How dependent are grip force and arm actions during holding an object?

Expectation of volitional arm movement has prolonged effects on the grip force exerted on a pinched object

Humans closely coordinate the grip force exerted on a hand-held object with changes in the load arising from the object's dynamics. Recent work suggests the grip force is responsive to the predictability of the load forces as well. The well-known grip-force-load-force coupling is intermittent when the load arising from volitional movements fluctuates predictably, whereas grip force increases when loads are unpredictable. Here, we studied the influence of expected but uncertain volitional movements on the digit forces during a static grasp. Young, healthy participants used a pinch grasp to hold an instrumented object and track visual targets by moving the object. We quantified the mean grip force, the temporal decline in grip force (slacking), and the coupling between the pressing digit forces that yield the grip force during static prehension with no expectation of movement, and during the static phase of a choice reaction time task, when the participant expected to move the object after a variable duration. Simply expecting to move the object led to sustained (for at least 5 s) higher magnitude and lower slacking in the grip force, and weaker coupling between the pressing digit forces. These effects were modulated by the direction of the expected movement and the object's mass. The changes helped to maintain the safety margin for the current grasp and likely facilitated the transition from static to dynamic object manipulation. Influence of expected actions on the current grasp may have implications for manual dexterity and its well-known loss with age.

Fine adaptive precision grip control without maximum pinch strength changes after upper limb neurodynamic mobilization

Before and immediately after passive upper limb neurodynamic mobilizations targeting the median nerve, grip (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF) and load (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF) forces applied by the thumb, index and major fingers (three-jaw chuck pinch) were collected using a manipulandum during three different grip precision tasks: grip-lift-hold-replace (GLHR), vertical oscillations (OSC), and vertical oscillations with up and down collisions (OSC/COLL/u, OSC/COLL/d). Several parameters were collected or computed from \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF. Maximum pinch strength and fingertips pressure sensation threshold were also examined. After the mobilizations, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF max changes from 3.2 ± 0.4 to 3.4 ± 0.4 N (p = 0.014), d\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF from 89.0 ± 66.6 to 102.2 ± 59.6 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N~\text{s}^{-1}$$\end{document}Ns-1 (p = 0.009), and d\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 43.6 ± 17.0 to 56.0 ± 17.9 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N~\text{s}^{-1}$$\end{document}Ns-1 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<$$\end{document}p<0.001) during GLHR. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF SD changes from 0.9 ± 0.3 to 1.0 ± 0.2 N (p = 0.004) during OSC. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF peak changes from 17.4 ± 8.3 to 15.1 ± 7.5 N (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<$$\end{document}p<0.001), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF from 12.4 ± 6.7 to 11.3 ± 6.8 N (p = 0.033), and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 2.9 ± 0.4 to 3.00 ± 0.4 N (p = 0.018) during OSC/COLL/u. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF peak changes from 13.5 ± 7.4 to 12.3 ± 7.7 N (p = 0.030) and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 14.5 ± 6.0 to 13.6 ± 5.5 N (p = 0.018) during OSC/COLL/d. Sensation thresholds at index and thumb were reduced (p = 0.001, p = 0.008). Precision grip adaptations observed after the mobilizations could be partly explained by changes in cutaneous median-nerve pressure afferents from the thumb and index fingertips.

Distinct adaptation patterns between grip dynamics and arm kinematics when the body is upside-down

In humans, practically all movements are learnt and performed in a constant gravitational field. Yet, studies on arm movements and object manipulation in parabolic flight have highlighted very fast sensorimotor adaptations to altered gravity environments. Here, we wondered if the motor adjustments observed in those altered gravity environments could also be observed on Earth in a situation where the body is upside-down. To address this question, we asked participants to perform rhythmic arm movements in two different body postures (right-side-up and upside-down) while holding an object in precision grip. Analyses of grip-load force coordination and of movement kinematics revealed distinct adaptation patterns between grip and arm control. Grip force and load force were tightly synchronized from the first movements performed in upside-down posture, reflecting a malleable allocentric grip control. In contrast, velocity profiles showed a more progressive adaptation to the upside-down posture and reflected an egocentric planning of arm kinematics. In addition to suggesting distinct mechanisms between grip dynamics and arm kinematics for adaptation to novel contexts, these results also suggest the existence of general mechanisms underlying gravity-dependent motor adaptation that can be used for fast sensorimotor coordination across different postures on Earth and, incidentally, across different gravitational conditions in parabolic flights, in human centrifuges, or in Space.NEW & NOTEWORTHY During rhythmic arm movements performed in an upside-down posture, grip control adapted very quickly, but kinematics adaptation was more progressive. Our results suggest that grip control and movement kinematics planning might operate in different reference frames. Moreover, by comparing our results with previous results from parabolic flight studies, we propose that a common mechanism underlies adaptation to unfamiliar body postures and adaptation to altered gravity.

