Improving the control of patient symptoms in Parkinson’s disease
Parkinson’s disease (PD) is a neurodegenerative condition that affects the nerve cells in the brain that control movement. According to the European Parkinson’s Disease Association, around 10 million people have the condition worldwide. While there is no cure for the disease, treatments continue to advance. Take for example closed-loop deep brain stimulation. “Deep brain stimulation, or DBS, is a form of therapy that electrically stimulates neurons within the deep structures of the brain using surgically implanted electrodes,” explains Madeleine Lowery, a biomedical engineer at University College Dublin. “Closed-loop DBS is a proposed advanced form of DBS that senses a patient’s symptom severity and adjusts the amount of stimulation accordingly.” Although closed-loop DBS has the potential to increase therapeutic efficacy and reduce side-effects and costs, it’s not yet ready for clinical use. “Before this therapy can be used with patients, we first need to identify appropriate biomarkers for monitoring symptoms and stimulation-induced side effects, and to develop new algorithms for controlling stimulation in real time,” says Lowery. This is where the EU-funded DBSModel project comes in. “Using our computational models, we designed and tested new strategies for closed-loop deep brain stimulation that have the potential to adapt to changes in patient symptoms and side-effects by changing various stimulation parameters,” remarks Lowery, the project’s lead researcher. “These approaches can now be tested in preclinical animal models and in patients.”
New models achieve important results
At the heart of this European Research Council (ERC) supported project is a new, multiscale model of the human neuromuscular system. “The model spans multiple spatial and temporal scales and incorporates different aspects of the underlying biophysics and physiology involved in DBS,” notes Lowery. “These include the distribution of the electric field around the electrode, the effect of DBS on individual neurons and networks of neurons in the brain, and its influence on tremor and force generation in muscle.” With this model in hand, researchers developed and tested a range of different strategies for closed-loop control of DBS using different biomarkers from the nervous system. This enabled the team to propose new algorithms for automatically adjusting DBS parameters to adapt in response to recorded biomarkers. Experiments were also conducted with volunteer participants with PD and with DBS. The goal of these experiments was to understand how Parkinson’s and DBS affects the behaviour of the neurons that control the muscles involved in fine motor control. According to Lowery, the experimental results provided new data for examining how the activity of the motoneurons that control muscle changes with medication and DBS. The computational models provided insight into the physiological mechanism responsible for these behaviours. As such, they can be used to further understand how DBS exerts its therapeutic influence and to design and test new stimulation strategies. “These results will also contribute to the next generation of implanted closed-loop neuromodulation devices to improve the control of patient symptoms in Parkinson’s disease,” concludes Lowery. Lowery says that her team plans to continue its research, with the aim of laying the foundations for the clinical translation of the project’s results on closed-loop DBS. Furthermore, with the support of an ERC Proof of Concept Grant, the team is already conducting preclinical studies to examine the efficacy of the project’s closed-loop DBS algorithms in vivo.
Keywords
DBSModel, Parkinson’s disease, deep brain stimulation, DBS, brain, neurodegenerative, disease, closed-loop deep brain stimulation, biomarkers