EEG-estimated functional connectivity, and not behavior, differentiates Parkinson's patients from health controls during the Simon conflict task
Journal:
arXiv
Published Date:
Oct 9, 2024
Abstract
Neural biomarkers that can classify or predict disease are of broad interest
to the neurological and psychiatric communities. Such biomarkers can be
informative of disease state or treatment efficacy, even before there are
changes in symptoms and/or behavior. This work investigates EEG-estimated
functional connectivity (FC) as a Parkinson's Disease (PD) biomarker.
Specifically, we investigate FC mediated via neural oscillations and consider
such activity during the Simons conflict task. This task yields sensory-motor
conflict, and one might expect differences in behavior between PD patients and
healthy controls (HCs). In addition to considering spatially focused
approaches, such as FC, as a biomarker, we also consider temporal biomarkers,
which are more sensitive to ongoing changes in neural activity. We find that
FC, estimated from delta (1-4Hz) and theta (4-7Hz) oscillations, yields spatial
FC patterns significantly better at distinguishing PD from HC than temporal
features or behavior. This study reinforces that FC in spectral bands is
informative of differences in brain-wide processes and can serve as a biomarker
distinguishing normal brain function from that seen in disease.
