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Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegenerationNARA Subscribed
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can fi...
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion te...
The Black Array of Broadband Absolute Radiometers Earth Radiation Imager (BABAR-ERI) is a small, adaptable nadir-pointed pushbroom imager to measure Earth-leaving broadband radiance from 0.3 µm to 100 µm with higher information content than is currently measured by reducing radiometric uncertainty and enabling cloud-resolving spatial resolution. The three-instrument BABAR-ERI suite fits a 12U CubeSat form factor and contains c...
Restoration of riparian forests can improve water quality and wildlife habitat and also sequester carbon. Unfortunately, failures of riparian restoration efforts are common due to planting mortality. Selection of well-suited species, dense planting and use of mechanical soil site preparations may potentially enhance wetland restoration plantings. Carbon valuation of forestland is increasing and additional research is needed to...
Modelling Like an ExperimentalistNARA Subscribed
Modelling has become a routine part of ecological and evolutionary research, yet its practice often lacks a clear conceptual framework. I propose that modelling can be fruitfully understood as experimentation. Like empirical studies, modelling projects involve treatments, levels and responses: parameter regimes or data manipulations serve as treatments, replicated runs yield summaries and comparisons across conditions reveal m...
Theoretical models suggest that the mean time to extinction scales with habitat size through either exponential or power law relationships, depending on demographic and environmental stochasticity. Despite extensive theoretical work, empirical validation of these scaling relationships is limited. Here, we report a microcosm study of Daphnia magna populations in experimental chambers consisting of 1, 2, 4, 8, 16, or 32 patches,...
Species' distributions are changing around the planet as a result of global climate change. Most research has focused on shifts in mean climate conditions, leaving the effects of increased environmental variability comparatively underexplored. This paper proposes two new macroecological hypotheses—the variability damping hypothesis and the variability adaptation hypothesis —to understand how ecological dynamics and evolutionar...
Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learningNARA Subscribed
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, th...
Propagating Uncertainty in Predicting Individuals and Means Illustrated with Foliar Chemistry and Forest BiomassNARA Subscribed
Quantifying uncertainty is important to establishing the significance of comparisons, to making predictions with known confidence, and to identifying priorities for investment. However, uncertainty can be difficult to quantify correctly. While sampling error is commonly reported based on replicate measurements, the uncertainty in regression models used to estimate forest biomass from tree dimensions is commonly ignored and has...
Natural disasters interact to affect the resilience and prosperity of communities and disproportionately affect low income families and communities of colour. However, due to lack of a common theoretical framework, these are rarely quantified. Observing severe weather events (e.g. hurricanes and tornadoes) and epidemics (e.g. COVID‐19) unfolding in southeastern US communities led us to conjecture that interactions among catast...