Finger inter-dependence: linking the kinetic and kinematic variables

Age-related differences in finger interdependence during complex hand movements

The well-known decrease in finger dexterity during healthy aging leads to a significant reduction in quality of life. Still, the exact patterns of altered finger kinematics of older adults in daily life are fairly unexplored. Finger interdependence is the unintentional comovement of fingers that are not intended to move, and it is known to vary across the lifespan. Nevertheless, the magnitude and direction of age-related differences in finger interdependence are ambiguous across studies and tasks and have not been explored in the context of daily life finger movements. We investigated five different free and daily-life-inspired finger movements of the right, dominant hand as well as a sequential finger tapping task of the thumb against the other fingers, in 17 younger (22-37 yr) and 17 older (62-80 yr) adults using an exoskeleton data glove for data recording. Using inferential statistics, we found that the unintentional comovement of fingers generally decreases with age in all performed daily-life-inspired movements. Finger tapping, however, showed a trend towards higher finger interdependence for older compared with younger adults. Using machine learning, we predicted the age group of a person from finger interdependence features of single movement trials significantly better than chance level for the daily-life-inspired movements, but not for finger tapping. Taken together, we show that for specific tasks, decreased finger interdependence (i.e., less comovement) could potentially act as a marker of human aging that specifically characterizes older adults' complex finger movements in daily life.NEW & NOTEWORTHY Kinematic finger movement data were analyzed with regard to age-related differences. Extensive analyses of complex and daily-life-inspired movements reveal that the direction of age effects is not uniform but task-dependent: Although older adults generally show more finger interdependence than younger adults in a simple finger tapping task, this effect is reversed for daily-life-inspired movement tasks. For these tasks, finger interdependence indices offer potential new markers to predict the age group of an individual using machine learning approaches.

Exploring Kinetic and Kinematic Finger Individuation Capability in Children With Hemiplegic Cerebral Palsy

While fine manual dexterity develops over time, the extent to which children show independent control of their digits in each hand and the impact of perinatal brain injury on this individuation have not been well quantified. Our goal in this study was to assess and compare finger force and movement individuation in 8-14 year old children with hemiplegic cerebral palsy (hCP; n = 4) and their typically developing peers (TD; n = 10). We evaluated finger force individuation with five independent load cells and captured joint movement individuation with video tracking. We observed no significant differences in individuation indices between the dominant and non-dominant hands of TD children, but individuated force and movement were substantially reduced in the paretic versus non paretic hands of children with hCP (p < 0.001). In TD participants, the thumb tended to have the greatest level of independent control. This small sample of children with hCP showed substantial loss of individuation in the paretic hand and some deficits in the non-paretic hand, suggesting possible benefit from targeted training of digit independence in both hands for children with CP.

Interfinger Synchronization Capability of Paired Fingers in Discrete Fine-Force Control Tasks

This study examined whether within-a-hand and between-hands finger pairings would exhibit different interfinger synchronization capabilities in discrete fine-force control tasks. Participants were required to perform the designed force control tasks using finger pairings of index and middle fingers on one or two hands. Results demonstrated that the delayed reaction time and the timing difference of paired fingers showed a significant difference among finger pairings. In particular, paired fingers exhibited less delayed reaction time and timing difference in between-hands finger pairings than in within-a-hand finger pairings. Such bimanual advantage of the pairings with two symmetric fingers was evident only in the task types with relatively high amplitudes. However, for a given finger pairing, the asymmetric amplitude configuration, assigning a relatively higher amplitude to either left or right finger of paired fingers, has no significant effect on the interfinger synchronization. Therefore, paired fingers on both hands showed a bimanual advantage in the relatively high force, especially for the pairing of symmetrical fingers, whereas asymmetric amplitude configuration for a finger pairing was able to suppress the bimanual advantage. These findings would enrich the understanding of the interfinger synchronization capability of paired fingers and be referential for interactive engineering applications when leveraging the interfinger synchronization capability in discrete fine-force control tasks.

Dynamical Synergies of Multidigit Hand Prehension

Hand prehension requires highly coordinated control of contact forces. The high-dimensional sensorimotor system of the human hand operates at ease, but poses several challenges when replicated in artificial hands. This paper investigates how the dynamical synergies, coordinated spatiotemporal patterns of contact forces, contribute to the hand grasp, and whether they could potentially capture the force primitives in a low-dimensional space. Ten right-handed subjects were recruited to grasp and hold mass-varied objects. The contact forces during this multidigit prehension were recorded using an instrumented grip glove. The dynamical synergies were derived using principal component analysis (PCA). The contact force patterns during the grasps were reconstructed using the first few synergies. The significance of the dynamical synergies, the influence of load forces and task configurations on the synergies were explained. This study also discussed the contribution of biomechanical constraints on the first few synergies and the current challenges and possible applications of the dynamical synergies in the design and control of exoskeletons. The integration of the dynamical synergies into exoskeletons will be realized in the near future.

