Abstract
Recent advances in microelectrode array technology now permit a direct examination of the way populations of sensory neurons encode information about a limb's position in space. To address this issue, we recorded nerve impulses from about 100 single units simultaneously in the L6 and L7 dorsal root ganglia (DRG) of the anesthetized cat. Movement sensors, placed near the hip, knee, ankle, and foot, recorded passive movements of the cat's limb while it was moved pseudo-randomly. The firing rate of the neurons was correlated with the position of the limb in various coordinate systems. The firing rates were less correlated to the position of the foot in Cartesian coordinates (x, y) than in joint angular coordinates (hip, knee, ankle), or in polar coordinates. A model was developed in which position and its derivatives are encoded linearly, followed by a nonlinear spike-generating process. Adding the nonlinear portion significantly increased the correlations in all coordinate systems, and the full models were able to accurately predict the firing rates of various types of sensory neurons. The observed residual variability is captured by a simple stochastic model. Our results suggest that compact encoding models for primary afferents recorded at the DRG are well represented in polar coordinates, as has previously been suggested for the cortical and spinal representation of movement. This study illustrates how sensory receptors encode a sense of limb position, and it provides a general framework for modeling sensory encoding by populations of neurons.
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