Welcome to the Cognitive Motor Neuroscience Lab!

The Cognitive Motor Neuroscience Lab is part of the Department of Kinesiology in the College of Nursing and Health Innovation at the University of Texas at Arlington. The primary motivation of our lab is understanding how the brain helps us learn and perform movements, as well as how these cognitive and neural process change throughout our lifespan, in health and disease. We use a combination of behavioral, neuroimaging (i.e., electroencephalography; EEG), and computational techniques and our interdisciplinary research combines approaches from Kinesiology, Cognitive Neuroscience, Psychology, Computer Science, and Engineering.

Our long-term goal is to optimize human performance and brain health throughout the lifespan.

We have three areas of focus:

Motor Behavior
Movement makes life possible. Motor skills underlie activities of daily living (e.g., walking, driving, playing sports, and engaging in our hobbies) and are critical for interacting with people and the environment. We are interested in understanding the motor processes and how they allow us to not only learn and maintain motor skills throughout our life, but also become expert movers and world-class athletes, dancers, musicians, and painters.

Cognition
Cognition powers activities of daily living, and includes processes such as memory, attention, and executive function (i.e., the ability to plan, organize, solve problems, and make decisions). Impairment in cognitive processes is linked to a decrease in quality of life and affects relationships with others and independence. Due to these associations, cognitive impairment is an important public health concern.

Brain Activity
We study human movement through the lens of cognitive neuroscience. We are interested in how brain activity changes when performing cognitive and motor tasks across the lifespan, in health and disease. We use electroencephalography (EEG), a non-invasive technique, to measure electrical brain activity and understand how activity across brain regions changes with behavior. We also apply advanced computational techniques to large behavioral and EEG data sets to discover patterns of activity and associations between brain and behavior to understand how they are disrupted with aging and/or disease.

We study a range of populations, including young adults, older adults, individuals who use cannabis, and patients with movement disorders (e.g., Parkinson’s disease).