The hypothesis that the central nervous system (CNS) generates movement as a shift of the limb's equilibrium posture has been corroborated experimentally in studies involving single- and multijoint motions. Posture may be controlled through the choice of muscle length-tension curve that set agonist-antagonist torque-angle curves determining an equilibrium position for the limb and the stiffness about the joints. Arm trajectories seem to be generated through a control signal defining a series of equilibrium postures. The equilibrium-point hypothesis drastically simplifies the requisite computations for multijoint movements and mechanical interactions with complex dynamic objects in the environment. Because the neuromuscular system is springlike, the instantaneous difference between the arm's actual position and the equilibrium position specified by the neural activity can generate the requisite torques, avoiding the complex “inverse dynamic” problem of computing the torques at the joints. The hypothesis provides a simple, unified description of posture and movement as well as contact control task performance, in which the limb must exert force stably and do work on objects in the environment. The latter is a surprisingly difficult problem, as robotic experience has shown. The prior evidence for the hypothesis came mainly from psychophysical and behavioral experiments. Our recent work has shown that microstimulation of the frog spinal cord's premotoneural network produces leg movements to various positions in the frog's motor space. The hypothesis can now be investigated in the neurophysiological machinery of the spinal cord.

This target article draws together two groups of experimental studies on the control of human movement through peripheral feedback and centrally generated signals of motor commands. First, during natural movement, feedback from muscle, joint, and cutaneous afferents changes; in human subjects these changes have reflex and kinesthetic consequences. Recent psychophysical and microneurographic evidence suggests that joint and even cutaneous afferents may have a proprioceptive role. Second, the role of centrally generated motor commands in the control of normal movements and movements following acute and chronic deafferentation is reviewed. There is increasing evidence that subjects can perceive their motor commands under various conditions, but that this is inadequate for normal movement; deficits in motor performance arise when the reliance on proprioceptive feedback is abolished either experimentally or because of pathology. During natural movement, the CNS appears to have access to functionally useful input from a range of peripheral receptors as well as from internally generated command signals. The unanswered questions that remain suggest a number of avenues for further research.

It is increasingly clear that spinal reflex systems cannot be described in terms of simple and constant reflex actions. The extensive convergence of segmental and descending systems onto spinal interneurons suggests that spinal interneurons are not relay systems but rather form a crucial component in determining which muscles are activated during voluntary and reflex movements. The notion that descending systems simply modulate the gain of spinal interneuronal pathways has been tempered by the observation that spinal interneurons gate and distribute descending control to specific motoneurons. Spinal reflex systems are complex but current approaches will continue to provide insight into motor systems. During movement, several neural mechanisms act to reduce the functional complexity of motor systems by inhibiting some of the parallel reflex pathways available to segmental afferents and descending systems. The flexion reflex system is discussed as an example of the flexibility of spinal interneuron systems and as a useful conceptual construct. Examples are provided of the kinds of experiments that can be developed using current approaches to spinal interneuronal systems.

Engineers use neural networks to control systems too complex for conventional engineering solutions. To examine the behavior of individual hidden units would defeat the purpose of this approach because it would be largely uninterpretable. Yet neurophysiologists spend their careers doing just that! Hidden units contain bits and scraps of signals that yield only arcane hints about network function and no information about how its individual units process signals. Most literature on single-unit recordings attests to this grim fact. On the other hand, knowing a system's function and describing it with elegant mathematics tell one very little about what to expect of interneuronal behavior. Examples of simple networks based on neurophysiology are taken from the oculomotor literature to suggest how single-unit interpretability might decrease with increasing task complexity. It is argued that trying to explain how any real neural network works on a cell-by-cell, reductionist basis is futile and we may have to be content with trying to understand the brain at higher levels of organization.

Prevailing engineering-inspired theories of motor control based on sequential/algorithmic or motor-programming models are difficult to reconcile with what is known about the anatomy and physiology of the motor areas. This is partly because of certain problems with the theories themselves and partly because of features of the cortical and basal ganglionic motor circuits that seem ill-suited for most engineering analyses of motor control. Recent developments in computational neuroscience offer more realistic, that is, connectionist, models of motor processing. The distributed, highly parallel, and nonalgorithmic processes in these models are inherently self-organizing and hence more plausible biologically than their more traditional algorithmic or motor-programming counterparts. The newer models also have the potential to explain some of the unique features of natural, brain-based motor behavior and to avoid some of the computational dilemmas associated with engineering approaches.

The premise explored in this target article is that the function of the cerebellum is best understood in terms of the operation it performs across its structurally homogeneous subdivisions. The functional heterogeneity sometimes ascribed to these different regions reflects the multiplicity of functions subserved by the central targets receiving the outputs of different cerebellar regions. Recent studies from our own laboratory and others suggest that the functional unit of the cerebellum is the sagittal zone. It is hypothesized that the climbing fiber system produces a short-lasting modification in the gain of Purkinje cell responses to its other principal afferent input, the mossy fiber-granule cell-parallel fiber system. Because the climbing fiber inputs to sagittally aligned Purkinje cells can be activated under functionally specific conditions, these afferents could select populations of Purkinje neurons that would be most highly modulated by mossy fiber inputs responding to the same conditions. These operations may be critical for the on-line integration of inputs characterizing external target space with features of the intended movement, proprioceptive and kinesthetic cues, and the body image.

To investigate neural mechanisms of movement, physiologists have analyzed the activity of task-related neurons in behaving animals. The relative onset latencies of neural activity have been scrutinized for evidence of a functional hierarchy of sequentially recruited centers, but experiments reveal that activity changes occur largely in parallel. Neurons whose activity covaries with movement parameters have been sought for evidence of explicit coding of parameters such as active force, limb displacement, and behavioral set. Neurons with recognizable relations to the task are typically selected from a larger population, ignoring those cells with complex relations to the task and unmodulated cells. Selective interpretations are also used to support the notion that different motor regions perform different motor functions; again, current evidence suggests that units with similar properties are distributed over widely different regions.

These coding issues are reexamined for premotoneuronal (PreM) cells, whose correlational links with motoneurons are revealed by spike-triggered averages. PreM cells are recruited over long times relative to their target muscles; they show diverse response patterns relative to the muscle force they produce; functionally disparate PreM cells such as afferent fibers and descending corticomotoneuronal and rubromotoneuronal cells can exhibit similar patterns. Neural mechanisms have been further elucidated by neural network simulations of sensorimotor behavior; the pre-output hidden units typically show diverse response patterns in relation to their target units. Thus, studies in which both the activity and the connectivity of the same units are known reveal that units with both simple and complex relations to the task contribute significantly to the output. This suggests that the search for explicit coding may be diverting us from understanding distributed neural mechanisms that operate without literal representations.

The posterior parietal cortex (PPC) is the most likely site where egocentric spatial relationships are represented in the brain. PPC cells receive visual, auditory, somaesthetic, and vestibular sensory inputs; oculomotor, head, limb, and body motor signals; and strong motivational projections from the limbic system. Their discharge increases not only when an animal moves towards a sensory target, but also when it directs its attention to it. PPC lesions have the opposite effect: sensory inattention and neglect. The PPC does not seem to contain a “map” of the location of objects in space but a distributed neural network for transforming one set of sensory vectors into other sensory reference frames or into various motor coordinate systems. Which set of transformation rules is used probably depends on attention, which selectively enhances the synapses needed for making a particular sensory comparison or aiming a particular movement.