Authors: Alice Weatherston
Frequent adjustment of deep brain stimulation (DBS) equipment is often required in order to reach the most effective stimulation pattern for a patient and to ultimately optimize treatment outcomes. While eventually effective, the current ‘trial and error’ method does not represent the most efficient method of administering DBS and suboptimal delivery can cause adverse side effects. A new study from researchers at the Mayo Clinic (MN, USA) has sought to solve this problem by designing and testing a new system that is capable of measuring neurotransmitter production and automatically adjusting the DBS pattern in response. The research was presented at Neuroscience 2015 recently (17—21 October 2015, IL, USA).
The clinical success of DBS for conditions such as Parkinson’s disease is dependent on the correct identification and implementation of a selection of stimulation parameters, including amplitude, frequency and impulse duration.
The novel technology, termed WINCS Harmoni, utilizes a closed-loop algorithm that is reliant on neurochemical feedback mechanisms. The system was designed to continuously measure levels of dopamine within the brain and automatically make adjustments to the DBS pattern in order to produce the optimal neurochemical response. Findings indicated that the algorithm achieved the desired results when tested in a range of animal models, including rodents, swine and non-human primates.
Lead author, Kendall Lee (Mayo Clinic) commented: “Our preliminary results in animals show that by monitoring real-time changes in brain chemistry we can automate and optimize the parameters of stimulation.”
The team believe that the specificity of the system and the ability to increase the efficiency of DBS may provide an opportunity to improve the therapeutic outcomes of the treatment in the future.
Source: Neuroscience 2015 press release. The full abstract can be found here