The Nature of Finger Enslaving: New Results and Their Implications

We present a review on the phenomenon of unintentional finger action seen when other fingers of the hand act intentionally. This phenomenon (enslaving) has been viewed as a consequence of both peripheral (e.g., connective tissue links and multifinger muscles) and neural (e.g., projections of corticospinal pathways) factors. Recent studies have shown relatively large and fast drifts in enslaving toward higher magnitudes, which are not perceived by subjects. These and other results emphasize the defining role of neural factors in enslaving. We analyze enslaving within the framework of the theory of motor control with spatial referent coordinates. This analysis suggests that unintentional finger force changes result from drifts of referent coordinates, possibly reflecting the spread of cortical excitation.

Synergies at the level of motor units in single-finger and multi-finger tasks

We explored the organization of motor units recorded in the flexor digitorum superficialis into stable groups (MU-modes) and force-stabilizing synergies in spaces of MU-modes. Young, healthy participants performed one-finger and three-finger accurate cyclical force production tasks. Two wireless sensor arrays (Trigno Galileo, Delsys, Inc.) were placed over the proximal and distal portions of the muscle for surface recording and identification of motor unit action potentials. Principal component analysis with Varimax rotation and factor extraction was used to identify MU-modes. The framework of the uncontrolled manifold hypothesis was used to analyze inter-cycle variance in the space of MU-modes and compute the index of force-stabilizing synergy. Multiple linear regression between the first MU-mode in the three-finger task and the first MU-modes in the three single-finger tasks showed no differences between the data recorded by the two electrodes suggesting that MU-modes were unlikely to be synonymous with muscle compartments. Multi-MU-mode synergies stabilizing task force were documented across all tasks. In contrast, there were no force-stabilizing synergies in the three-finger task analyzed in the space of individual finger forces. Our results confirm the synergic organization of motor units in single-finger tasks and, for the first time, expand this result to multi-finger tasks. We offer an interpretation of the findings within the theoretical scheme of control with spatial referent coordinates expanded to the analysis of individual motor units. The results confirm trade-offs between synergies at different hierarchical levels and expand this notion to intra-muscle synergies.

Perturbation-induced fast drifts in finger enslaving

We explored changes in finger forces and in an index of unintentional finger force production (enslaving) under a variety of visual feedback conditions and positional finger perturbations. In particular, we tested a hypothesis that enslaving would show a consistent increase with time at characteristic times of about 1-2 s. Young healthy subjects performed accurate force production tasks under visual feedback on the total force of the instructed fingers (index and ring) or enslaved fingers (middle and little). Finger feedback was covertly alternated between master and enslaved fingers in a random fashion. The feedback could be presented over the first 5 s of the trial only or over the whole trial duration (21 s). After 5 s, the fingers were lifted by 1 cm, and after 15 s, the fingers were lowered to the initial position. The force of the instructed fingers drifted toward lower magnitudes in all conditions except the one with continuous feedback on that force. The force of enslaved fingers showed variable behavior across conditions. In all conditions, the index of enslaving showed a consistent increase with the time constant varying between 1 and 3 s. We interpret the results as pointing at the spread of excitation to enslaved fingers (possibly, in the cortical M1 areas). The relatively fast changes in enslaving under positional finger perturbations suggest that quick changes of the input into M1 from pre-M1 areas can accelerate the hypothesized spread of cortical excitation.

On the origin of finger enslaving: control with referent coordinates and effects of visual feedback

When a person tries to press with a finger, other fingers of the hand produce force unintentionally. We explored this phenomenon of enslaving during unintentional force drifts in the course of continuous force production by pairs of fingers of a hand. Healthy subjects performed accurate force production tasks by finger pairs Index-Middle, Middle-Ring, and Ring-Little with continuous visual feedback on the combined force of the instructed (master) fingers or of the noninstructed (enslaved) fingers. The feedback scale was adjusted to ensure that the subjects did not know the difference between these two, randomly presented, conditions. Across all finger pairs, enslaved force showed a drift upward under feedback on the master finger force, and master force showed a drift downward under feedback on the enslaved finger force. The subjects were unaware of the force drifts, which could reach over 50% of the initial force magnitude over 15 s. Across all conditions, the index of enslaving increased by ∼50% over the trial duration. The initial moment of force magnitude in pronation-supination was not a consistent predictor of the force drift magnitude. These results falsify the hypothesis that the counter-directional force drifts reflected drifts in the moment of force. They suggest that during continuous force production, enslaving increases with time, possibly due to the spread of excitation over cortical finger representations or other mechanisms, such as increased synchronization of firing of α-motoneurons innervating different compartments of extrinsic flexors. These changes in enslaving, interpreted at the level of control with referent coordinates for the fingers, can contribute to a variety of phenomena, including unintentional force drifts.NEW & NOTEWORTHY We report a consistent slow increase in finger enslaving (force production by noninstructed fingers) when visual feedback was presented on the force produced by either two instructed fingers or two noninstructed fingers of the hand. In contrast, force drifts could be in opposite directions depending on the visual feedback. We interpret enslaving and its drifts at the level of control with referent coordinates for the involved muscles, possibly reflecting spread of cortical excitation.

