The human brain is a highly convoluted organ with much of the processing occuring on the surface layer called the grey matter. The folding patterns of every indivudal are unique, making it difficulty to compare control groups to target populations. Due to the complex folding patterns of the brain, neuroscientists are interested in utilizing mathematical methods to quantify and characterize brain function and anatomy. I will present some of the methods that I am using from topology, geometry and complex analysis to create conformal maps of the human brain from magnetic resonance imaging (MRI) data. I will also discuss some of the issues that arise and future directons that are needed to compare different population groups, including MRI data acquired from populations with schizophrenia, Alzheimer's and major depressive disorder.