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Workshop 3: Biomechanics and Neural Control - Muscle, Limb, and Brain (January 14-18, 2008)

Organizers: Art Kuo, Lena Ting, John Guckenheimer, and Anthony Bloch

Biological movement is governed by a complex interplay between the central nervous system and the musculoskeletal system. The nervous system has conventionally been thought to reside atop a hierarchical control system. The periphery was thought to receive motor commands, with the role of integrating, filtering, and acting upon those commands. However, neuroscientists have gathered increasing evidence that supports a more collaborative control structure. Most evident is the importance of feedback loops that provide sensory information not only locally but also from throughout the periphery. Feedforward components to motor control have gradually given way to feedback, where there is no hierarchy. Instead, each system contributes to the overall behavior of a feedback loop. The nervous system receives sensory information, with the role of integrating, filtering, and acting upon that feedback. Recent evidence indicates that an internal representation of body and environment dynamics contributes to sensorimotor integration for state estimation and motor planning.

The collaboration between sensors, actuators, limbs, and neurons is a systems problem. The physiology of these components is increasingly understood in quantitative terms. The dynamics of these components, however, are not well understood, especially when they interact. A systems approach is ideal for studying the organization of the nervous system and its interplay with the musculoskeletal system. It is critical for experts in areas such as muscle physiology, body and limb mechanics, and neurophysiology, to share knowledge, not only in descriptive terms, but also in a mathematical language amenable to a systems approach.

The goal of this workshop is to foster interaction between experts on muscle, limb, and brain. The proposed speakers include pioneers in the use of mathematical tools in biomechanics, as well as state-of-the-art experimentalists whose approaches may not be quantitative but are nonetheless amenable to a systems approach.