Cliona Golden
Courant Institute.
| Functional Magnetic Resonance Imaging (fMRI) is a brain imaging technique which records over time changes in blood oxygenation level that can be associated with underlying neural activity. However, fMRI images are very noisy and extracting useful information from them calls for a variety of methods of analysis. I will discuss the results of a study of how justified and robust are model-free 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. |
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