Analysis of cortical thickness in aging and dementia

This project focuses on analyzing the developmental trajectories of brain cortical surface metrics in elderly adults; we are interested in understanding morphological differences that may arise from dementia and look to elucidate their underpinnings. Specifically, we examine changes in key brain structure parameters—such as cortical thickness, curvedness, shape index, and sulcal depth—across longitudinal time points.

The project draws from MRI images received from various imaging datasets. We use tools, like our in-house pipeline, for generating surface-based metrics from brain scans. Comparisons are occasionally made to other datasets, including adult human brains from the ABIDE (Autism Brain Imaging Data Exchange) collection, non-human primates, and chimpanzees, to provide evolutionary and developmental context.

Key goals include:

• Quantifying correlations between local metrics (e.g., curvedness vs. surface area) to identify patterns of cortical thinning.
• Visualizing distributions (via histograms and kernel density estimates, or KDEs) to track shifts over time, such as changing complexity in shape index as the brain matures.
• Generating insights into neurodevelopmental norms, which could inform studies on atypical development.

All processing and analysis occur in a high-performance computing environment.