Papers
1
Total Citations
2
H-Index
1
About
David Grow is a researcher whose work bridges computational modeling and motor control, with a primary focus on understanding the neural basis of movement disorders. His key research areas include cerebellar function, motor planning, and the biomechanics of reaching movements. Grow is best known for his 2014 study, "Testing models of cerebellar ataxia via dynamic simulation," which critically examined the prevailing hypothesis that the cerebellum acts as an internal model for movement planning. By simulating the dynamics of ataxic movements, he demonstrated how cerebellar damage leads to uncoordinated reaching due to a failure to account for arm dynamics. This work has been cited 2 times and provides a foundational framework for linking neural deficits to observable motor behavior. Grow’s contributions are particularly valuable for students and researchers interested in computational neuroscience, rehabilitation engineering, and the intersection of robotics and neurology. His careful integration of dynamic simulation with clinical data exemplifies how modeling can test and refine theories of brain function, offering a clear path toward more effective therapies for movement disorders.
Research Focus
Key Achievements
Top Papers
- 1Testing models of cerebellar ataxia via dynamic simulation2 citations · 2014