All ETDs from UAB

Advisory Committee Chair

Amy W Amara

Advisory Committee Members

Lori L McMahon

Zachary Irwin

Matthew S Goldberg

Harrison C Walker

Arie Nakhmani

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Engineering


Parkinson's disease (PD) is more than a movement disorder, and non-motor symptoms, including cognitive deficits and sleep disorders, present early and adversely affect the quality of life of a person with Parkinson's disease (PwP). Unfortunately, no pharmacological therapies slow or halt the progression of cognitive decline in PD. A substantial obstacle to developing effective cognitive therapies is the heterogeneous cognitive profile in PD, as well as a lack of a reliable biomarker of cognitive impairment. Moreover, the ideal biomarker would be generalizable, widely accessible, easily measured, non-invasive, and, ideally, modifiable. Unfortunately, thus far, proposed markers of cognitive deficits often include invasive measures or genetic testing, making them less readily accessible. Identifying novel network electrophysiological biomarkers as predictors of cognitive performance in PwP will advance the field substantially and improve well-being in PwP. To accomplish this goal, we leveraged the newly developed PD rat model with a mutation in PARK6, which encodes the protein PTEN-induced kinase 1 (PINK1), to study hippocampal excitatory transmission. Along with investigating cognitive ii neurophysiological markers in preclinical models, we also conducted translational studies to assess the effect of quantitative sleep electroencephalogram markers on cognitive performance in patients with PD. Recording excitatory postsynaptic potentials from the extracellular dendritic field revealed no early differences in short- and long-term plasticity mechanisms or the strength of basal synaptic transmission in the preclinical study. However, in the translational studies, we found increased slow wave sleep, higher delta spectral power (1.0-4.0Hz), Scalp-SW (<1 Hz) density, sleep spindle density, and co-occurrence percent of SW-spindle were associated with better cognitive performance in PD. Further, we discovered that baseline sleep spindle density predicts longitudinal development of mild cognitive impairment in PD. The present study has contributed substantially to the advancement of the field and identified sleep spindle density as a novel non-invasive electrophysiological marker to identify PD patients at risk for mild cognitive impairment to optimize trial populations and tailor clinical care.

Included in

Engineering Commons



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