Parkinson's Disease Related Alterations in Common Spatial Patterns of EEG Signals
Year: 2024
Type: conference-paper
Study design: Observational Study
Abstract: Diagnosing Parkinson's Disease (PD) is a challenging task since the complex neuronal dynamics of the brain under wide range of effects have not been fully identified. Furthermore, conventional approaches like subjective clinical evaluations can be impractical on a large scale due to their expense and limited availability. EEG has the capability to measure electrical fields of neuronal sources non-invasively. Rapid fluctuations can be detected easily due to the high time resolution of EEG, though its poor spatial resolution restricts its ability to precisely localize the source of activity within the brain. Common Spatial Patterns (CSP) allow identification of spatial changes in neuronal activity by considering EEG signals across different conditions. In this study, we adopted the Common Spatial Patterns technique to analyze EEG signals from 13 healthy controls, 13 PD patients, and 13 PD patients with freezing of gait symptom(PDFOG) to detect disease-driven spatial alterations. CSP filters contrasting pre-stimulus and post-stimulus EEG signals were designed across δ, θ, α, β1, β2, and broad-band frequency bands, along with different temporal ranges during the post-stimulus pedaling task. The findings based on two-sample t-tests indicated that the CSP filter weights change significantly between populations and the weights observed at the δ band were the most discriminative among all group comparisons.
Authors: ONAY, Fatih, KARAÇALI, BILGE
Institutions: Bursa Technical University, Izmir Institute of Technology
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7168087577