Socioeconomic disparities and neuroplasticity: Moving toward adaptation, intersectionality, and inclusion

Relations among Socioeconomic Status, Perceived Stress, and the Home Language Environment

While socioeconomic disparities in the home language environment have been well established, the mechanisms explaining these disparities are poorly understood. One plausible mechanism is heightened stress. The current study investigated whether maternal perceived stress was 1) associated with measures of the home language environment, and 2) mediated the relation between socioeconomic disparities and the home language environment. Data from three independent studies were analyzed, which together comprised 322 mother-child dyads. Two studies included mothers and their six- to twelve-month-old infants (N = 227). The third included mothers and their five- to nine-year-old children (N = 95). Mothers reported their educational attainment, income, and stress. Language Environment Analysis (LENA) measured the home language environment. As has been previously reported, socioeconomic disparities were observed in adult words and conversational turns. Stress did not mediate these associations, nor was it associated with adult words or conversational turns. Alternate mechanisms for future exploration are discussed.

Mothers with low incomes view both individual and structural interventions as potentially helpful for supporting early child development

Many developmental psychologists aspire to conduct research that informs interventions and policies to prevent income-related disparities in child development. Among growing researcher discussion about the value of interventions that target "structural" and resource-related correlates of income inequality and child development (e.g., housing, food, material goods, cash), rather than individual, person-centered correlates (e.g., parenting behaviors), the perspectives of mothers with low incomes may provide important context. 281 mothers with young children and low incomes rated various structural and individual interventions, framed as having minimal costs and entry barriers, for their perceived helpfulness. Analyses were pre-registered. Overall, mothers rated all interventions very highly, though they rated structural interventions as slightly more helpful than individual interventions. Mothers rated interventions they used in the past as less helpful than those they hadn't previously used. An exploratory qualitative analysis revealed mothers' desires for supports in other intervention domains beyond those addressed in our survey. Together, mothers' responses indicated that they did not see individual interventions as inherently unhelpful due to a focus on individual states, knowledge, and skills. Implications for developmental psychology and intervention science are discussed.

Diversity-aware Population Models: Quantifying Associations between Socio-Spatial Factors and Cognitive Development in the ABCD Cohort

Population-level analyses are inherently complex due to a myriad of latent confounding effects that underlie the interdisciplinary topics of research interest. Despite the mounting demand for generative population models, the limited generalizability to underrepresented groups hinders their widespread adoption in downstream applications. Interpretability and reliability are essential for clinicians and policymakers, while accuracy and precision are prioritized from an engineering standpoint. Thus, in domains such as population neuroscience, the challenge lies in determining a suitable approach to model population data effectively. Notably, the traditional strata-agnostic nature of existing methods in this field reveals a pertinent gap in quantitative techniques that directly capture major sources of population stratification. The emergence of population-scale cohorts, like the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study, provides unparalleled opportunities to explore and characterize neurobehavioral and sociodemographic relationships comprehensively. We propose diversity-aware population modeling, a framework poised to standardize systematic incorporation of diverse attributes, structured with respect to intrinsic population stratification to obtain holistic insights. Here, we leverage Bayesian multilevel regression and poststratification, to elucidate inter-individual differences in the relationships between socioeconomic status (SES) and cognitive development. We constructed 14 varying-intercepts and varying-slopes models to investigate 3 cognitive phenotypes and 5 sociodemographic variables (SDV), across 17 US states and 5 race subgroups. SDVs exhibited systemic socio-spatial effects that served as fundamental drivers of variation in cognitive outcomes. Low SES was disproportionately associated with cognitive development among Black and Hispanic children, while high SES was a robust predictor of cognitive development only among White and Asian children, consistent with the minorities' diminished returns (MDRs) theory. Notably, adversity-susceptible subgroups demonstrated an expressive association with fluid cognition compared to crystallized cognition. Poststratification proved effective in correcting group attribution biases, particularly in Pennsylvania, highlighting sampling discrepancies in US states with the highest percentage of marginalized participants in the ABCD Study©. Our collective analyses underscore the inextricable link between race and geographic location within the US. We emphasize the importance of diversity-aware population models that consider the intersectional composition of society to derive precise and interpretable insights across applicable domains.

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.

Language processing following childhood poverty: Evidence for disrupted neural networks

Childhood poverty is related to deficits in multiple cognitive domains including adult language function. It is unknown if the brain basis of language is disrupted in adults with childhood poverty backgrounds, controlling for current functioning. Fifty-one adults (age 24) from an existing longitudinal study of childhood poverty, beginning at age 9, were examined on behavioral phonological awareness (LP) and completed an event-related fMRI speech/print processing LP task. Adults from childhood poverty backgrounds exhibited lower LP in adulthood. The middle-income group exhibited greater activation of the bilateral IFG and hippocampus during language processing. In psychophysiological interaction (PPI) analyses, the childhood poverty group exhibited greater coupling between ventral Broca's and the middle temporal gyrus (MTG) as well as coupling between Wernicke's region and bilateralization. Childhood poverty disrupts language processing neural networks in adulthood, after controlling for LP, suggesting that poverty in childhood influences the neurophysiological basis for language processing into adulthood.