Visual Feedback of Object Motion Direction Influences the Timing of Grip Force Modulation During Object Manipulation

During manipulation, object slipping is prevented by modulating the grip force (GF) in synchrony with motion-related inertial forces, i.e., load force (LF). However, due to conduction delays of the sensory system, GF must be modulated in advance based on predictions of LF changes. It has been proposed that such predictive force control relies on internal representations, i.e., internal models, of the relation between the dynamic of the environment and movement kinematics. Somatosensory and visual feedback plays a primary role in building these internal representations. For instance, it has been shown that manipulation-dependent somatosensory signals contribute to building internal representations of gravity in normal and altered gravitational contexts. Furthermore, delaying the timing of visual feedback of object displacement has been shown to affect GF. Here, we explored whether and the extent to which spatial features of visual feedback movement, such as motion direction, may contribute to GF control. If this were the case, a spatial mismatch between actual (somatosensory) and visual feedback of object motion would elicit changes in GF modulation. We tested this hypothesis by asking participants to generate vertical object movements while visual feedback of object position was congruent (0° rotation) or incongruent (180° or 90°) with the actual object displacement. The role of vision on GF control was quantified by the temporal shift of GF modulation as a function of visual feedback orientation and actual object motion direction. GF control was affected by visual feedback when this was incongruent in the vertical (180°), but not horizontal dimension. Importantly, 180° visual feedback rotation delayed and anticipated GF modulation during upward and downward actual movements, respectively. Our findings suggest that during manipulation, spatial features of visual feedback motion are used to predict upcoming LF changes. Furthermore, the present study provides evidence that an internal model of gravity contributes to GF control by influencing sensory reweighting processes during object manipulation.

The coordination between digit forces is altered by anticipated changes in prehensile movement patterns

Stability is the ability of a system to maintain a desired static or dynamic motor pattern. Maneuverability, on the other hand, is the ability to transition between motor patterns, and it is antagonistic to stability. Animals frequently reduce the stability of an ongoing task to facilitate anticipated movement transitions. Such stability-maneuverability tradeoffs are observed in human locomotion. However, the notion applies to other behaviors and this paper reports the first study on the stability-maneuverability tradeoff in human prehension. We tested if the coordination between the digit forces during the manipulation of a hand-held object is altered in response to an expected change in the manipulation pattern. We focused on the coupling between the grip and the load force and between the opposing forces exerted by the thumb and the four fingers, and on the transition from rhythmic vertical oscillation to non-vertical oscillation of the object. The nature of these couplings depends on the oscillation direction. Therefore, the stability-maneuverability tradeoff predicts that an expected volitional change to the object's movement will diminish the strength of these couplings so that the force patterns generating the current movement can efficiently transition into new ones that generate the new movement. The strength of the grip-load coupling did not alter in tasks that required a change in movement compared to tasks that did not. We speculate that participants preferred safety over maneuverability and maintained the grip-load coupling strength to counter high inertial loads and avoid object slip. In contrast, the strength of the coupling between the thumb and the four fingers' opposing forces reduced in tasks that required a change in movement compared to tasks that did not. Thus, the stability-reduction aspect of the stability-maneuverability tradeoff occurs in prehensile behavior. Future work should focus on associating the reduction in stability with gains in maneuverability, and on developing a comprehensive account of this tradeoff in prehensile tasks.

Better grip force control by attending to the controlled object: Evidence for direct force estimation from visual motion

Estimating forces acting between our hand and objects is essential for dexterous motor control. An earlier study suggested that vision contributes to the estimation by demonstrating changes in grip force pattern caused by delayed visual feedback. However, two possible vision-based force estimation processes, one based on hand position and another based on object motion, were both able to explain the effect. Here, to test each process, we examined how visual feedback of hand and object each contribute to grip force control during moving an object (mass) connected to the grip by a damped-spring. Although force applied to the hand could be estimated from its displacement, we did not find any improvements by the hand feedback. In contrast, we found that visual feedback of object motion significantly improved the synchrony between grip and load forces. Furthermore, when both feedback sources were provided, the improvement was observed only when participants were instructed to direct their attention to the object. Our results suggest that visual feedback of object motion contributes to estimation of dynamic forces involved in our actions by means of inverse dynamics computation, i.e., the estimation of force from motion, and that visual attention directed towards the object facilitates this effect.

