Bogdan Draganski - Biography#

Pr Draganski received his MD degree at the Humboldt University medical school in Berlin, Germany. As a fully qualified neurologist he completed his professional training in the UK´s and Germany´s premier clinical neuroscience centres. Parallel to his clinical education he turned to imaging neuroscience and was trained in state-of-the-art magnetic resonance imaging (MRI) techniques to investigate brain morphology correlates of neurological disorders.

In the following years, he conceived the speculative idea that local structure in the mature human brain may change in response to training and learning. Data he published first confirmed this to be a very germane idea that is leading to a new area of research exploring use-dependant plasticity. As a research fellow at the Wellcome Trust Centre for Neuroimaging, London he developed a probabilistic diffusion tractography method to investigate cortico-basal ganglia pathways underlying goal-directed behaviour. Together with MR physicists he established a novel quantitative multi-parameter approach to study in vivo histological properties of the brain and developed the correspondent analytical technique (voxel-based quantification-VBQ).

In 2010 Pr Draganski joined the CHUV as a consultant neurologist and the University of Lausanne as a faculty member at the assistant professor level and was nominated as associate professor in 2014. As Head of the Neuroimaging lab LREN and supported by the other principal investigators he is responsible for the strategic decisions regarding scientific and academic career planning of the laboratory. Under his leadership LREN has focused on the development and implementation of advanced non-invasive quantitative magnetic resonance neuroimaging techniques for early diagnosis of neurodegeneration and investigating the neurobiology of mental disorders. Pr Draganski's scientific achievements in the field of computational anatomy prompted (inter)national research labs to initiate collaborations in the field of neuroplasticity, neurodegeneration and ageing.