Application of a Global Bayes Factor Detect a Brain Region Activation

• Activity Number: 342 - Novel Statistical Testing and Activation-Detection Methods for Imaging Data
• Type: Contributed
• Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Imaging
• Author(s): Mozhdeh Forghani* and Khalil Shafie and HasniIdayu Saidi
• Companies: University of Northern Colorado and University of Northern Colorado and University of Northern Colorado
• Keywords: Bayes factor ; fMRI ; Voxel

Abstract

For the past two decays there have been many studies on the problem of searching for activation in brain images obtained from functional magnetic resonance imaging (fMRI). In recent years a series of Bayesian approaches have been suggested which in most of those, the test for the activation is voxel based. However, Shafie et al (JSM 2014, Boston) proposed a method of testing for the activation by using a "Global Bayes Factor" which consider the whole image as an infinite dimensional object. In this work, we have explored this method in more details and applied it to search for activation in brain images obtained from an auditory fMRI experiment by Geraint Rees and Karl Friston (http://www._l.ion.ucl.ac.uk/spm/data/auditory/). Here, the Global Bayes Factor is calculated to test the hypothesis of no activation on two different models fitted to the data.