About Our Research
The Motor and Cognition Lab (MoCoLab), led by principal investigator Vincent Koppelmans, PhD, studies the causes and neural correlates of motor dysfunction in Alzheimer's disease and depression, and explores how these findings can be leveraged for classification and prediction models.
Identifying Motor Dysfunction in Alzheimer’s and Depression
Our lab's research focuses on motor dysfunction in neurological and psychiatric disorders that are not primarily linked to motor deficits such as Alzheimer’s disease (AD) and major depressive disorder (MDD). While motor deficits are not the main or major areas of functional loss in AD or MDD, motor impairment such as slowing of gait is frequently observed in these disorders.
Within AD and MDD, we study the breadth of motor domains (i.e., gait, balance, dexterity, motor learning and adaptation, graphomotor skills, and muscle strength) to identify profiles of motor dysfunction that could be both sensitive and specific for the building classification or prediction models. Additionally, ongoing work focuses on the effects of Lecanemab, a recent FDA-approved drug for treatment of AD, on motor function in relation to brain functional connectivity.
Learn more about our research
Using supervised machine learning methods, we construct classification models that could help with distinguishing between healthy and diseases subjects (e.g., normal aging versus dementia), as well as subtyping (e.g., amnestic versus non-amnestic Mild Cognitive Impairment). Similar methodology is used for prediction modeling of disease progression or treatment response over time based on baseline assessments of motor behavior.
Using functional and structural magnetic resonance imaging (MRI) we provide insight in the neural mechanisms of motor dysfunction in AD and MDD. This is particularly informative for understanding disease specific motor profiles and subtypes.
Building sensitive and specific classification models for AD and MDD can improve diagnostic accuracy that will ultimately lead to improved treatment response. Successful prediction models will be able to select patients likely to progress to AD, which could assist with clinical trial enrichment for the development of novel treatments, specifically because motor behavioral measures are more cost-efficient and non-invasive compared to existing enrichment biomarkers.
Previous and ongoing research in the MoCoLab is sponsored by NIH/NIA, NASA, The Ben and Iris Margolis Foundation, The University of Utah Center on Aging, and the Utah State University Alzheimer's Disease and Dementia Research Center.
Collaborators
Departments
Faculty
Meet our research team
Principal Investigator
Vincent Koppelmans, PhD
Dr. Koppelmans is a Research Associate Professor of Psychiatry. His research focuses on disease and age-related brain neuroplasticity and its impact on cognitive function and motor behavior. He is currently funded by an NIH/NIA K01 award to study neural and behavioral motor profiles as novel biomarkers for Alzheimer's disease.
Lab members
selected publications
- Koppelmans V, Ruitenberg MFL, Schaefer SY, King JB, Hoffman JM, Mejia AF, Tasdizen T, Duff K (2023). Delayed and More Variable Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers and Applications for Classification. J Alzheimers Dis.
- Ruitenberg MFL, Koppelmans V, Seidler RD, Schomaker J (2023). Developmental and age differences in visuomotor adaptation across the lifespan. Psychol Res
- Ruitenberg MFL, Koppelmans V, Wu T, Averbeck BB, Chou KL, Seidler RD (2022). Neural correlates of risky decision making in Parkinson's disease patients with impulse control disorders. Exp Brain Res.
- Koppelmans V, Silvester B, Duff K (2022). Neural Mechanisms of Motor Dysfunction in Mild Cognitive Impairment and Alzheimer's Disease: A Systematic Review. [Review]. J Alzheimers Dis Rep, 6(1), 307-344.
- Koppelmans V, Mulavara AP, Seidler RD, De Dios YE, Bloomberg JJ, Wood SJ (2022). Cortical thickness of primary motor and vestibular brain regions predicts recovery from fall and balance directly after spaceflight. Brain Struct Funct, 227, 2073-2086.
- Mejia AF, Koppelmans V, Jelsone-Swain L, Kalra S, Welsh RC (2022). Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS. Neuroimage, 255, 119180.
- Ruitenberg MFL, Koppelmans V, Seidler RD, Schomaker J (2021). Novelty exposure induces stronger sensorimotor representations during a manual adaptation task. Ann N Y Acad Sci, 1510(1), 68-78.
- Waskowiak P, Koppelmans V, Ruitenberg MFL (2021). Trait Anxiety as a Risk Factor for Impulse Control Disorders in de novo Parkinson's Disease. J Parkinsons Dis, 12(2), 689-697.