A numerical simulation of muscle spindle ensemble encoding during planar movement of the human arm.

We address the issue of what proprioceptive information, regarding movement of the human arm, may be provided to the central nervous system by proprioceptors located within muscles of this limb. To accomplish this we developed a numerical simulation which could provide estimates of the length regimes experienced by a set of model receptors located within some of the principal muscles of the human arm during planar movement of this limb. These receptors were assumed to have characteristics analogous to those associated with a simple model of muscle spindle signalling of movement. To this end each spindle had proprioceptive 'channels' associated with it. These corresponded to primary and secondary spindle afferent fibers which could provide independent afferent output regarding the parent muscle the spindle monitored. The angles of the shoulder and elbow joints attained by subjects performing a task requiring movement of the right arm in a horizontal plane to a static visual target were recorded. For this angular data the lengths and rates of change of lengths experienced by muscle fascicles, and hence the model spindles, during movement were calculated by means of the numerical simulation. The discharge rates of the simulated spindles during the movement were calculated to derive a measure of the depth of modulation, induced by the movement, for each spindle. These values were then summed for all spindles to provide a first-order approximation of spindle ensemble coding of the movement. Significant correlations (P < 0.0001, Spearman's rank order) were found between the resulting ensemble encodings and, in order of significance, the angular velocity of the shoulder joint (rS = 0.945), the tangential velocity of the hand (rS = 0.942), and the angular velocity of the elbow joint (rS = 0.917). Correlations between the angular positions of the shoulder (rS = -0.623) and elbow (rS = 0.628) were lower. These findings indicate that the ensemble profiles of the simulated muscle spindles, encode information regarding kinematic parameters of movements related to both intrinsic and extrinsic coordinate systems. This suggests that motor structures capable of deriving such an ensemble encoding would be in a position to perform the sensory-motor transformations between intrinsic and extrinsic frames of reference necessary for controlling movements planned in extrinsic coordinates.

A numerical simulation of muscle spindle ensemble encoding during planar movement of the human arm: correlation sensitivity and parameter dependence.

We extend the analysis developed in the preceding paper in which we correlated kinematic parameters of planar movements of the human arm made by subjects moving to a visual target with numerical estimates of the ensemble encoding of muscle spindles within some of the muscles of this limb. Three possible models for the inclusion of noise in the calculations of the ensemble encodings are considered: (i) random errors in the angular coordinates from which muscle fascicle, and hence spindle length are calculated, (ii) variability of spindle discharge rates, and (iii) variability in the calculation of the ensemble encoding. In each case the correlations between kinematic variables of the movements and the resultant ensemble encodings decrease as the contribution of the noise term to the calculation of the encodings increases. Subject to the constraint that the magnitude of the noise term remains within physiologically realistic limits, however, the observed correlations persist at statistically significant levels. We also investigate the dependence of the observed correlations on the choice of model parameters, namely (i) the absolute and relative contributions made by simulated spindle primary and secondary afferents to the ensemble encoding, (ii) the inclusion of explicit length-related terms in the model of muscle spindle discharge, and (iii) the fractional power of velocity experienced by the model spindles during movement. The resulting correlations are approximately independent of both the fractional power of velocity and absolute firing levels of both the primary and secondary afferents of the spindle model. The inclusion of explicit length-dependent terms in the model does result in differences in the observed correlation coefficients. In this case, however, the magnitudes of the differences are small. On the basis of these findings we conclude that the correlations between kinematic variables of movement and the associated ensemble encodings are robust with regard to both the choice of model parameters and noise inherent at all stages of the transduction and processing of proprioceptive information. The findings of the present study provide further evidence, therefore, to support the hypothesis that motor structures capable of deriving such an ensemble encoding would be provided with information regarding ongoing movements in both intrinsic (body-centered) and extrinsic (Cartesian) coordinate systems.