Biology subjects

Tooley, U. A.

Publications and source records attributed to Tooley, U. A..

8 recordsLinked to original sources

bioRxiv2024

Associations between parenting and cognitive and language abilities at age 2 depend on prenatal exposure to disadvantage

ObjectiveTo investigate whether parenting and/or neonatal brain volumes mediate the associations between prenatal social disadvantage (PSD) and cognitive/language abilities; and whether these mechanisms vary by level of disadvantage. Study DesignPregnant women were recruited from obstetric clinics in St Louis, Missouri. PSD encompassed access to social (e.g., education) and material (e.g., income-to-needs, health insurance, area deprivation, and nutrition) resources during pregnancy. Neonates underwent brain magnetic resonance imaging. Mother-child dyads (N=202) returned at age 1 for parenting measures and at age 2 for cognition/language assessments (Bayley-III). Generalized additive and mediation models tested hypotheses. ResultsGreater PSD was nonlinearly associated with poorer cognitive/language scores. The relation between parenting and cognition/language was moderated by PSD, such that supportive and non-supportive parenting behaviors only related to cognition/language in children with low PSD. Further, parenting mediations differed by level of PSD, such that both supportive and non-supportive parenting mediated PSD-cognition/language associations in children with low PSD, but not in children with high PSD. PSD-associated reductions in neonatal subcortical grey matter ({beta}=.19, q=.03), white matter ({beta}=.23, q=.02), and total brain volume ({beta}=.18, q=.03) were associated with lower cognition, but they did not mediate PSD-cognition associations. ConclusionsParenting moderates and mediates associations between PSD and early cognitive and language development, but only in families with lower levels of social disadvantage. These findings, while correlational, suggest that there may be a critical threshold of disadvantage, below which mediating or moderating factors become less effective, highlighting the importance of reducing disadvantage as primary prevention.

neuroscience↗

bioRxiv2023

Multilayer network associations between the exposome and childhood brain development

Growing up in a high poverty neighborhood is associated with elevated risk for academic challenges and health problems. Here, we take a data-driven approach to exploring how measures of childrens environments relate to the development of their brain structure and function in a community sample of children between the ages of 4 and 10 years. We constructed exposomes including measures of family socioeconomic status, childrens exposure to adversity, and geocoded measures of neighborhood socioeconomic status, crime, and environmental toxins. We connected the exposome to two structural measures (cortical thickness and surface area, n = 170) and two functional measures (participation coefficient and clustering coefficient, n = 130). We found dense connections within exposome and brain layers and sparse connections between exposome and brain layers. Lower family income was associated with thinner visual cortex, consistent with the theory that accelerated development is detectable in early-developing regions. Greater neighborhood incidence of high blood lead levels was associated with greater segregation of the default mode network, consistent with evidence that toxins are deposited into the brain along the midline. Our study demonstrates the utility of multilayer network analysis to bridge environmental and neural explanatory levels to better understand the complexity of child development.

neuroscience↗

bioRxiv2022

The age of reason: Functional brain network development during childhood

Human childhood is characterized by dramatic changes in the mind and brain. However, little is known about the large-scale intrinsic cortical network changes that occur during childhood due to methodological challenges in scanning young children. Here, we overcome this barrier by using sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 years (n = 92). At multiple spatial scales, age is positively associated with brain network segregation. At the system level, age was associated with segregation of systems involved in attention from those involved in abstract cognition, and with integration among attentional and perceptual systems. Associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, the two ends of a gradient from perceptual, externally oriented cortex to abstract, internally oriented cortex. These findings suggest that both ends of the sensory-association gradient may develop early, in contrast to the classical theories that cortical maturation proceeds from back to front, with sensory areas developing first and association areas developing last. More mature patterns of brain network architecture, controlling for age, were associated with better visuospatial reasoning abilities. Our results suggest that as cortical architecture becomes more specialized, children become more able to reason about the world and their place in it. SignificanceAnthropologists have called the transition from early to middle childhood the "age of reason", when children across cultures become more independent. We employ cutting-edge neuroimaging acquisition and analysis approaches to investigate associations between age and functional brain architecture in childhood. Age was positively associated with segregation between cortical systems that process the external world, and those that process abstract phenomena like the past, future, and minds of others. Surprisingly, we observed pronounced development at both ends of the sensory-association gradient, challenging the theory that sensory areas develop first and association areas develop last. Our results open new directions for research into how brains reorganize to support rapid gains in cognitive and socioemotional skills as children reach the age of reason.

