Dynamical Grounding: Closed-loop Control to Evaluate Functional Neural Models, Application to Spinal Pathway

This paper presents a framework supporting enforcement of functional constraints for a range of computational neural models relating to motor control. It builds upon a control structure addressing the tracking problem for a class of neuro-musculoskeletal systems. We illustrate, through a specific example, the manner in which it may be used to investigate functional efficacy of a class of spinal pathway models. Specifically, we assess efficacy of a stretch-reflex model in fulfilling its expected function and compare it to performance to an alternative model proposed here. A discussion of the manner in which the framework can be employed to help constrain a broad range of neural models concludes this paper.