The promise and pitfalls of a strength-based approach to child poverty and neurocognitive development: Implications for policy

There has been significant progress in understanding the effects of childhood poverty on neurocognitive development. This progress has captured the attention of policymakers and promoted progressive policy reform. However, the prevailing emphasis on the harms associated with childhood poverty may have inadvertently perpetuated a deficit-based narrative, focused on the presumed shortcomings of children and families in poverty. This focus can have unintended consequences for policy (e.g., overlooking strengths) as well as public discourse (e.g., focusing on individual rather than systemic factors). Here, we join scientists across disciplines in arguing for a more well-rounded, "strength-based" approach, which incorporates the positive and/or adaptive developmental responses to experiences of social disadvantage. Specifically, we first show the value of this approach in understanding normative brain development across diverse human environments. We then highlight its application to educational and social policy, explore pitfalls and ethical considerations, and offer practical solutions to conducting strength-based research responsibly. Our paper re-ignites old and recent calls for a strength-based paradigm shift, with a focus on its application to developmental cognitive neuroscience. We also offer a unique perspective from a new generation of early-career researchers engaged in this work, several of whom themselves have grown up in conditions of poverty. Ultimately, we argue that a balanced strength-based scientific approach will be essential to building more effective policies.

Early life stress and functional network topology in children

Brain networks are continuously modified throughout development, yet this plasticity can also make functional networks vulnerable to early life stress. Little is currently known about the effect of early life stress on the functional organization of the brain. The current study investigated the association between environmental stressors and network topology using data from the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study. Hierarchical modeling identified a general factor of environmental stress, representing the common variance across multiple stressors, as well as four subfactors including familial dynamics, interpersonal support, neighborhood SES deprivation, and urbanicity. Functional network topology metrics were obtained using graph theory at rest and during tasks of reward processing, inhibition, and affective working memory. The general factor of environmental stress was associated with less specialization of networks, represented by lower modularity at rest. Local metrics indicated that general environmental stress was also associated with less efficiency in the subcortical-cerebellar and visual networks while showing greater efficiency in the default mode network at rest. Subfactors of environmental stress were associated with differences in specialization and efficiency in select networks. The current study illustrates that a wide range of stressors in a child's environment are associated with differences in brain network topology.

Association between adolescents' socioeconomic status and working memory updating functioning: Role of parental educational involvement

Family socioeconomic status (SES) is positively associated with executive functioning. This study tested whether parental educational involvement mediates this association. Two hundred and sixty, 12-15-year-old adolescents completed working memory updating (WMU) and general intelligence tasks, and questionnaires on SES and parental educational involvement. SES and WMU ability were positively associated; there was no difference between the fathers and mothers for three types of educational involvement. The mothers' behavioural involvement positively mediated the SES-WM updating association, whereas a negative mediation was observed for the mothers' intellectual involvement. The fathers' educational involvement did not play a significant mediating role. These results might inform interventions targeting educational involvement for enhancing the cognitive development of children from low SES families.

Adolescent Depressive Symptoms: The Role of Late Childhood Frontal EEG Asymmetry, Executive Function, and Adolescent Cognitive Reappraisal

Cognitive reappraisal is adaptive for decreasing symptoms of depression; however, a gap in the research is understanding the childhood processes that contribute to cognitive reappraisal in adolescence. This study examined executive function and frontal electroencephalogram (EEG) asymmetry during late childhood as predictors of adolescent cognitive reappraisal and depressive symptoms. Data were from 123 participants in late childhood (age 10) and adolescence (age 14.5). A moderated mediation model was fit to the data to examine frontal EEG asymmetry as a moderator in the relation between late childhood inhibitory control and adolescent cognitive reappraisal as well as adolescent cognitive reappraisal and adolescent depressive symptoms. Results indicated lower inhibitory control was associated with lower cognitive reappraisal when children had right frontal EEG asymmetry. Lower cognitive reappraisal in turn was associated with higher depressive symptoms for children with right frontal EEG asymmetry. Working memory and cognitive flexibility were also examined but were not significant indicators. Results suggest the potential for targeting inhibitory control and cognitive reappraisal to diminish depressive symptoms particularly among adolescents with right frontal EEG asymmetry.

The intersectionality of life course socioeconomic status, race, and cognitive decline: An 18-year follow-up

OBJECTIVES

Studies have documented the impact of childhood socioeconomic status (SES) on cognition. However, research that simultaneously considers SES in varied life stages, the multidimensional mechanisms, and racial differences is relatively understudied. This study examines the intersectionality across age, SES, and race and its impact on cognitive trajectories.

METHODS

Using 8376 respondents aged 65+ from the 1998-2016 Health and Retirement Study, we used latent growth curve modeling to examine the effects of four life course models (latency, pathway, accumulation, and mobility) on 18-year trajectories of mental status and episodic memory. We further tested for differences in the links between SES and cognitive trajectories between black and white respondents.

RESULTS

Cognitive function declines with age and is interrelated with SES and race. Adulthood has a stronger effect on cognitive performance than childhood. However, linked positive childhood and adulthood SES contributes to positive cognition. Accumulated SES disadvantages were associated with lower cognition. Older adults with downward mobility and low SES throughout their lifespans had the lowest cognition scores. Life course models operated differently on trajectories of cognitive decline, yet the effects were particularly evident among older black respondents. Overall, those with socioeconomic advantages tended to have a slower decline in cognition, while a faster decline occurred for those with accrued disadvantages.

CONCLUSIONS

Cognitive performance is a complex, longitudinal process intertwined with socioeconomic conditions and population heterogeneity shaped by life course contexts. Policies that facilitate healthy cognitive performance and address SES inequality could equalize health opportunities and address racial cognitive disparities later in life.