The general linear model (GLM) is one of the most commonly utilized statistical platform that is currently used in analyzing task-based fMRI data. In this talk we will introduce the general over view and basic concepts of GLM and how it is used in this very specific application of clinical neuroimaging. We will briefly review the history of introduction of GLM into the fMRI community and later use some examples to demonstrate the utility in analyzing fMRI data. In the end we will discuss some of its limitations.
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