neuroscience↗

bioRxiv2021

Individual differences in frontoparietal plasticity in humans

Neuroplasticity, defined as the brains potential to change in response to its environment, has been extensively studied at the cellular and molecular levels. Work in animal models suggests that stimulation to the ventral tegmental area (VTA) enhances plasticity, and that myelination constrains plasticity. Little is known, however, about whether proxy measures of these properties in the human brain are associated with learning. Here, we investigated the plasticity of the frontoparietal system by asking whether VTA resting-state functional connectivity and myelin map values (T1w/T2w ratios) predicted learning after short-term training on the adaptive n-back (n = 46, ages 18-25). We found that stronger baseline connectivity between VTA and lateral prefrontal cortex predicted greater improvements in accuracy. Lower myelin map values predicted improvements in response times, but not accuracy. Our findings suggest that proxy markers of neural plasticity can predict learning in humans.

neuroscience↗

bioRxiv2021

Early life stress is associated with earlier emergence of permanent molars

Exposure to adversity can accelerate biological aging. However, existing biomarkers of early aging are either difficult to detect in individuals at scale, like epigenetic signatures, or cannot be detected until late childhood, like pubertal onset. We evaluated the hypothesis that early adversity is associated with earlier molar eruption, an easily assessed measure that has been used to track the length of childhood across primates. In a pre-registered analysis (N = 117, ages 4-7), we demonstrate that lower family income and exposure to adverse childhood experiences (ACEs) are significantly associated with earlier eruption of the first permanent molars, as rated in T2-weighted magnetic resonance images (MRI). We replicate relationships between income and molar eruption in a population-representative dataset (NHANES; N = 1,973). These findings suggest that the impact of stress on the pace of biological development is evident in early childhood, and detectable in the timing of molar eruption.

neuroscience↗

bioRxiv2021

Functional brain network community structure in childhood: Unfinished territories and fuzzy boundaries

Adult cortex is organized into distributed functional communities. Yet, little is known about community architecture of childrens brains. Here, we uncovered the community structure of cortex in childhood using fMRI data from 670 children aged 9-11 years from the Adolescent Brain and Cognitive Development study. Children showed similar community structure to adults in early-developing sensory and motor communities, but differences emerged in transmodal areas. Children have more cortical territory in the limbic community, which is involved in emotion processing, than adults. Regions of association cortex interact more flexibly across communities, creating uncertainty for the model-based assignment algorithm, and perhaps reflecting cortical boundaries that are not yet solidified. Uncertainty was highest for cingulo-opercular areas involved in flexible deployment of cognitive control. Collectively, our findings suggest that community boundaries are not solidified by middle childhood, an instability that provides important context for childrens thoughts and behaviors.

neuroscience↗

bioRxiv2020

QSIPrep: An integrative platform for preprocessing and reconstructing diffusion MRI

Diffusion-weighted magnetic resonance imaging (dMRI) has become the primary method for non-invasively studying the organization of white matter in the human brain. While many dMRI acquisition sequences have been developed, they all sample q-space in order to characterize water diffusion. Numerous software platforms have been developed for processing dMRI data, but most work on only a subset of sampling schemes or implement only parts of the processing workflow. Reproducible research and comparisons across dMRI methods are hindered by incompatible software, diverse file formats, and inconsistent naming conventions. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing upon a diverse set of software suites to capitalize upon their complementary strengths, QSIPrep automatically applies best practices for dMRI preprocessing, including denoising, distortion correction, head motion correction, coregistration, and spatial normalization. Throughout, QSIPrep provides both visual and quantitative measures of data quality as well as "glass-box" methods reporting. Taken together, these features facilitate easy implementation of best practices for processing of diffusion images while simultaneously ensuring reproducibility.

bioinformatics↗

bioRxiv2020

Evaluating the sensitivity of functional connectivity measures to motion artifact in resting-state fMRI data

Functional connectivity (FC) networks are typically inferred from resting-state fMRI data using the Pearson correlation between BOLD time series from pairs of brain regions. However, alternative methods of estimating functional connectivity have not been systematically tested for their sensitivity or robustness to head motion artifact. Here, we evaluate the sensitivity of six different functional connectivity measures to motion artifact using resting-state data from the Human Connectome Project. We report that FC estimated using full correlation has a relatively high residual distance-dependent relationship with motion compared to partial correlation, coherence and information theory-based measures, even after implementing rigorous methods for motion artifact mitigation. This disadvantage of full correlation, however, may be offset by higher test-retest reliability and system identifiability. FC estimated by partial correlation offers the best of both worlds, with low sensitivity to motion artifact and intermediate system identifiability, with the caveat of low test-retest reliability. We highlight spatial differences in the sub-networks affected by motion with different FC metrics. Further, we report that intra-network edges in the default mode and retrosplenial temporal sub-networks are highly correlated with motion in all FC methods. Our findings indicate that the method of estimating functional connectivity is an important consideration in resting-state fMRI studies and must be chosen carefully based on the parameters of the study.

neuroscience↗