children with early signs of ASD.

Childhood disadvantage, neurocognitive development and neuropsychiatric disorders: Evidence of mechanisms

PURPOSE OF REVIEW

Children living in socioeconomically disadvantaged households have excess risks of neurodevelopmental and neuropsychiatric problems. The purpose of this review is to synthesize evidence for mechanisms that may contribute to these excess risks.

RECENT FINDINGS

The majority of the 60 studies included in our review focused on children's neurocognitive development and behavioural problems. About half conducted mediation analyses of factors in the family and neighbourhood environments, including access to resources (e.g. cognitive inputs within the home environment) and exposure to stressors (e.g. negative parenting practices), as well as neurobiological embedding of childhood disadvantage. In addition, many studies conducted moderation analyses of factors that were hypothesized to interact with (i.e. exacerbate or mitigate) the harmful effects of childhood disadvantage.

SUMMARY

Many of the factors that contribute to the excess risk of neurodevelopmental and neuropsychiatric problems among children in disadvantaged households are potentially modifiable (e.g. cognitively stimulating materials, parental language input, cultural resources, parental stress and psychopathology, negative parenting, neighbourhood violence). If their causality is ultimately established, they could be targets for the prevention and reduction of disparities. The continued search for mechanisms should not detract from work to reduce and hopefully eliminate children's exposure to disadvantage.

Effects of COVID-19 Lockdown on the Emotional and Behavioral Profiles of Preschool Italian Children with and without Familial Risk for Neurodevelopmental Disorders

The effects of COVID-19 containment measures on the emotional and behavioral development of preschoolers are not clear. We investigated them within an ongoing longitudinal project including typically developing children (TD) and children at high familial risk for neurodevelopmental disorders (HR-NDD) who were potentially more vulnerable. The study included ninety children aged 2-6 years (TD = 48; HR-NDD = 42). Before the emergency phase (T0), all children received a clinical assessment, including the parent questionnaire Child Behavior Checklist for Ages 1.5-5 (CBCL 1.5-5). The same questionnaire was filled out again during the emergency (T1), together with an ad-hoc questionnaire investigating environmental factors characterizing the specific period. Changes in the CBCL profiles between T0 and T1 were evaluated. Overall, irrespective of familial risk, the average T-scores on specific CBCL scales at T1 were higher than at T0. Associations emerged between delta scores reflecting worsening scores on specific CBCL scales and clinical and environmental factors. Our results confirmed the negative impact of the lockdown on preschool children's emotional/behavioral profiles, and highlight the need for strategic approaches in the age range of 2-6 years, especially for more susceptible children owing to environmental factors and pre-existing emotional problems.

Maternal stress predicts neural responses during auditory statistical learning in 26-month-old children: An event-related potential study

Exposure to high levels of early life stress have been associated with long-term difficulties in learning, behavior, and health, with particular impact evident in the language domain. While some have proposed that the increased stress of living in a low-income household mediates observed associations between socioeconomic status (SES) and child outcomes, considerable individual differences have been observed. The extent to which specific variables associated with socioeconomic status - in particular exposure to stressful life events - influence the neurocognitive mechanisms underlying language acquisition are not well understood. Auditory statistical learning, or the ability to segment a continuous auditory stream based on its statistical properties, develops during early infancy and is one mechanism thought to underlie language learning. The present study used an event-related potential (ERP) paradigm to test whether maternal stress, adjusting for socioeconomic variables (e.g., family income, maternal education) was associated with neurocognitive processes underlying statistical learning in a sample of 26-month-old children (n = 23) from predominantly low- to middle-income backgrounds. Event-related potentials were recorded while children listened to a continuous stream of tri-tone "words" in which tone elements varied in transitional probability. "Tone-words" were presented in random order, such that Tone 1 always predicted Tones 2 and 3 (transitional probability for Tone 3 = 1.0), but Tone 1 appeared randomly. A larger P2 amplitude was observed in response to Tone 3 compared to Tone 1, demonstrating that children implicitly tracked differences in transitional probabilities during passive listening. Maternal reports of stress at 26 months, adjusting for SES, were negatively associated with difference in P2 amplitude between Tones 1 and 3. These findings suggest that maternal stress, within a low-SES context, is associated with the manner in which children process statistical properties of auditory input.

The Neuroscience of Socioeconomic Inequality

A burgeoning literature has recently begun investigating the links between socioeconomic inequality and the developing brain. This work suggests widespread disparities in both brain structure and function that begin as early as the first year of life. Here we review disparities in neural structure that have been reported in both cortical and subcortical gray matter, as well as in white matter. Disparities in brain function have also been reported, particularly in circuits that support language, memory, executive functioning, and emotion processing. We additionally review recent work investigating the mechanisms that underlie socioeconomic disparities in brain development. Taken together, this work has the potential to identify important targets for intervention in policy and practice.

Paternal-but Not Maternal-Autistic Traits Predict Frontal EEG Alpha Asymmetry in Infants with Later Symptoms of Autism

Previous research found that the parental autism phenotype is associated with child autism spectrum disorder (ASD), even if the pathway between autistic traits in parents and child ASD is still largely unknown. Several studies investigated frontal asymmetry in alpha oscillation (FAA) as an early marker for ASD. However, no study has examined the mediational effect of FAA between parental autistic traits and child ASD symptoms in the general population. We carried out a prospective study of 103 typically developing infants and measured FAA as a mediator between both maternal and paternal autistic traits and child ASD traits. We recorded infant baseline electroencephalogram (EEG) at 6 months of age. Child ASD symptoms were measured at age 24 months by the Child Behavior Checklist 1½-5 Pervasive Developmental Problems Scale, and parental autistic traits were scored by the Autism spectrum Quotient questionnaire. The mediation model showed that paternal vs. maternal autistic traits are associated with greater left FAA which, in turn, is associated with more child ASD traits with a significant indirect effect only in female infants vs. male infants. Our findings show a potential cascade of effects whereby paternal autistic traits drive EEG markers contributing to ASD risk.