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. (shrink)

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. (shrink)

This study examines how a Purkinje cell receives its appropriate olivary error signal during the learning of compound movements. We suggest that the Purkinje cell only reinforces those target pyramidal cells which already participate in the movement, subsequently reducing any repeated error signal, such as its own climbing fiber input, [simpson et al.; smith].

The cerebellum probably obeys the rules of sensorimotor integration common in the nervous system. One such a rule is formulated: the nervous system organizes spatial frames of reference for the sensorimotor apparatus and produces voluntary movements by shifting their origin points. We give examples of spatial frames of reference for different single- and multi-joint movements including locomotion and also illustrate that the process of motor development and learning may depend critically on the formation of appropriate frames of reference and the (...) organism's ability to manage them. We suggest that a solution to the problem of sensorimotor integration may not be trivial and may actually change the mental and experimental paradigms used in the understanding of the cerebellum and other brain structures, [HOUK et al.; SIMPSON et al.; SMITH; TIIACH]. (shrink)

We suggest that the cerebellum generates sensory or estimates based on outgoing motor commands and sensory feedback. Thus, it is not a motor pattern generator (HOUK et al.) but a predictive system which is intimately involved in motor behavior. This theory may explain the sensitivity of the climbing fibers to both unexpected external events and motor errors (SIMPSON et al.), and we speculate that unusual biophysical properties of the inferior olive might allow the cerebellum to develop multiple asynchronous sensory estimates, (...) [HOUK et al.; SIMPSON et al.; THACH]. (shrink)

The views of Houk et al., Smith, and Thach on the role of cerebellum in movement control differ substantially, but all three are flawed by the false reasoning that because information passes from the cerebellum to movements the cerebellum must be a movement controller, or a part of one. The divergent and less than compelling ideas expressed by these leading cerebellar theorists epitomize the fruitlessness of this paradigm, and signal the need for a change. [HOUK et al.; SMITH; THACH].

For reasons I have never understood, some students of the cerebellum have been unwilling to accept the now overwhelming evidence that the cerebellum exhibits lasting synaptic plasticity and plays an essential role in some forms of learning and memory. With a few exceptions (e.g., target article by SIMPSON et al.) this is no longer the case, as is clear in the excellent target articles on cerebellar LTD and the excellent target review by HOUK et al. [CRÉPEL et al.; HOUR et (...) al.; KANO; LINDEN; SIMPSON et al.; SMITH; VINCENT]. (shrink)

The target article on cellular mechanisms of long-term depression appears to have been well received by most authors of the relevant commentaries. This may be due to the fact that this review aimed to give a general account of the topic, rather than just describe previous work of the present author. The present response accordingly only raises questions of major interest for future research.

The involvement of nitric oxide in cerebellar long-term depression is supported by the observation that nitric oxide is released by climbing fiber stimulation and by pharmacological tool usage. Two forms of long-term depression should be distinguished by their physiological relevance. [CRÉPEL et al.; LINDEN; VINCENT].

The present commentary considers the question of what must be learned in different types of motor skills, thereby limiting the question of what should be adjusted in the APG model in order to explain successful learning. It is concluded that an open loop model like the APG might well be able to describe the learning pattern of motor skills in a stable, predictable environment. Recent research on saccadic plasticity, however, illustrates that motor skills performed in an unpredictable environment depend heavily (...) on sensory (mostly visual) feedback, [HOUK et al.]. (shrink)

Several themes can be identified in the commentaries. The first is that the climbing fibers may have more than one function; the second is that the climbing fibers provide sensory rather than motor signals. We accept the possibility that climbing fibers may have more than one function consequence(s)’ in the title. Until we know more about the function of the inhibitory input to the inferior olive from the cerebellar nuclei, which are motor structures, we have to keep open the possibility (...) that the climbing fiber signals can be a combination of sensory and motor signals. (shrink)

PET studies using classical conditioning paradigms are reported. It is emphasized that PET studies show and not in learning paradigms. The importance of dissociating motor performance and learning deficits in human lesions studies is demonstrated in two exemplary studies. The different role of the cerebellum in adaptation of postural reflexes and learning of complex voluntary arm movements is discussed, [THACH].

Studies comparing movement-related cortical potentials, post-excitatory inhibition after transcranial magnetic brain stimulation, and PET findings in normal controls and patients with cerebellar degeneration demonstrate plasticity of cerebro-cerebellar interactions and hereby support Thach's theory that the cerebellum has the ability to play a role in building behavioral context-response linkages and to build up appropriate responses from simpler constitutive elements, [THACH].

The adjustable pattern generator (APG) model addresses physiological detail in a manner that renders it eminently testable. However, the problem for which the APG was developed, namely, limb control, may be computationally too complex for this purpose. Instead, it is proposed that recent empirical and theoretical advances in understanding the role of the cerebellum in low-level saccadic control could be used to refine and extend the APG. [HOUK et al.].

We argue that the function of the cerebellum is more than just an error-detecting mechanism. Rather, the cerebellum plays an important role in all movements. The bias in (re)calibration is an unfortunate restrictive result of a very successful and important experiment, [SMITH, THACH].

In the behavioral literature on human movement, a distinction is made between the learning of parameters and the learning of new movement forms or topologies. Whereas the target articles by Thach, Smith, and Houk et al. provide evidence for cerebellar involvement in parametrization learning and adaptation, the evidence in favor of its involvement in the generation of new movement patterns is less straightforward. A case is made for focusing more attention on the latter issue in the future. This would directly (...) help to bridge the gap between current neurophysiological approaches to the role of the cerebellum and the behavioral expressions of human motor learning, [HOUK et al.; SMITH; THACH]. (shrink)

The primary assumption made in this series of target articles is that the cerebellum is directly involved in motor control. However, in my opinion, there is ample and growing experimental evidence to question this classical view, whether or not learning is involved. I propose, instead, that the cerebellum is involved in the control of data acquisition for many different sensory systems, [CRÉPEL et al., HOUK et al., SMITH, THACH].

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. (shrink)