FULL, R.J.; Univ. of California, Berkeley: Principles of Neuromechanics: Integration of Experiments, Mathematical and Physical Models

Locomotion results from high-dimensional, dynamically coupled interactions between an organism and its environment. Fortunately, simple models we call templates can resolve the redundancy of multiple legs, joints and muscles. A template is the simplest dynamical system model that exhibits a targeted behavior. For example, diverse species that differ in leg number and posture run in a stable manner like sagittal- and horizontal-plane spring-mass systems. Templates must be grounded in more detailed models to ask questions about multiple legs, the joint torques that actuate them, the recruitment of muscles that produce those torques and the neural networks that activate the ensemble. We term these more elaborate models anchors. Since mechanisms require controls, anchors incorporate hypotheses concerning the manner in which unnecessary motion or energy from legs, joints and muscles is removed, leaving behind the behavior of the body in the low-degree of freedom template. Guided by direct experiments on many-legged animals, mathematical models and physical models (robots), we postulate a hierarchical family of control loops that necessarily include constraints of the body�s mechanics. At the lowest end of this neuromechanical hierarchy, we hypothesize the primacy of mechanical feedback � neural clock excited tuned muscles acting through chosen skeletal postures. On top of this physical layer, we hypothesize sensory feedback driven reflexes that increase an animal�s stability further and, at the highest level, environmental sensing that operates on a stride-to-stride timescale to direct the animal�s body. The challenge of neuromechanical integration demands an interdisciplinary effort to match data systematically across mathematical models, numerical simulations, physical models, as well as biological experiments.