Andrew Monaghan, PhD 

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Investigator Bio:

Dr. Andrew Monaghan is a postdoctoral fellow in the Wallace H. Coulter Department of Biomedical Engineering at Emory University and Georgia Tech. He completed his PhD in 2023 at Arizona State University, where he conducted research in the Gait and Balance Disorders Laboratory under Dr. Daniel Peterson. Supported by The Michael J. Fox Foundation for Parkinson’s Research, his doctoral studies focused on the adaptability and neural control of reactive balance in Parkinson’s disease (PD). Currently, Andrew works under the guidance of Dr. Lena Ting and Dr. Michael Borich, studying the interactions between neural and biomechanical systems in older adults with neurodegenerative diseases, using balance as a motor paradigm. His research primarily investigates electrocortical dynamics during balance control in older adults with PD, with a specific focus on mechanisms underlying freezing of gait (FoG) to inform PD therapies and identify prodromal indicators of freeze risk. 

Objective:

To identify electrophysiological biomarkers of FoG using mobile electroencephalography (EEG).  

Background:

FoG, occurring in 50% of individuals with PD, manifests as brief, episodic halts in forward progression despite the intention to walk, reducing mobility and increasing fall risk. A limited understanding of the neural mechanisms behind FoG, compounded by its sporadic nature and the temporal resolution limitations of functional imaging techniques, impedes treatment development. 

Methods/Design:

I will assess a person’s freeze risk without a freezing event using mobile electroencephalography (HD-EEG) during well-controlled perturbations to standing balance as a “behavioral probe,” which excites brain circuits implicated in FoG. I hypothesize that individuals that typically experience FoG will show increased brain activity in response to balance challenges than those who do not experience FoG. Characterizing consistent and reliable brain activity using a probe that does not require a freeze event addresses the inherent unpredictability and sporadic nature of FoG, providing deeper insights into the individual risk of developing FoG. Next, I will employ mobile EEG to characterize irregular brain activity patterns occurring before and during FoG during a clinical gait assessment. I hypothesize that FoG episodes are preceded by irregular brain activity stemming from an increased reliance on cortical resources.  

Relevance to Diagnosis/Treatment of Parkinson’s Disease:

This approach holds translational potential for real-time detection, monitoring, and prevention of FoG. I envision using electrophysiological biomarkers from the brain to provide neurophysiological input for adaptive interventions, such as deep brain stimulators or wearable cueing devices, to prevent or intervene during FoG.