Detection of neural activities in FMRI using Jensen-Shannon Divergence

In this report, we present a statistical technique based on Jensen-Shanon divergence for detecting the regions of activity in fMRI images. The method is model free and we exploit the metric property of the square root of Jensen-Shannon divergence to accumulate the variations between successive time frames of fMRI images. Theoretically and experimentally we show the effectiveness of our algorithm.

By: Jayanta Basak

Published in: RI07002 in 2007


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