The Stretch Reflex Arc (SRA) is the simplest and most fundamental regulatory mechanism of posture control and muscle contraction. Understanding the details of the functioning of this important biological control system could (a) result in novel tools for the early detection/therapies of neuromuscular diseases such as Amyotrophic Lateral Sclerosis (ALS), (b) help explain certain pathological conditions such as spasticity that are secondary to Spinal Cord Injury (SCI), as well as (c) lead to the development of novel in-silico control systems (adaptive sensors, non-linear controllers, novel movement control in robotics, etc). The overall goal in the proposed study is to establish a data-true non-linear dynamic model of the SRA and examine the effects of modulatory neurotransmission on the overall stability of the SRA.
Our specific aims are: 1. To characterize the nonlinear dynamics of the basic elements (DRG cells, motoneurons, skeletal muscle) and subsystems (namely, DRG AE motoneuron, motoneuron AE muscle) of the SRA by using electrophysiological and mechanical measurements in a well defined in vitro test bed. 2. To recreate the overall dynamic response of the SRA in simulation by utilizing component models obtained in aim 1 and integrating those with standard models from literature for components for which cultures are not available in our laboratory. 3. To quantify the effect of the neurotransmitters serotonin and norepinephrine on the non-linear dynamics of the DRG AE motoneuron segment. 4. To compare the overall dynamic response of the SRA under increased monoaminergic drive with that obtained under healthy conditions. Towards achieving our specific aims, the confluence of experimental, analytical, and computer simulation techniques will be exploited. Broadly, experiments for modeling SRA components will involve bandlimited white noise current injection in current clamp mode into patch-clamped cells with concurrent recording of action potentials (or contraction force in the case of the muscle). Experiments for modeling subsystems will use similar methodology as stated above except that dual patch clamp recordings on a presynaptic and a postsynaptic cell will be obtained. Analysis will involve quantification of component or subsystem models in terms of linear and non-linear filters (kernels) - optimization techniques will be utilized to restrict the complexity of the models. Nonlinear component and subsystem models obtained would be interfaced in computer simulation to recreate the overall experimentally observed behavior of the SRA.
The direct or indirect involvement of the stretch reflex arc (SRA) has been implicated in diseases such as ALS, Parkinson's disease and in generation of spasticity after Spinal Cord Injury. Deeper understanding of the dynamic non-linear behavior of the SRA and its neuromodulation could (a) help to understand the development of the motor symptoms of these diseases, (b) result in novel methods for early detection, and (c) offer novel strategies for noninvasive monitoring of the effectiveness of possible therapies. A non-linear dynamic model of the SRA would also be of critical importance to the development of any interface between biological and man-made components - be it neuronally driven prosthetics or cyber driven musculature.
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