| Project Detail |
Simulating muscle response in cerebral palsy
Cerebral palsy is a neurodevelopmental disorder that appears early in childhood and although symptoms may vary, they include poor movement and muscle tone. Particularly, joints demonstrate hyper-resistance to movement, but the underlying aetiology remains poorly understood. Funded by the Marie Sklodowska-Curie Actions programme, the simSpas project is working under the hypothesis that movement history is partly responsible for the observed functional impairment. Researchers will develop a computer simulation test that will allow them to clinically test how muscle responds to stretch during walking or standing. This modelling approach will help improve diagnosis and the quality of life of patients with cerebral palsy.
Joint hyper-resistance to movement affects 85% of children with cerebral palsy (CP), the most common cause of physical disability in children. Joint hyper-resistance is an important treatment target in CP. Yet, its contribution to gait and balance impairments is poorly understood because it has been hard to associate clinical test outcomes to gait and balance deficits. Here, we will test a novel hypothesis about the mechanisms underlying joint hyper-resistance. We hypothesize that the neural component of joint hyper-resistance results from movement history-dependent muscle mechanics and its interaction with background muscle activity and hyperactive reflexes. The movement history-dependent muscle force response to stretch, which drives spindle firing and reflex activity, might explain why it has been so hard to relate clinical test outcomes to functional impairments. Indeed, movement history might be very different when walking than when relaxing during a clinical test. However, it is unfeasible to measure muscle and spindle responses to stretch non-invasively. Hence, we will use computer simulations to test whether the proposed mechanism can explain the response to stretch in clinical tests, during perturbed standing balance, and during walking. This requires two extensions to existing simulation frameworks. First, we will integrate more mechanistic muscle models in whole body simulations of movement as the commonly used phenomenological Hill models do not accurately capture the response to stretch. Second, we will account for uncertainty due to sensorimotor noise when simulating whole body movement as such uncertainty might trigger muscle stretch and maladaptive responses. I will build on my own and the host’s experience to realize these computationally challenging modeling developments. This project might improve the diagnosis and treatment of joint hyper-resistance in CP and has thereby the potential to improve the quality of life of many individuals with CP. |
