Multimodality Brain Atlases of Mice and Men
Art Toga
UCLA
Neurology
The ability to statistically and visually compare brain imaging data from multiple subjects is essential for understanding normal variability and distinguishing healthy from diseased populations. This talk introduces the use of probabilistic atlases designed to characterize specific subpopulations, quantify their variability, and identify structural differences between them.
Using structural MRI data, we have constructed atlases with defined coordinate systems that provide a framework for mapping data from functional, histological, and other studies of the same populations across several species. The talk outlines the fundamental methodology and key components involved in constructing probabilistic atlases, and presents examples of results from both normal and diseased populations.
We also illustrate approaches for analyzing multidimensional data and understanding relationships among variables over time. Applications across multiple species are presented, including examples relevant to basic research and a case study demonstrating the clinical utility of these methods.
Audio (MP3 File, Podcast Ready)