The ability to statistically and visually compare and contrast brain image data from multiple subjects is essential to understanding normal variability and differentiating normal from diseased populations. This talk introduces the application of probabilistic atlases that describe specific subpopulations, measures their variability and characterizes the structural differences between them. Utilizing data from structural MRI, we have built atlases with defined coordinate systems creating a framework for mapping data from functional, histological and other studies of the same population in several species. This talk describes the basic approach and some of the constructs that enable the calculation of probabilistic atlases and examples of their results from several different normal and diseased populations. The talk will also illustrate some approaches useful in understanding multidimensional data and the relationships between them over time. Furthermore, there will be examples of applications in several species applied to basic research and a case study demonstrating the utility of these approaches in clinical medicine.
Audio (MP3 File, Podcast Ready)
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