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Connectivity- and sensor-based optimisation of stimulation parameters in patients with essential tremor and deep brain stimulation

Description

This project focuses on one of the most common movement disorder, essential tremor (ET). ET is an involuntary, rhythmic tremor of the upper limbs. It affects people of all ages, but is most common in young adults. As available drug therapy is only effective in about 50% of people with ET, invasive treatment options were considered early on. Deep brain stimulation (DBS) is a safe therapeutic approach with a more favourable side-effect profile. However, the clinical outcome depends largely on the precision of the stimulation site and the neuromodulatory parameters, which require time-consuming testing by experienced movement disorders specialists. Given the time-consuming nature of THS systems and their increasing complexity, this seems increasingly inefficient without a priori narrowing of the parameter space. Previous studies have shown that resting functional connectivity of stimulated tissue can predict tremor reduction in ET patients with clinically optimal settings after THS. However, further studies are needed to optimise the clinically complex testing of the best possible parameter combinations and to integrate neurobiological information into the targeting. The present project combines for the first time sensor-based tremor measurements with systematically varying stimulation parameters with a connectivity analysis of the associated stimulation volumes with the aim of enabling individualised preoperative planning and neuromodulation based on functional imaging.

Contact

Dr. rer. nat. Marina Ruppert-Junck, Dr. Kenan Steidel
Mrs. Sarah Reznik
Telefone: 06421/58 - 65299
Telefax: 06421/58 - 67055
marina.ruppert@.*

* please add "uni-marburg.de" for a full email-address.