Abstract:
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The historical practice in fMRI brain imaging has been to determine areas of brain activaion via linear regression techniques. In recent times, machine learning methods have become popular for data analysis. In this talk, a statistical machine learning approach to computing brain activation will be explored. Results, lessons, and future areas of work will be presented.
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