A Nonlinear Dynamical Technique for Improving the Function of the Human Postural Control System

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9634024 Collins The objective of this project, which is a renewal proposal of a prior NSF award, is to develop a noise-based technique which can be used to lower the detection thresholds of the proprioceptive system and thereby improve the performance of the human postural control system. Upright stance in humans is regulated by a complex control system that involves a number of different sensory mechanisms, including the proprioceptive system. Aperiodic stochastic resonance (ASR) is a phenomenon wherein the response of a nonlinear system to a subthreshold aperiodic input signal is optimized by the presence of a particular level of noise. ASR has been demonstrated in a simple neuronal model and in cutaneous sensory neurons. This work suggests that it should be possible to introduce noise artificially into a neurophysiological sensory system (e.g., the proprioceptive system) in order to improve its ability to detect arbitrary subthreshold signals. To date, however, bioengineering applications have not been explored. The specific objectives of this study are 1) to develop a physiologically-realistic neuronal model as a test-bed for bioengineering applications of ASR; 2) to demonstrate that the detection thresholds of the proprioceptive system are changed with the addition of input noise; and 3) to demonstrate that noise-induced changes to the proprioceptive detection thresholds at the ankle affect the postural control system. This work could result in the development of an inexpensive technique for improving the performance of the human postural control system. Such a technique could have important ramifications for individuals with elevated proprioceptive thresholds, such as older adults and patients with neural disorders, who may be predisposed to falls. Thus, the results of this project could eventually serve to reduce the incidence, cost, and health risks of falling. ***