Masters candidate in Biostatistics, David Schneck, will present:
“Association between Parkinson’s Disease Severity and the Power, Coherence, and Phase Locking Values of the Basal-Ganglia Thalamocorticol Network”
Plan B Adviser: Mark Fiecas
Abstract: Electrophysiological biomarkers such as Low and High Beta Band oscillatory power, phase locking values (PLV), and coherence obtained from regions in the Basal-Ganglia Thalamocortical (BGTC) network were evaluated for their association with Parkinson’s Disease (PD) severity in two non-human primates (NHP) for whom PD progression was induced. Longitudinal measurements were collected on the biomarkers and the modified Unified Parkinson’s Disease Rating Scale (mUPDRS), a measure of PD severity. A changepoint analysis indicated four distinct levels of severity for each primate. Linear mixed models were fit to characterize the association between individual network Low and High Beta powers and PD severity and the association between PLV and mUPDRS. A scalar-on-function regression approach was used to model mUPDRS against coherence, which is a smooth function over frequencies. Results indicate associations between mUDPRS and subcortical oscillatory power within regions within the BGTC. Furthermore, PLV is associated with mUPDRS in connections between subcortical STN and GP networks. Finally, the scalar-on-function model identified frequencies for which the coherence between the M1 cortical network and the GP subcortical networks were significantly associated with mUPDRS. Through these analyses we find that there are associated alterations in power and coherence in BGTC regions as PD progresses.