Joint source based analysis of multiple brain structures in studying major depressive disorder

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show significant differences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave-one-out experiment, we use a Fisher Linear Discriminant (FLD) classifier to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.