Msc. Louise Martens

The aim of this project is to investigate how (ultra-) high field MRS can be used to understand the neurobiological basis underlying abnormalities found in other imaging modalities in psychiatric populations, and to use functional connectivity measures in conjunction with information on neurometabolism to predict disease status. 

Using a combination of MRS and functional connectivity analysis, it is possible to investigate whether increased activation or deactivation in network (nodes) are mediated by excitatory or inhibitory neurometabolite levels. Abnormal functional connectivity and other resting-state measures can thus be interpreted in the context of impaired excitatory or inhibitory neurotransmission. In my PhD project, I will apply this approach in studies of alcohol-dependent subjects and populations with high childhood trauma and GAD65 (GABA-synthesizing enzyme) encoding gene polymorphisms. The second aim of this project is to apply machine learning approaches to classify subjects based on single voxel spectroscopy Glu and GABA and whole-brain or single-slice MRSI data.