The overarching goal of our research is to investigate novel ways to treat symptoms of Parkinson’s disease using non-invasive, non-pharmacological technology.
Specifically, we are interested in better understanding brain connectivity and network dynamics and extrapolating work from related disciplines such as Alzheimer’s disease and Multiple Sclerosis to investigate whether tools originally developed for other pathological diseases are also useful in PD.
We are also focused on utilizing portable and wearable technologies to record and collect research data and to ultimately provide a means of home-based symptom management.
In order to investigate disease effects and effects of treatment, we utilize a variety of functional brain and muscle assessment techniques, including:
functional Magnetic Resonance Imaging (fMRI)
Electrodermal activity (EDA)
- Kinematics and posturography
We are currently investigating novel treatments for Parkinson's that are non-invasive and non-pharmacological such as Galvanic Vestibular Stimulation, Transcranial AC stimulation, Exercise with music contingency, and EEG-guided biofeedback. In order to get these treatments to be effective, we are attempting to extract more information via non-invasive methods such as EEG, fMRI and sEMG -- we do not do testing on animals. However, this requires us, in collaboration with other experts, to utilize and develop new methods of analysis.
How can the brain compensate for the development of Parkinson's disease? A curious and unexplained feature of PD is the considerable heterogeneity in the progression of the disease, which renders prognostication difficult and complicates the interpretation of clinical studies examining disease-modifying treatments. Interestingly, motor symptoms in PD only occur after an estimated 60-80% of striatal dopamine levels have been lost.
Furthermore, imaging measures of pathological disease progression do not necessarily correlate with clinical measures of disability, such as the Unified Parkinson’s Rating Scale (UPDRS). These observations suggest the involvement of compensatory mechanisms, which serve to delay the onset of symptoms and preserve an optimal level of function.
Compensation can be achieved via biochemical changes at the synaptic level, and through macroscopic functional and structural changes at the systems level. The work in our lab focuses on the latter. When comparing Parkinson’s subjects to healthy controls, we've observed that patients maximally recruit the 'normal' motor networks when performing a motor task at its lowest level of difficulty. Additionally, to maintain near-normal motor output during the more difficult levels of the task, patients recruit novel brain areas not seen in controls. In addition, changes in activation amplitude are accompanied by alterations in functional connectivity between brain regions in PD patients. Patients demonstrate increased connectivity within the cerebello-thalamo-cortical loop as well as increased inter-hemispheric connectivity between basal ganglia nuclei regardless of the level of task difficulty. These results support prior work implicating the cerebellum as an important compensatory structure in PD.