What you feel is what you see: inverse dynamics estimation underlies the resistive sensation of a delayed cursor

How our central nervous system (CNS) learns and exploits relationships between force and motion is a fundamental issue in computational neuroscience. While several lines of evidence have suggested that the CNS predicts motion states and signals from motor commands for control and perception (forward dynamics), it remains controversial whether it also performs the 'inverse' computation, i.e. the estimation of force from motion (inverse dynamics). Here, we show that the resistive sensation we experience while moving a delayed cursor, perceived purely from the change in visual motion, provides evidence of the inverse computation. To clearly specify the computational process underlying the sensation, we systematically varied the visual feedback and examined its effect on the strength of the sensation. In contrast to the prevailing theory that sensory prediction errors modulate our perception, the sensation did not correlate with errors in cursor motion due to the delay. Instead, it correlated with the amount of exposure to the forward acceleration of the cursor. This indicates that the delayed cursor is interpreted as a mechanical load, and the sensation represents its visually implied reaction force. Namely, the CNS automatically computes inverse dynamics, using visually detected motions, to monitor the dynamic forces involved in our actions.

Superposition of automatic and voluntary aspects of grip force control in humans during object manipulation

When moving grasped objects, people automatically modulate grip force (GF) with movement-dependent load force (LF) in order to prevent object slip. However, GF can also be modulated voluntarily as when squeezing an object. Here we investigated possible interactions between automatic and voluntary GF control. Participants were asked to generate horizontal cyclic movements (between 0.6 and 2.0 Hz) of a hand-held object that was restrained by an elastic band such that the load force (LF) reached a peak once per movement cycle, and to simultaneously squeeze the object at each movement reversal (i.e., twice per cycle). Participants also performed two control tasks in which they either only moved (between 0.6 and 2.0 Hz) or squeezed (between 1.2 and 4.0 Hz) the object. The extent to which GF modulation in the simultaneous task could be predicted from the two control tasks was assessed using power spectral analyses. At all frequencies, the GF power spectra from the simultaneous task exhibited two prominent components that occurred at the cycle frequency (ƒ) and at twice this frequency (2ƒ), whereas the spectra from the movement and squeeze control task exhibited only single peaks at ƒ and 2ƒ, respectively. At lower frequencies, the magnitudes of both frequency components in the simultaneous task were similar to the magnitudes of the corresponding components in the control tasks. However, as frequency increased, the magnitudes of both components in the simultaneous task were greater than the magnitudes of the corresponding control task components. Moreover, the phase relationship between the ƒ components of GF and LF began to drift from the value observed in the movement control task. Overall these results suggest that, at lower movement frequencies, voluntary and automatic GF control processes operate at different hierarchical levels. Several mechanisms are discussed to account for interaction effects observed at higher movement frequencies.

Force coordination in static manipulation: discerning the contribution of muscle synergies and cutaneous afferents

Both an elaborate coordination of the hand grip force (G; normal component of force acting at the digits-object contact area) and load force (L; tangential component), and the role of cutaneous afferents in G-L coordination have been well documented in a variety of manipulation tasks. However, our recent studies revealed that G-L coordination deteriorates when L consecutively changes direction (bidirectional tasks; e.g., when vigorously shaking objects or using tools). The aim of the study was to distinguish between the possible role of the synergy of hand grip and arm muscles (exerting G and L, respectively) and the role of cutaneous afferent input in the observed phenomenon. Subjects (N=14) exerted sinusoidal L pattern in vertical direction against an externally fixed device in trials that gradually changed from uni- to fully bidirectional. In addition, a manipulation of an external arm support decoupled L measured by the device (and, therefore, recorded by the cutaneous receptors) from the action of arm muscles exerting L. The results revealed that switching from uni- to bidirectional tasks, no matter how low and brief L exertion was in the opposite direction, was associated with an abrupt decrease in G-L coordination. This coordination remained unaffected by the manipulation of external support. The first result corroborates our previous conclusion that the force coordination in uni- and bidirectional manipulation tasks could be based on partly different neural control mechanisms. However, the second finding suggests that the studied control mechanisms could depend more on the cutaneous afferent input, rather than on the synergy of the muscles exerting G and L.

Aging affects the predictive control of grip force during object manipulation

We examined the effects of aging on the predictive control of grip force during object manipulation under various external force fields. Participants rhythmically moved a hand-held object (m = 0.4 kg) in the horizontal plane under three experimental conditions: (1) with an elastic cord attached to the upper arm (ARM), (2) with the elastic cord attached to the object (OBJECT), and (3) without any elastic cord (NO ELAST). Performance was evaluated in terms of both metric and spectral characteristics of the grip force (GF) profile, in relation to the movement-induced variations in load at the object-finger interface (LFO). The performance of a group of 12 older adults (mean age = 66.3 years) was compared to the performance of a group of 12 young adults (mean age = 25.0 years), whose metric characteristics were reported earlier (Exp. Brain Res. 172:331, 2006). Although elderly participants exerted a larger mean GF, a tight linear coupling between GF and LFO was found for both groups in OBJECT. In ARM and NO ELAST, coefficients of cross-correlations were markedly lower, the more so for the elderly participants. Adjustments in GF occurred slightly in advance of variations in LFO in young adults (+7 ms) and somewhat delayed in the elderly (-26 ms). Spectral analyses revealed that in OBJECT, LFO and GF varied primarily at the frequency of movement. In ARM and NO ELAST, where LFO varied at twice this frequency, GF modulations contained a substantial frequency component at the frequency of movement, with this effect being more pronounced for the elderly participants. We conclude that both young and older adults demonstrate a predictive control of GF, capable of separating external force fields acting on the arm or on object-finger interface. However, in the presence of variations in LFO occurring at twice the frequency of movement, the spectral profile of GF exhibits a non-functional component of variation at the frequency of movement. Aging amplifies this latter effect, thereby affecting the efficiency of the predictive control of grip force.

