David Hardoon
April 17, 2007
Title:
Using Image Stimuli to Drive fMRI Analysis
Abstract:
Recently machine learning methodologies have been increasingly used to analyse the relationship between stimulus categories and fMRI responses. In this talk, we introduce a new unsupervised machine learning approach to fMRI analysis approach, in which the simple categorical description of stimulus type (e.g. type of task) is replaced by a more informative vector of stimulus features. We compare this new approach with a standard Support Vector Machine (SVM) analysis of fMRI data using a categorical description of stimulus type of an emotional based fMRI experiment.