Project Description
The Neuromechanics lab combines ideas from neuroscience, economics and biomechanics to understand the costs and rewards underlying movement control. Using modeling, robotic interfaces, and virtual reality, we try to reverse engineer how the brain selects and controls movements. The investigations provide insight into the interplay between the neural processes underlying movement control, decision-making, and learning.
This project will examine how effort costs modulate learning in a walking task. Participants will walk on a treadmill with separate belts for each foot while wearing a weighted vest to differentiate effort levels. The DLA student will work directly with experiment participants and collect motion capture and force plate data to investigate learning dynamics while the two belts run at different speeds and whether effort cost modulates this process. Data analyses will examine movements and forces during learning and apply learning models to compare between effort levels. Throughout the project, the DLA student will work closely with a graduate student to procure,analyze, and present data and explore the implications of effort costs on learning and rehabilitation.
Special Requirements
Student should have basic programming skills (preferably familiar with MATLAB or python).
Contact
- Alaa Ahmed (faculty)
- Rachel Marbaker (graduate student)