My PhD work focused on the Lokomat robotic gait training device and measuring the actual forces that patients exerted during training in this device. As a postdoc I am currently investigating the ability of a rodent robotic gait training device to restore overground locomotion following cervical spinal cord injury and the underlying plasticity of the central nervous system in response to the training. In both human and animal robotic gait trainers, the training consists of actively guiding the limbs through a symmetric healthy gait pattern. As an independent researcher I propose to study different training patterns, specifically training within asymmetric force fields, in order to find the optimal robotic training. Asymmetric training can also be applied to other tasks, such as skilled reaching. Therefore I intend to show that the asymmetric training of both locomotion and reaching will lead to greater functional improvements in a variety of tasks and greater neuronal plasticity than the conventional symmetric training. By uncovering the optimal training techniques in animal models, clinical training practices may then be improved.
Following neurological injury, physical training has long been a favored treatment option among clinicians. Unfortunately, clinical practices are not always justified with the appropriate background animal research and experimental findings in animal models do not always make their way into the clinical setting. The proposed project aims to bridge this gap by first optimizing robotic treadmill training in rodent models, which would help maximize the robotic treadmill training of patients. Then by applying clinical techniques of asymmetric training, we aim to increase the effectiveness of skilled forelimb training of rodents following a cervical spinal cord injury.