Reference frames for spinal proprioception: Limb endpoint based or joint-level based?

Many sensorimotor neurons in the CNS encode global parameters of limb movem ent and posture rather than specific muscle or joint parameters. Our invest igations of spinocerebellar activity have demonstrated that these second-or der spinal neurons also may encode proprioceptive information in a limb-bas ed rather than joint-based reference frame. However, our finding that each foot position was determined by a unique combination of joint angles in the passive limb made it difficult to distinguish unequivocally between a limb -based and a joint-based representation. In this study, we decoupled foot p osition from limb geometry by applying mechanical constraints to individual hindlimb joints in anesthetized cats. We quantified the effect of the join t constraints on limb geometry by analyzing joint-angle covariance in the f ree and constrained conditions. One type of constraint, a rigid constraint of the knee angle, both changed the covariance pattern and significantly re duced the strength of joint-angle covariance. The other type, an elastic co nstraint of the ankle angle, changed only the covariance pattern and not it s overall strength. We studied the effect of these constraints on the activ ity in 70 dorsal spinocerebellar tract (DSCT) neurons using a multivariate regression model, with limb axis length and orientation as predictors of ne uronal activity. This model also included an experimental condition indicat or variable that allowed significant intercept or slope changes in the rela tionships between foot position parameters and neuronal activity to be dete rmined across conditions. The result of this analysis was that the spatial tuning of 37/70 neurons (53%) was unaffected by the constraints, suggesting that they were somehow able to signal foot position independently from the specific joint angles. We also investigated the extent to which cell activ ity represented individual joint angles by means of a regression model base d on a linear combination of joint angles. A backward elimination of the in significant predictors determined the set of independent joint angles that best described the neuronal activity for each experimental condition. Final ly, by comparing the results of these two approaches, we could determine wh ether a DSCT neuron represented foot position, specific joint angles, or no ne of these variables consistently. We found that 10/70 neurons (14%) repre sented one or more specific joint-angles. The activity of another 27 neuron s (39%) was significantly affected by limb geometry changes, but 33 neurons (47%) consistently elaborated a foot position representation in the coordi nates of the limb axis.