A Computational Perspective on Proprioception and Movement Guidance in Parietal Cortex

Computational models can offer much to our attempts to understand biological motor control. Even a naïve model can at least act as a mnemonic device, helping to organize one’s knowledge of a body of data. Of course, most models aspire to much more. One would expect that a good model not only provides a coherent and unifying explanation of data, but also generates testable hypotheses, which can influence future experimental work. Ultimately, what is most desirable is a complementary relationship between models and experiments, where each serves to refine the other.