Similarities between digits' movements in grasping, touching and pushing

Time-independent relationship between digits closure velocity and hand transport acceleration during reach-to-grasp movements

Prehension movements in primates have been extensively studied for decades, and hand transport and hand grip adjustment are usually considered as the main components of any object reach-to-grasp action. Evident temporal patterns were found for the velocity of the hand during the transport phase and for the digits kinematics during pre-shaping and enclosing phases. However, such kinematics were always analysed separately in regard to time, and never studied in terms of dependence one from another. Nevertheless, if a reliable one-to-one relationship is proven, it would allow reconstructing the digit velocity (and position) simply by knowing the hand acceleration during reaching motions towards the target object, ceasing the usual dependence seen in literature from time of movement and distance from the target. In this study, the aim was precisely to analyse reach-to-grasp motions to explore if such relationship exists and how it can be formulated. Offline and real-time results not only seem to suggest the existence of a time-independent, one-to-one relationship between hand transport and hand grip adjustment, but also that such relationship is quite resilient to the different intrinsic and extrinsic properties of the target objects such as size, shape and position.

Evidence for an internal model of friction when controlling kinetic energy at impact to slide an object along a surface toward a target

Although the role of an internal model of gravity for the predictive control of the upper limbs is quite well established, evidence is lacking regarding an internal model of friction. In this study, 33 male and female human participants performed a striking movement (with the index finger) to slide a plastic cube-like object to a given target distance. The surface material (aluminum or balsa wood) on which the object slides, the surface slope (-10°, 0, or +10°) and the target distance (25 cm or 50 cm) varied across conditions, with ten successive trials in each condition. Analysis of the object speed at impact and spatial error suggests that: 1) the participants chose to impart a similar speed to the object in the first trial regardless of the surface material to facilitate the estimation of the coefficient of friction; 2) the movement is parameterized across repetitions to reduce spatial error; 3) an internal model of friction can be generalized when the slope changes. Biomechanical analysis showed interindividual variability in the recruitment of the upper limb segments and in the adjustment of finger speed at impact in order to transmit the kinetic energy required to slide the object to the target distance. In short, we provide evidence that the brain builds an internal model of friction that makes it possible to parametrically control a striking movement in order to regulate the amount of kinetic energy required to impart the appropriate initial speed to the object.

Humans use minimum cost movements in a whole-body task

Humans have elegant bodies that allow gymnastics, piano playing, and tool use, but understanding how they do this in detail is difficult because their musculoskeletal systems are extraordinarily complicated. Nonetheless, common movements like walking and reaching can be stereotypical, and a very large number of studies have shown their energetic cost to be a major factor. In contrast, one might think that general movements are very individuated and intractable, but our previous study has shown that in an arbitrary set of whole-body movements used to trace large-scale closed curves, near-identical posture sequences were chosen across different subjects, both in the average trajectories of the body's limbs and in the variance within trajectories. The commonalities in that result motivate explanations for its generality. One explanation could be that humans also choose trajectories that are economical in cost. To test this hypothesis, we situate the tracing data within a forty eight degree of freedom human dynamic model that allows the computation of movement cost. Using the model to compare movement cost data from nominal tracings against various perturbed tracings shows that the latter are more energetically expensive, inferring that the original traces were chosen on the basis of minimum cost.

A review of grasping as the movements of digits in space

It is tempting to describe human reach-to-grasp movements in terms of two, more or less independent visuomotor channels, one relating hand transport to the object’s location and the other relating grip aperture to the object’s size. Our review of experimental work questions this framework for reasons that go beyond noting the dependence between the two channels. Both the lack of effect of size illusions on grip aperture and the finding that the variability in grip aperture does not depend on the object’s size indicate that size information is not used to control grip aperture. An alternative is to describe grip formation as emerging from controlling the movements of the digits in space. Each digit’s trajectory when grasping an object is remarkably similar to its trajectory when moving to tap the same position on its own. The similarity is also evident in the fast responses when the object is displaced. This review develops a new description of the speed-accuracy trade-off for multiple effectors that is applied to grasping. The most direct support for the digit-in-space framework is that prism-induced adaptation of each digit’s tapping movements transfers to that digit’s movements when grasping, leading to changes in grip aperture for adaptation in opposite directions for the two digits. We conclude that although grip aperture and hand transport are convenient variables to describe grasping, treating grasping as movements of the digits in space is a more suitable basis for understanding the neural control of grasping.

Humans Use Similar Posture Sequences in a Whole-Body Tracing Task

Humans have elegant bodies that allow gymnastics, piano playing, and tool use, but understanding how they do this in detail is difficult because their musculoskeletal systems are extremely complicated. Previous studies have shown that common movements such as reaching for a coffee cup, cycling a bicycle, or playing the piano have common patterns across subjects. This paper shows that an arbitrary set of whole-body movements used to trace large closed curves have common patterns both in the trajectory of the body's limbs and in variations within those trajectories. The commonality of the result should spur the search for explanations for its generality. One such principle could be that humans choose trajectories that are economical in energetic cost. Another synergistic possibility is that common movements can be saved in segments that can be combined to facilitate the process of deployment.

