environmental factors

Examining the foundations of reading comprehension: a longitudinal study of brain and behavior starting in infancy

SUMMARY Reading comprehension (RC) is one of the most complex skills that we utilize daily and is crucial for functioning in modern society, but despite its significance for academic achievement, employment prospects, and mental health, many children and adults do not exhibit proficient RC abilities. New theoretical models aiming to explain variability in RC suggest a dynamic interplay and co-development among ‘precursor’ foundational and cognitive- linguistic skills, interacting with environmental and socio-ecological factors across the developmental timeline of learning to read. Behavioral and neuroimaging studies in school-age children have demonstrated critical mechanistic support for these multifactorial RC models by identifying the developmental trajectories of precursor skills and further showing that brain areas, tracts, and networks typically underlying language and cognitive skills are also involved in RC. Nevertheless, the precursor skills that support RC start developing in infancy and the brain correlates underlying these precursors begin to develop in utero, which suggests that typical and atypical RC developmental trajectories could diverge long before school age. As such, examining RC development using a multifactorial, longitudinal approach that includes brain and behavior starting in infancy is critical for developing theoretical frameworks that can inform early preventative and intervention strategies. Here, we propose a comprehensive longitudinal study of RC development in which we examine direct and indirect effects on RC from brain, behavioral, familial risk, and environmental data from infancy to adolescence. To achieve this goal, we will combine two existing longitudinal cohorts, one ranging from infancy to late childhood (n = 174) and the other from preschool to early adolescence (n = 137). By applying state-of-the-art pediatric neuroimaging analyses, multiple indicator growth model structural equation models, and an innovative behavior- brain co-development measurement index to this unique, combined dataset, we will be able to identify brain and behavioral measures in infancy that directly and indirectly support subsequent RC development (Aim1). We will further characterize how longitudinal trajectories of behavioral measures as well as brain structure, function, and white matter organization contribute to RC development and how familial risk and environmental factors shape these trajectories (Aim 2). Finally, we will examine how the co-development of brain and behavior, as measured with an innovative co-development index, relates to subsequent RC (Aim 3). If successful, we will contribute the first multifactorial longitudinal model of RC development comprising direct and indirect effects from brain, behavior, brain-behavior co-development, familial risk, and environmental measures beginning in infancy. Understanding RC development using a multifactorial longitudinal lens will be crucial for building theoretical models and developing experimental designs focused on early preventative and intervention approaches long before the start of formal schooling.

Towards Human Systems Biology of Sleep/Wake Cycles: Phosphorylation Hypothesis of Sleep

The field of human biology faces three major technological challenges. Firstly, the causation problem is difficult to address in humans compared to model animals. Secondly, the complexity problem arises due to the lack of a comprehensive cell atlas for the human body, despite its cellular composition. Lastly, the heterogeneity problem arises from significant variations in both genetic and environmental factors among individuals. To tackle these challenges, we have developed innovative approaches. These include 1) mammalian next-generation genetics, such as Triple CRISPR for knockout (KO) mice and ES mice for knock-in (KI) mice, which enables causation studies without traditional breeding methods; 2) whole-body/brain cell profiling techniques, such as CUBIC, to unravel the complexity of cellular composition; and 3) accurate and user-friendly technologies for measuring sleep and awake states, exemplified by ACCEL, to facilitate the monitoring of fundamental brain states in real-world settings and thus address heterogeneity in human.

At the nexus of genes, aging and environment: Understanding transcriptomic and epigenomic regulation in Parkinson's disease

Parkinson’s Disease (PD), the most common neurodegenerative movement disorder, is based on a complex interplay between genetic predispositions, aging processes, and environmental influences. In order to better understand the gene-environment axis in PD, we pursue a multi-omics approach to comprehensively interrogate genome-wide changes in histone modifications, DNA methylation, and hydroxymethylation, accompanied by transcriptomic profiling in cell and animal models of PD as well as large patient cohorts. Furthermore, we assess the plasticity of epigenomic modifications under influence of environmental factors using longitudinal cohorts of sporadic PD cases as well as mouse models exposed to specific environmental factors. Here, we present gene expression changes in PD mouse models in context of aging as well as environmental enrichment and high-fat diet.

