OxCIN Global Scholars + WIP

Bayesian Hierarchical Modeling of Brain Morphometry Across Neurological Disorders in Nigeria

Presented by Patrick Filima

Abstract:This presentation explores the potential of Bayesian hierarchical modeling as a framework for analyzing brain morphometry data across neurological disorders in Nigeria. Neuroimaging datasets from underrepresented populations often face challenges such as small sample sizes, heterogeneity in acquisition, and variability across study groups, which can limit the robustness and generalizability of conventional statistical analyses. In this work(work is still in progress), I examine how hierarchical Bayesian approaches may provide a more flexible and principled way to model such data by accounting for both shared and group-specific sources of variation. The broader aim is to strengthen inference in African neuroimaging research and contribute to more inclusive and globally representative brain science.

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