The contribution of non-digital afferent signals to grip force adjustments evoked by brisk unloading of the arm or the held object

OBJECTIVE

Earlier studies suggest that grip force adjustments evoked by mechanical perturbations result more from cutaneous signals from the fingertips, than from afferent signals from the supporting limb. Generally an increase in tangential load at the fingertips induces an increase in grip force, whereas a decrease in load induces the opposite reaction. Some data suggest that prior knowledge and experience influences the magnitude of grip force adjustments.

METHODS

This study examines the relative contribution of digital and arm afferent signals in the context of brisk involuntary upward flexions obtained either by unloading the arm (ARM) or the held object (OBJECT). Following the perturbation, the tangential load at the fingertips increased in ARM, but decreased in OBJECT. A subsidiary goal was to compare the performance of naive subjects with the performance of trained and informed subjects.

RESULTS

When the perturbation was completely unexpected, grip force increased sharply after OBJECT and ARM unloading. By contrast, when subjects had prior knowledge and experience with the upcoming perturbation, grip responses were clearly differentiated; grip force increased after ARM, but decreased after OBJECT.

CONCLUSIONS

These results challenge the view that cutaneous signals of the fingertips are the driving signals of grip force responses. Instead, afferent signals from the flexed arm would account well for the lack of difference between grip force responses in ARM and OBJECT under unpredictable conditions. These data provide clear evidence that prior knowledge and experience influences reactive grip force control, since subjects became able to repress unnecessary grip force modulation in OBJECT.

SIGNIFICANCE

These data have implications for understanding the initiation and the modulation of grip force adjustments.

Similar motion of a hand-held object may trigger nonsimilar grip force adjustments

The tight coupling between load (L) and grip (G) forces during voluntary manipulation of a hand-held object is well established. The current study is to examine grip-load force coupling when motion of the hand with an object was either self-generated (voluntary) or externally generated. Subjects performed similar cyclic movements of different loads at various frequencies with three types of manipulations: 1) voluntary oscillation, 2) oscillating the right arm via the pulley system by the left leg (self-driven oscillation), and 3) oscillating the arm via the pulley system by another person (other-driven oscillation). During the self-generated movements: 1) the grip forces were larger and 2) grip-load force modulation was more pronounced than in the externally generated movements. The G-L adjustments are not completely determined by the mechanics of object motion; nonmechanical factors related to movement performance, for instance perceptual factors, may affect the G-L coupling.

Control strategies in object manipulation tasks

The remarkable manipulative skill of the human hand is not the result of rapid sensorimotor processes, nor of fast or powerful effector mechanisms. Rather, the secret lies in the way manual tasks are organized and controlled by the nervous system. At the heart of this organization is prediction. Successful manipulation requires the ability both to predict the motor commands required to grasp, lift, and move objects and to predict the sensory events that arise as a consequence of these commands.

Predictive control of grip force when moving object with an elastic load applied on the arm

Skilled object manipulation relies on the capability to adjust the grip force according to the consequences of our movements in terms of the resulting load force of the object. Such predictive grip force control requires (at least) two neural processes: (1) predicting the kinematic characteristics of the unfolding arm trajectory and (2) predicting the load force on the object resulting, among other factors, from the arm movement. The goal of this study was to examine whether subjects can still anticipate the resulting load force on the object when the moving arm is submitted to a type of load that does not contribute to the object load. To this end, 12 subjects were asked to rhythmically move a 0.4 kg object under three different conditions. In the first condition (ARM), an elastic cord was attached to the upper arm. In the second condition, the elastic cord was attached to the object (OBJECT). In the third condition, the elastic cord was absent (NO ELAST). At the kinematic level, results showed no influence of the elastic cord on the pattern of movement of the object. At the kinetic level, cross-correlation analyses between grip force and load force acting on the object revealed significant correlations with minimal delays. In addition, grip force profiles were similar under the ARM and NO ELAST conditions, both differing from the OBJECT condition. Overall, we interpret these results as evidence that the neural processes involved in the prediction of the arm trajectory and those involved in the prediction of the load on the object held can take into account different external force fields, thereby preserving the functionality of the behaviour.