Model of Muscle Spindle Proprioception


Muscle Spindle

Overview
Proprioceptors such as muscle spindles and Golgi tendon organs provide the CNS with sensory feedback for motor control and kinesthesia.  It is difficult to record afferent activity from such receptors during motor behavior, so theories of motor control usually depend on implicit or explicit assumptions about such activity.  The muscle spindle is the most important proprioceptor, playing a dominant role in kinesthesia and in the reflexive adjustments to perturbations.  Its fusimotor apparatus can shift the relative sensitivity of its receptors over a wide range of lengths and velocities, at the cost of complicating the interpretation of their signals by the nervous system and by researchers.  We have constructed a physiologically realistic model of the spindle that is composed of mathematical elements closely related to the anatomical components found in the biological spindle.  The spindle model consists of three nonlinear intrafusal fiber models (bag1, bag2, chain) that contribute variously to action potential generation of primary and secondary afferents. The model accurately captures the spindle’s behavior during a variety of ramp, triangular and sinusoidal stretches, and during different fusimotor conditions.  In the case of simultaneous static and dynamic fusimotor stimulation, the model demonstrates the experimentally observed partial occlusion effect.  The model also incorporates the appropriate temporal properties of three types of intrafusal fibers during static or dynamic fusimotor stimulation.  The advantage of including these properties is demonstrated by comparing model simulations with and without these properties to data from recently published experiments in which both fusimotor efferent and spindle afferent activity were recorded simultaneously during decerebrate locomotion in the cat (Taylor et al., J Physiol 529.3: 825-836, 2000).

The spindle model can be inverted to compute fusimotor drive from recordings of spindle afferent activity and muscle kinematics.  Once the principles of fusimotor control are understood, it should be possible to apply the spindle model to predict more accurately the activity of spindle afferents and their role in control of motor tasks.

Questions/Comments
For questions or comments regarding the model of muscle spindle, please contact Gerald E. Loeb (gloeb@usc.edu).


Alfred Mann Institute University of Southern California