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The 'body schema,' a spatial representation of the body in its environment, has been suggested to be an emergent property of a widespread network of effector-specific frontal and parietal areas, many of which integrate sensory input from the different modalities. On a behavioral level, such multimodality has been shown with temporal order judgment tasks, in which participants decide which of the two hands received a tactile stimulus first. The accuracy of these judgments is influenced by body posture, indicating that tactile stimuli are not simply represented in an anatomical reference frame, but are transformed into external spatial coordinates. So far, these studies have only investigated the hands. It is therefore unclear whether a default remapping of touch into external space is a special feature of visual-manual control or whether all body parts are represented in a common nonanatomically anchored reference frame. In the present study, blindfolded participants made temporal order judgments of stimuli presented to both hands, both feet, or one hand and one foot. The stimulated limbs were held in either a parallel or a crossed posture. Judgments were equally impaired by limb crossing in all limb combinations (hands only, feet only, hand and foot). These results suggest a remapping of tactile location of all body parts into a nonanatomitally anchored and, importantly, common reference frame rather than a specific remapping for eye-hand coordination only. body schema | feet | tactile | temporal order judgment | visual-manual control

It was assumed that kinesthetic modeling has more beneficial effects on learning the tennis serve than visual modeling because the spatial anchor points used to reach targets within the vicinity of the body are mainly defined with respect to the body. Also, we predicted that the efficiency of modeling is also affected by the way the representations are activated mentally. Thirty-two participants were assigned to kinesthetic or visual modeling with or without mental practice. Analyses showed the primacy of kinesthetic representation over visual representation in terms of speed scores and form performances but only if the learner had the opportunity to rehearse the model mentally. The results support the contention that the motor system can program closed skills more easily when one can represent efficiently the kinesthetic image of its later execution.

This article presents a mathematical model of the development of reaching that assumes that the major problem facing infants is their lack of lower level motor control and that infants learn to adjust their reaching strategies as a consequence of their previous experience and to match their current level of control. The model hypothesizes that infant reaches are a series of submovements, with the goal being to get the hand to the target in the face of errors in executed submovements. To relate actual infant reaches to this model, reaching data were decomposed into submovements, using a polynomial fitting algorithm that assumed minimum-jerk submovements. The model makes quantitative predictions about the course of development that are supported by existing results. The validity of the model's underlying assumptions was assessed by comparing the directional variability of the submovements with the variability assumed in the model.

This commentary focuses on issues related to Glover's suppositions regarding the information available to the on-line control system and the behavioral consequences of (visual) information disruption. According to the author, a 'highly accurate,' yet temporally unstable, visual representation of peripersonal space is available for real-time trajectory corrections. However, no direct evidence is currently available to support the position.

In the past, infinite regress criticisms that have been raised about models of motor behavior have been reserved for executive-type models (e.g., Beek & Meijer, 1988). On the basis of Godel's (1930/1986) proof that an algorithm cannot prove its own validity, the authors reason that executive--as well as self-organized-type explanatory models of motor behavior have infinite regress difficulties. The conclusion offered in the present article is that judgments on a model's theoretical importance should be based not on issues of infinite regress but on other relevant characteristics, such as its propensity for falsification (Popper, 1959)., Executive and self-organized emplanatory models of motor behavior are subject to infinite regress problems. Therefore researchers should examine their theoretical importance. Judgements of a model's importance should be based on relative characteristics such as motor programs, schemas, traces, actions systems, nodes and demons when modeling motor behavior., Key words: infinite regress, models, self-organization, theories Beek and Meijer (1988), Edelman (1987), Kelso (1982), and Turvey (1977) have proposed that memory representations used as the basis for motor control [...]

The underdetermination of intentional explanation by motor behavior complicates inferences drawn from preserved artifacts in the archaeological record to intentions in their production. Without knowledge of a producer's intentions, inferences drawn from those intentions to required cognitive abilities for having those intentions is also complicated.

Recent computational models of motor planning have relied heavily on anticipating the consequences of motor acts. Such anticipation is vital for dealing with the redundancy problem of motor control (i.e., the problem of selecting a particular motor solution when more than one is possible to achieve a goal). Computational approaches to motor planning support the Theory of Event Coding (TEC).

In Schmidt's experiments, only properties of actually produced movements systems are measured; in Fitts' experiments, external task parameters are measured too (target size and distance). Thus, the laws contain variables of different natures and cannot be reduced to each other even formally. These difference especially reveals itself in modeling: a model of variability, can be simpler if it deals with the performance variables only. On the other hand, modeling Fitts' law, one should take into account not only the human effector system but features of the experimental apparatus as well. These differences have not been sufficiently reflected in Plamondon & Alimi's target article.

Consistent with the planning-control model, recent fMRI data reveal that the inferior parietal lobe, the frontal lobes, and the basal ganglia are involved in motor planning. Inconsistent with the planning-control model, however, recent behavioral data reveal a spatial repulsion effect, indicating that the visual context surrounding the target can sometimes influence the on-line control of goal-directed action.