Using human pluripotent stem cells to model obesity in vitro

Obesity and neurodegeneration lead to millions of premature deaths each year and lack broadly effective treatments. Obesity is largely caused by the abnormal function of cell populations in the hypothalamus that regulate appetite. We have developed methods generate human hypothalamic neurons from hPSCs to study how they respond to nutrients and hormones (e.g. leptin) and how disease-associated mutations alter their function. Since human hypothalamic neurons can be produced in large numbers, are functionally responsive, have a human genome that can be readily edited, and are in culture environment that can be readily controlled, there is an unprecedented opportunity to study the genetic and environmental factors underlying obesity. In addition, we are fascinated by the fact that mid-life obesity is a risk factor for dementia later in life, and caloric restriction, exercise, and certain anti-obesity drugs are neuroprotective, suggesting that there are shared mechanisms between obesity and neurodegeneration. Studies of HPSC-derived hypothalamic neurons may help bridge the mechanistic gulf between human genetic data and organismic phenotypes, revealing new therapeutic targets. ​

Slowing down the body slows down time (perception)

Interval timing is a fundamental component action, and is susceptible to motor-related temporal distortions. Previous studies have shown that movement biases temporal estimates, but have primarily considered self-modulated movement only. However, real-world encounters often include situations in which movement is restricted or perturbed by environmental factors. In the following experiments, we introduced viscous movement environments to externally modulate movement and investigated the resulting effects on temporal perception. In two separate tasks, participants timed auditory intervals while moving a robotic arm that randomly applied four levels of viscosity. Results demonstrated that higher viscosity led to shorter perceived durations. Using a drift-diffusion model and a Bayesian observer model, we confirmed these biasing effects arose from perceptual mechanisms, instead of biases in decision making. These findings suggest that environmental perturbations are an important factor in movement-related temporal distortions, and enhance the current understanding of the interactions of motor activity and cognitive processes. https://www.biorxiv.org/content/10.1101/2020.10.26.355396v1

Defining new multimodal neuroimaging marker for grey matter characterization

The human cortical ribbon varies during the lifespan, from childhood to senescence. To study the effects of genetic and environmental factors on these dynamics, one needs to measure specific phenotypes (cortical volume, surface area, thickness, new neuroimaging phenotypes such as intracortical myelination or multimodal ones based on their combination, or their asymmetries) that characterize the cerebral grey matter accurately

Abstraction and Analogy in Natural and Artificial Intelligence

Learning by analogy is a powerful tool children’s developmental repertoire, as well as in educational contexts such as mathematics, where the key knowledge base involves building flexible schemas. However, noticing and learning from analogies develops over time and is cognitively resource intensive. I review studies that provide insight into the relationship between mechanisms driving children’s developing analogy skills, highlighting environmental inputs (parent talk and prior experiences priming attention to relations) and neuro-cognitive factors (Executive Functions and brain injury). I then note implications for mathematics learning, reviewing experimental findings that show analogy can improve learning, but also that both individual differences in EFs and environmental factors that reduce available EFs such as performance pressure can predict student learning.

Epigenetics and Dementia: Lessons From the 20-Year Indianapolis-Ibadan Dementia Study

Dementia is of global interest because of the rapid increase in both the number of individuals affected and the population at risk. It is essential that the risk factors be carefully delineated for the formulation of preventive strategies. Epigenetics refers to external modifications that turn genes "on" or "off”, and cross-cultural studies of migrant populations provide information on the interplay of environmental factors on genetic predisposition. The Indianapolis-Ibadan Dementia Study compared the prevalence, incidence and risk factors of dementia in African Americans and Yoruba to tease out the role of epigenetics in dementia. The presentation will provide details on biomarkers of dementia, vascular risk factors and the association with apolipoprotein E in the Yoruba. The purpose will be to inspire early career researchers on possibilities and research strategies applicable in African populations

Microglia polarization and its modulation by environmental factors

Multidimensional predictors of antidepressant response: using computational approaches to integrate biological networks, environmental factors and clinical outcomes

Role of the lifestyle and environmental factors in the complexity of the migraine aura