Multimodal Imaging for Correlates of Abnormal Glutamatergic and GABAergic Neurotransmission in MDD Patients
ER4: Imaging study of abnormal glutamatergic and GABAergic neurotransmission This position has been filled.
Description: Imaging study of abnormal glutamatergic and GABAergic neurotransmission
This project is part of the consortial effort to uncover new mechanistic insight on depressive and anxiety disorders. We will perform multi-modal imaging to search for molecular, macro-structural and functional correlates of abnormal glutamatergic and GABAergic neurotransmission in MDD patients and healthy controls. The candidate will receive advanced training in high field MRI in healthy and patient populations. In detail, the candidate will be trained in 1) functional brain architecture including cortico-limbic networks underlying anhedonia or anxiety 2) MRS scanning including manual shimming, basis sets for quantification and analysis tools such as LC model 3) Correction methods for magnetic field inhomogeneity necessary to exploit the full potential of ultra-high resolution anatomical imaging at 7 Tesla 4) Surface based estimation methods of cortical shrinkage 5) Resting state fMRI imaging 6) Analysis of focal spontaneous signals representing tissue integrity and interregional connectivity as a basis for a network approach towards brain dysfunction in depression and anxiety 7) Concepts of functional architecture and domain specific subunits within the medial prefrontal and cingulate cortex 8) Understanding the link between immune related glial processes, NR mediated glutamatergic dysfunction and local metabolite concentrations and their implication for abnormal functional activations in fMRI studies.
The candidate is expected to have a PhD degree or equivalent preferably in psychology, psychiatry, biology or neuroscience. The candidate should be able to perform and coordinate a designated research project within a highly collaborative and interdisciplinary framework. The position includes secondments in collaborating labs of the consortium. It is expected that the candidate will produce peer reviewed articles during this time.
Experience in the field of affective neuroscience and in state of the art functional connectivity analysis of non-invasive imaging data is highly desirable. Furthermore, knowledge of modeling approaches to understand abnormal cost- and benefit balance of motivated behavior in affective disorders would be considered beneficial. Moreover, a genuine interest in the clinical relevance of current neuroimaging developments is highly appreciated.
Given the multimodal research aim, a candidate is sought with profound background in both Biochemistry and Bioinformatics. Ideally the candidate has previous research experience working on functional or structural imaging biomarkers in human depression. The analysis of multimodal imaging data further requires expertise on current image analysis pipelines as well as sufficient experience with programming languages including Python, Matlab and JAVA.