Incoroporating Neurobiology into the Analysis of Brain Imaging Data

Friday, October 13, 2000 - 11:30am - 12:15pm
Keller 3-180
Randy Mcintosh (University of Toronto)
Many approaches to the analysis of brain imaging data have adopted conventional parametric statistics (e.g., t-test, ANOVA, MANOVA) for evaluation of brain imaging data. There is a great deal of information that can be lost with such approaches since they were developed for different purposes. We have recently applied methods that are more suited for analysis of systems that show characteristics similar to the brain, such as high interdependency and high dimensionality. I will present two of these methods, path analysis and partial least squares, and discuss the new directions that analytic approaches need to go in order to capitalize on the wealth of information brain imaging can provide.