How removing visual information affects grasping movements

Our interaction with objects is facilitated by the availability of visual feedback. Here, we investigate how and when visual feedback affects the way we grasp an object. Based on the main views on grasping (reach-and-grasp and double-pointing views), we designed four experiments to test: (1) whether the availability of visual feedback influences the digits independently, and (2) whether the absence of visual feedback affects the initial part of the movement. Our results show that occluding (part of) the hand's movement path influences the movement trajectory from the beginning. Thus, people consider the available feedback when planning their movements. The influence of the visual feedback depends on which digit is occluded, but its effect is not restricted to the occluded digit. Our findings indicate that the control mechanisms are more complex than those suggested by current views on grasping.

Unusual prism adaptation reveals how grasping is controlled

There are three main theories on how human grasping movements are controlled. Two of them state that grip aperture and the movement of the hand are controlled. They differ in whether the wrist or the thumb of the hand is controlled. We have proposed a third theory, which states that grasping is a combination of two goal-directed single-digit movements, each directed at a specific position on the object. In this study, we test predictions based on each of the theories by examining the transfer of prism adaptation during single-digit pointing movements to grasping movements. We show that adaptation acquired during single-digit movements transfers to the hand opening when subsequently grasping objects, leaving the movement of the hand unaffected. Our results provide strong evidence for our theory that grasping with the thumb and index finger is based on a combination of two goal-directed single-digit movements.

Titchener's ⊥ in context 1--delimited, discrete monomotif patterns, line arrangements, and branching patterns

Three experiments tested the effects of the presence of nontarget ⊥s on Titchener's (1901) ⊥-illusion. Experiment 1 used patterns of four separate ⊥s, Experiment 2 used branching patterns in which four ⊥s were stuck together, and Experiment 3 used patterns of four triangles or four beehive forms for which the ⊥ could be seen as a skeleton. Three independent samples of 12 observers each had to haptically indicate the lengths of target lines and verbally judge the relative lengths of the two lines of target ⊥s. The illusion to judge or indicate the ⊥’s undivided line as longer than its divided line survived throughout except for the branching patterns: here, haptic indications did not differ between the two types of lines. Specific features of these patterns and of the ⊥ itself may be responsible for these effects.

Movements of individual digits in bimanual prehension are coupled into a grasping component

The classic understanding of prehension is that of coordinated reaching and grasping. An alternative view is that the grasping in prehension emerges from independently controlled individual digit movements (the double-pointing model). The current study tested this latter model in bimanual prehension: participants had to grasp an object between their two index fingers. Right after the start of the movement, the future end position of one of the digits was perturbed. The perturbations resulted in expected changes in the kinematics of the perturbed digit but also in adjusted kinematics in the unperturbed digit. The latter effects showed up when the end position of the right index finger was perturbed, but not when the end position of the left index finger was perturbed. Because the absence of a coupling between the digits is the core assumption of the double-pointing model, finding any perturbation effects challenges this account of prehension; the double-pointing model predicts that the unperturbed digit would be unaffected by the perturbation. The authors conclude that the movement of the digits in prehension is coupled into a grasping component.

Grasping kinematics from the perspective of the individual digits: a modelling study

Grasping is a prototype of human motor coordination. Nevertheless, it is not known what determines the typical movement patterns of grasping. One way to approach this issue is by building models. We developed a model based on the movements of the individual digits. In our model the following objectives were taken into account for each digit: move smoothly to the preselected goal position on the object without hitting other surfaces, arrive at about the same time as the other digit and never move too far from the other digit. These objectives were implemented by regarding the tips of the digits as point masses with a spring between them, each attracted to its goal position and repelled from objects' surfaces. Their movements were damped. Using a single set of parameters, our model can reproduce a wider variety of experimental findings than any previous model of grasping. Apart from reproducing known effects (even the angles under which digits approach trapezoidal objects' surfaces, which no other model can explain), our model predicted that the increase in maximum grip aperture with object size should be greater for blocks than for cylinders. A survey of the literature shows that this is indeed how humans behave. The model can also adequately predict how single digit pointing movements are made. This supports the idea that grasping kinematics follow from the movements of the individual digits.

Grasping and hitting moving objects

Some experimental evidence suggests that grasping should be regarded as independent control of the thumb and the index finger (digit control hypothesis). To investigate this further, we compared how the tips of the thumb and the index finger moved in space when grasping spheres to how they moved when they were hitting the sphere using only one digit. In order to make the tasks comparable, we designed the experiment in such a way that subjects contacted the spheres in about the same way in the hitting task as when grasping it. According to the digit control hypothesis, the two tasks should yield similar digit trajectories in space. People hit and grasped stationary and moving spheres. We compared the similarity of the digits’ trajectories across the two tasks by evaluating the time courses of the paths of the average of the thumb and the index finger. These paths were more similar across tasks than across sphere motion, supporting the notion that grasping is not controlled fundamentally differently than hitting.