February 12, 2003

Cliona Golden,
Program in Applied and Computational Mathematics, Princeton University.

Analysis of fMRI Data in Neuroscience

 Abstract:

Functional Magnetic Resonance Imaging (fMRI) is a technique which can be used to take images of brain activity over time. However, the images obtained from an fMRI scanner are very noisy and difficult to understand and they call for a variety of methods of analysis to make sense of them.

I will discuss the results of a study of how justified and robust are techniques, such as Independent Component Analysis (ICA), that are currently being used in the analysis of fMRI data in neuroscience. I will also talk about the development, using mathematical criteria, of new methods of analysis for this data.

Time-Frequency Brown Bag Seminar's homepage.