Fourth annual PMDC pilot grants fund record number of studies

The VCU Parkinson’s and Movement Disorders Center (PMDC) has awarded funding to five studies, the largest number since the pilot grant program’s founding in 2021, broadening the program's impact on movement disorders research at VCU.

The 2024 awardees represent the multidisciplinary nature of research, with faculty from the VCU School of Medicine, College of Engineering, College of Humanities and Sciences and School of Nursing. This year’s recipients also include faculty from the College of William and Mary’s Department of Computer Sciences.

“We’re continuing to reach a broad range of investigators across the School of Medicine, VCU and beyond,” said Brian Berman, M.D., director of the PMDC. “Our ability to make advances toward a cure requires having good models to understand the disease and having a breadth of investigators and departments certainly helps that pursuit.”

This year’s funded studies include investigations into the safe use of Wi-Fi for Parkinson’s monitoring, a novel use of deep-brain stimulation to treat a debilitating symptom of Parkinson’s disease and funding for benchtop science projects investigating the pathogenesis of Parkinson’s disease. This award cycle also features mentor-mentee team featuring a postdoctoral student and his faculty advisor, which advances the PMDC’s mission to foster the next generation of movement disorders researchers.

“The tech-forward aspect of this year’s awards is one of the most exciting aspects to see,” Berman said. “There’s a lot of potential for artificial intelligence and other technologies to advance care for patients with movement disorders and beyond.”

PMDC Pilot Grant Awardees 2024-2025

Rohil Hameed, Ph.D., postdoctoral fellow, Department of Biology, VCU College of Humanities and Sciences

Alaattin Kaya, Ph.D., assistant professor, Department of Biology, Department of Human and Molecular Genetics, VCU College of Humanities and Sciences and VCU School of Medicine

Conserved essential genes as pro-neuroprotective targets: Getting out from under the lamppost

This proposal seeks to examine the potential for over-expression of essential genes to modify phenotypes associated with Parkinson’s disease models in Caenorhabditis elegans. Due to their essential nature, this class of genes are very much understudied in genetic models, as, traditionally, loss-of-function mutations or reduced expression is the most common approach to examine the roles of candidate genes, an approach which leads to lethality with an essential gene. The investigator proposes to use two Parkinson’s disease models, previously published by other groups. Identification of genes that modulate phenotypes in the two models will represent candidate genes not previously identified that may play a role in the pathology of Parkinson’s disease.

Dean J. Krusienski, Ph.D., professor and graduate program director, Department of Biomedical Engineering, VCU College of Engineering

Gang Zhou, Ph.D., Department of Computer Science, William and Mary Arts and Sciences

Huajie Shao, Ph.D., Department of Computer Science, William and Mary Arts and Sciences

Kathryn Holloway, M.D., professor and director, Department of Neurosurgery, VCU School of Medicine

Leslie Cloud, M.D., professor, Rogliano Family Endowed Chair and director of Parkinson’s Disease Program, Department of Neurology, VCU School of Medicine

Ingrid Pretzer-Aboff, Ph.D., R.N., professor, Department of Adult Health and Nursing Systems, VCU School of Nursing

Harsh Shah, M.D., Department of Neurosurgery, VCU School of Medicine

Transformer-based anomaly detection to predict freezing-of-gait from GPi local field potentials and ankle IMU data

Freezing of gait (FoG) is among the most debilitating manifestations of Parkinson’s disease (PD), but is also relatively poorly understood and difficult to treat. This study will attempt to train machine learning (ML) architectures to reliably detect FoG episodes by combining changes in LFPs monitored by deep brain stimulation (DBS) with globus pallidus internus (GPi) leads with abnormalities in kinematic data provided by wearable inertial motion units (IMUs). Expert review of video of participant physical performance will be completed to confirm flagged episodes of FoG compared to periods of normal walking and standing.

Santiago Lima, Ph.D., associate professor, Department of Biology, VCU College of Humanities and Sciences

Jason Newton, Ph.D., assistant professor, Department of Biology, VCU College of Humanities and Sciences

Examination of a GBA-RTK-α-Synuclein axis in cellular and preclinical models of Parkinson's disease

Building on their 2023 PMDC pilot grant-funded project that helped them develop a GBA knockout cell model with increased a-synuclein accumulation, Lima and Newton aim to now explore how GBA activity defects and associated glycosphingolipid alterations influence Trk receptor activity and impact cell survival. Establishing a link between GBA-related mechanisms and the altered kinase signaling pathway contribution to Parkinson’s disease pathogenesis would provide greater insight into pathogenesis of Parkinson’s disease and perhaps lead to identification of potential novel therapeutic targets.

Eyuphan Bulut, Ph.D., Associate Professor, Department of Computer Science, VCU College of Engineering

Brian D. Berman, M.D., M.S., Professor and Bemiss Endowed Chair, Director, VCU Parkinson’s and Movement Disorders Center, Division of Movement Disorders Chief, Department of Neurology, VCU School of Medicine

At-home monitoring of Parkinson’s disease patients through non-invasive Wi-Fi sensing

This proposal outlines a pilot study aimed at developing and testing a non-invasive, low-cost, and privacy-preserving system for monitoring Parkinson's disease (PD) patients at home using Wi-Fi sensing technology. The system intends to track PD-related symptoms, such as tremors and motor fluctuations, by analyzing the channel state information (CSI) from Wi-Fi signals. The project aims to improve the monitoring of PD patients, provide better insights into the effectiveness of medications, and ultimately enhance patient outcomes.

Changqing Luo, Ph.D., assistant professor, Department of Computer Science, VCU College of Engineering

Physical adversarial attacks on Wi-Fi sensing systems for monitoring Parkinson's disease patients

Wi-Fi sensing systems are especially vulnerable to physical adversarial attacks, such as signal manipulation, due to the open-air transmission of signals, which can disrupt input data. This proposal aims to explore and design unnoticeable over-the-air physical attacks on Wi-Fi sensing systems used for monitoring Parkinson's disease (PD) patients. The research focuses on understanding the vulnerabilities in machine learning (ML) models used in these systems and devising attack strategies to disrupt the accurate monitoring of PD patient movements. The proposal addresses a critical gap in the security of Wi-Fi sensing systems by investigating physical adversarial attacks, which can compromise the effectiveness of these systems in monitoring PD patients.

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