Understanding of the λ model has greatly increased in recent years as evidenced by most of the commentaries. Some commentators underscored the potential of the model to integrate aspects of different sensorimotor systems in the production of movement. Other commentators focused on not-yet-fully-developed parts of the model. A few persisted in misunderstanding some of its basic concepts, and on these grounds they reject it. In responding to commentaries we continue to elaborate on some fundamental points of the model, especially control (...) variables, the idea of movement production by shifting the positional frame of reference and the hypothesis of biomechanical correspondence in motor control. We also continue to develop our ideas on the intrinsic generation of the frame of reference associated with external space and utilized for the control of arm movement and locomotion. The dynamic principles underlying the model are discussed in light of the dynamical systems approach. (shrink)

The authors report that the reorganization of body configuration during weightlessness is based on an intrapersonal frame of reference such as the configuration of the support surface and the position of the body's center of gravity. These results stress the importance of “knowledge” of the state of internal geometric structures, which cannot be directly signalled by specific receptors responsible for direct dialogue with the physical external world.

We criticize the synaptic theory of long-term memory and the inappropriate usage of physical notions such as in motor control theories. Motor control and motor memory hypotheses should be based on explicitly specified hypothetical control variables that are sound from both physiological and physical perspectives. [HOUK et al.; SMITH; THACH].

The equilibrium-point hypothesis (the λ-model) is superior to all other models of single-joint control and provides deep insights into the mechanisms of control of multi-joint movements. Attempts at associating control variables with neurophysiological variables look confusing rather than promising. Probabilistic mechanisms may play an important role in movement generation in redundant systems.

The problem for the CNS in any particular movement task is to coordinate the various frames of reference appropriate to the task. Control variables are determined by this coordination. The coordination problem varies greatly from task to task, and so no single set of control variables is likely to account for a broad range of movement tasks.

This article reviews models of the cerebellum and motor learning, from the landmark papers by Marr and Albus through those of the present time. The unique architecture of the cerebellar cortex is ideally suited for pattern recognition, but how is pattern recognition incorporated into motor control and learning systems? The present analysis begins with a discussion of exactly what the cerebellar cortex needs to regulate through its anatomically defined projections to premotor networks. Next, we examine various models showing how the (...) microcircuitry in the cerebellar cortex could be used to achieve its regulatory functions. Having thus defined what it is that Purkinje cells in the cerebellar cortex must learn, we then evaluate theories of motor learning. We examine current models of synaptic plasticity, credit assignment, and the generation of training information, indicating how they could function cooperatively to guide the processes of motor learning. (shrink)

The experiments Feldman and Levin suggest do not definitively test their proposed solution to the problem of selecting muscle activations. Their test of the movement directions that elicit EMG activity can be interpreted without regard to the form of the central commands, and their fast elbow flexion test is based on a forward computation that obscures the insensitivity of the predicted trajectory to the details of the putative commands.

We argue that the concept of a control variable (CV) as described by Feldman and Levin needs to be revised because it does not account for the influence of sensory feedback from the periphery. We provide evidence from the realm of rhythmic movements that sensory feedback can permanently alter the frequency and phase of a centrally generated rhythm.

The lambda model predicts that the command received by each motor nucleus during locomotion is specific for the joint at which its muscle acts and is independent of external conditions. However, investigation of the commands received by motor nuclei during fictive locomotion and of the sensitivity of these commands to feedback from the limb during locomotion indicates that neither condition is satisfied.

Extrapersonal frames of reference for aimed movements are representationally convenient. They may, however, carry associated costs when the movement is executed in terms of the complex coordination of multiple joints they require. Studies that have measured both fingertip and joint paths suggest the motor systems may seek a compromise between simplicity of extrapersonal spatial representation and computational simplicity of multi-joint execution.

Models of central control variables (CVs) that are expressed in positional reference frames and rely on proprioception as the dominant specifier of muscle activation patterns have not yet been shown to be adequate for the description of fast, voluntary movement, even of single joints. An alternative model with illustrative data is proposed.

Kinematic properties of reaching movements reflect constraints imposed on the joint angles. Contemporary models present solutions to the redundancy problem by a pseudoinverse procedure (Whitney 1969) or without any inversion (Berkenblit et al. 1986). Feldman & Levin suggest a procedure based on a regular inversion. These procedures are considered as an outcome of a more general approach.

The search for simplifying principles in motor control motivates the target article. One method that the CNS uses to simplify the task of controlling a limb's mechanical properties is absent from the article. Evidence from multi-joint, force-field measurements and from kinematics that points to the existence of multi-joint primitives as control variables is discussed.

Recent results have shown that the relative activation of muscles is different for isometric contractions and for movements. These results exclude an explanation of muscle activation patterns by a combination ofreciprocal and coactivation commands. These results also indicate that joint stiffness is not uniquely determined and that it may be different for isometric contractions and movements.

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].

The λ model suggests that detailed kinematics arise from changes in control variables and need not be explicitly planned. However, we have shown that when moving a grasped object, grip force is precisely modulated in phase with acceleration-dependent inertial load. This suggests that the motor system can predict detailed kinematics. This prediction may be based on a forward model of the dynamics of the loaded limb.

We affirm the dynamical systems approach taken by Feldman and Levin, but argue that a more mathematically rigorous and standard exposition of the model according to dynamical systems theory would greatly increase readability and testability. Such an explication would also have heuristic value, suggesting new variations of the model. We present one such variant, a new solution to the redundancy problem.

The lambda model of Feldman & Levin for intentional hand movement is compared with a hemispheric motor model (IIMM). Both models imply similar conclusions independently. This increases the validity of both models.

A hypothesis about sensorimotor integration (the λ model) is described and applied to movement control and kinesthesia. The central idea is that the nervous system organizes positional frames of reference for the sensorimotor apparatus and produces active movements by shifting the frames in terms of spatial coordinates. Kinematic and electromyographic patterns are not programmed, but emerge from the dynamic interaction among the system s components, including external forces within the designated frame of reference. Motoneuronal threshold properties and proprioceptive inputs to (...) motoneurons may be cardinal components of the physiological mechanism that produces positional frames of reference. The hypothesis that intentional movements are produced by shifting the frame of reference is extended to multi-muscle and multi-degrees-of-freedom systems with a solution of the redundancy problem that allows the control of a joint alone or in combination with other joints to produce any desired limb configuration and movement trajectory. The model also implies that for each motor behavior, the nervous system uses a strategy that minimizes the number of changeable control variables and keeps the parameters of these changes invariant. Examples are provided of simulated kinematic and electromyographic signals from single- and multi-joint arm movements produced by suggested patterns of control variables. Empirical support is provided and additional tests of the model are suggested. The model is contrasted with others based on the ideas of programming of motoneuronal activity, muscle forces, stiffness, or movement kinematics. (shrink)

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)

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 concept of a conservative control strategy minimizing the number of degrees of freedom used is criticised with reference to 3-D simple reaching and grasping experiments. The vector error in a redundant system would not be the prime controlled variable, but rather the posture for reaching, as exemplified by nearly straight displacements in joint space as opposed to curved ones in task space.