Neurofeedback based on Deep Brain Stimulation for Enhancement of Motor Performance
In this project, a novel rehabilitation approach based on neurofeedback using signals from the deep brain will be explored. A collection of personalized neural biomarkers underlying pathological gait features in Parkinson’s patients will be identified. The visual display of these neural correlates potentially allows patients to reduce the pathological brain signals and hereby improve their motor performance. This will be further investigated in a clinical trial.
Parkinson’s disease is the second most common neurodegenerative disease in the population above 60 years. The loss of dopaminergic neurons in the basal ganglia causes deteriorations in neural activity, related to gait disturbances like postural instability, freezing of gait, bradykinesia (slow movement), and hypokinesia (reduced range of motion). These symptoms complicate basic activities of daily living and reduce the independence of the affected persons.
Deep-Brain-Stimulation (DBS) is used to alleviate the symptoms of Parkinson’s disease: electrodes implanted in the subthalamic nucleus of the basal ganglia stimulate the brain and help to control many of the movement-related cardinal symptoms of Parkinson’s disease (Poewe et al., 2017). However, not all patients get therapeutic benefits from DBS surgery (Ravi et al., 2019), and the improvements are very heterogeneous, especially when it comes to gait. To enhance the results of the DBS treatment and to reduce the heterogeneity of its effects, more personalized therapy approaches are required. However, the exact mechanism underlying successful/unsuccessful surgical outcomes remain largely inconclusive due to the lack of robust electrophysiological biomarkers associated with Parkinsonian gait symptoms.
We combine measurements of cortical and subcortical brain activity as well as advanced motion capture techniques to investigate neural oscillations in healthy persons and persons with Parkinson’s disease. Besides electroencephalography (EEG) recordings, we will wirelessly measure electrophysiological signals from subcortical areas using a novel generation of DBS devices in Parkinson’s patients.
By applying advanced data processing such as frequency decomposition, we select individual neural biomarkers relevant to gait rehabilitation and motor performance. These established neural correlates for gait will be further incorporated in a neurofeedback setup where a visual representation of the biomarkers will be displayed on a screen, potentially allowing participants to modulate and interact with their neural oscillations.
We hypothesize that by using a personalized, neurofeedback-based therapy approach, the occurrence of pathologic oscillations can be reduced, and through that positively affect motor performance and ultimately result in improved gait rehabilitation.
This project will give us further insights into the neural processes of gait in healthy participants and PD patients. It will help us identify and select neural biomarkers as optimal candidates for neurofeedback, targeting relevant movement characteristics for gait rehabilitation.
Funding
external pageThe Loop Zurich / StimuLOOP
external pageVontobel Stiftung