Sparse Inverse Covariance Analysis of human brain for Alzheimer's disease study

Analysis of functional neuroimaging data in the studies of human brain has become very critical in understanding neuro-degenerative diseases such as Alzheimer's disease (AD). The most common approach in AD neuroimaging studies has been of univariate nature, where individual brain regions/voxels are analyzed separately. In many cases these techniques prove to be effective. However, they could not shed light on inter brain region connectivity associated with the brain function or disease of interest. Indeed, human brain is a very complex organ anatomically and the functional interactions between its regions are even more. As a result, there is a need to understand this interdependency or inter-connection of brain regions.