Muriah D Wheelock
Washington University in St Louis, MO·Neuroscience
The brain regions that grow and change the most in early childhood appear to be among the first to break down in Alzheimer disease. Regions that mature earliest, such as primary sensory areas, are spared until late.
- Fields
Neuroscience
Medicine & Clinical Research
Public Health & Epidemiology
- Topics
Alzheimer disease
neurodegeneration
brain development
- Grants
- 2 known grants, through Mar 2030
What they work on
- Compare the spatial and temporal patterns of brain development from birth to age three with patterns of aging and Alzheimer degeneration, using harmonized MRI datasets (eLABE, Baby Connectome Project, ADNI, SORTOUT-AB, HABS-HD) to test the 'first in last out' hypothesis.
- Determine how neighborhood deprivation and genetic risk affect functional connectivity and structural brain development in early childhood and brain degeneration in later life.
- Use lifespan population data from the UK Biobank to test how genetic risk, neighborhood deprivation, birthweight, and early childhood trauma contribute to accelerated brain aging and susceptibility to degenerative disease.
- Optimize concurrent EEG-fMRI recording and analysis in sleeping infants and toddlers, so sleep stages can be scored by EEG while brain network activity is measured by fMRI.
- Chart how sleep-state functional brain networks develop by collecting EEG-fMRI from 50 children at birth and at 24 months, separating the effects of age from those of sleep stage.
- Train machine learning models to decode sleep stages from fMRI alone, and apply them to existing infant datasets (eLABE, Baby Connectome Project) to improve prediction of developmental and mental health outcomes.
More about the research
This 'first in last out' pattern suggests that early brain development and late-life degeneration may be connected. The research uses brain imaging, especially functional magnetic resonance imaging (fMRI), and large datasets to study the developing brain. The goals are to understand how early-life conditions shape brain networks and to predict children's developmental and long-term outcomes. One project links infancy to aging. The other improves how the brains of sleeping babies are measured and interpreted.
Why it matters
Low birthweight, poverty, and childhood trauma are early-life conditions that can be changed. Showing how they shape vulnerable brain networks could point to early opportunities to lower later risk of Alzheimer disease and accelerated brain aging. Correcting for sleep state in infant brain scans could make brain-based predictions of children's developmental and mental health outcomes more reliable and reproducible.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Itamar Kahn
Columbia University, NY·Neuroscience
Chart how brain network organization, especially system segregation, changes across the mouse lifespan by repeatedly scanning the same awake mice with resting-state fMRI from 3 to 21 months of age.
Ashley Nielsen
Washington University in St Louis, MO·Neuroscience·Early-career
Code parent-child interaction videos at age 1 to measure unpredictability in parents' sensory signals (visual, auditory, touch) and in their emotional signals (inconsistent nurturing or support).
Heather Shappell
Wake Forest University, NC·Mathematics & Statistics·Early-career
Develop a unified statistical framework that estimates whole-brain functional networks from fMRI and how those networks change over seconds to minutes during a scan.
The school
Washington University in St Louis: 97 labs on PI Pages, $1.2B a year on research, 365 research doctorates a year.
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