On Primitives in Motor Control

The concept of primitives has been used in motor control both as a theoretical construct and as a means of describing the results of experimental studies involving multiple moving elements. This concept is close to Bernstein’s notion of engrams and level of synergies. Performance primitives have been explored in spaces of peripheral variables but interpreted in terms of neural control primitives. Performance primitives reflect a variety of mechanisms ranging from body mechanics to spinal mechanisms and to supraspinal circuitry. This review suggests that primitives originate at the task level as preferred time functions of spatial referent coordinates or at mappings from higher level referent coordinates to lower level, frequently abundant, referent coordinate sets. Different patterns of performance primitives can emerge depending, in particular, on the external force field.

Single finger movements in the aging hand: changes in finger independence, muscle activation patterns and tendon displacement in older adults

With aging, hand mobility and manual dexterity decline, even under healthy circumstances. To assess how aging affects finger movement control, we compared elderly and young subjects with respect to (1) finger movement independence, (2) neural control of extrinsic finger muscles and (3) finger tendon displacements during single finger flexion. In twelve healthy older (age 68-84) and nine young (age 22-29) subjects, finger kinematics were measured to assess finger movement enslaving and the range of independent finger movement. Muscle activation was assessed using a multi-channel electrode grid placed over the flexor digitorum superficialis (FDS) and the extensor digitorum (ED). FDS tendon displacements of the index, middle and ring fingers were measured using ultrasound. In older subjects compared to the younger subjects, we found: (1) increased enslaving of the middle finger during index finger flexion (young: 25.6 ± 12.4%, elderly: 47.0 ± 25.1%; p = 0.018), (2) a lower range of independent movement of the index finger (young_middle = 74.0%, elderly_middle: 45.9%; p < 0.001), (3) a more evenly distributed muscle activation pattern over the finger-specific FDS and ED muscle regions and (4) a lower slope at the beginning of the finger movement to tendon displacement relationship, presenting a distinct period with little to no tendon displacement. Our study indicates that primarily the movement independence of the index finger is affected by aging. This can partly be attributed to a muscle activation pattern that is more evenly distributed over the finger-specific FDS and ED muscle regions in the elderly.

Increased enslaving in elderly is associated with changes in neural control of the extrinsic finger muscles

Aging has consequences for hand motor control, among others affecting finger force enslaving during static pressing tasks. The aim of this study was to assess whether the extent of finger force enslaving changes with aging during a task that involves both static and dynamic phases. Ten right-handed young (22-30 years) and ten elderly subjects (67-79 years) were instructed to first exert a constant force (static phase) and then flex their index finger while counteracting constant resistance forces orthogonal to their fingertips (dynamic phase). The other fingers (non-instructed) were held in extension. EMG activities of the flexor digitorum superficialis (FDS) and extensor digitorum (ED) muscles in the regions corresponding to the index, middle and ring fingers together with their forces and position of index finger were measured. In both elderly and young, forces exerted by the non-instructed fingers increased (around 0.6 N for both young and elderly) during isotonic flexion of the index finger, but with a different delay of on average 100 ± 72 ms in elderly and 334 ± 101 ms in young subjects. Results also suggest different responses in activity of FDS and ED muscle regions of the non-instructed fingers to index finger flexion between elderly and young subjects. The enslaving effect was significantly higher in elderly than in young subjects both in the static (12% more) and dynamic (14% more) phases. These differences in enslaving can at least partly be explained by changes in neuromuscular control.

Timing and extent of finger force enslaving during a dynamic force task cannot be explained by EMG activity patterns

Finger enslaving is defined as the inability of the fingers to move or to produce force independently. Such finger enslaving has predominantly been investigated for isometric force tasks. The aim of this study was to assess whether the extent of force enslaving is dependent on relative finger movements. Ten right-handed subjects (22–30 years) flexed the index finger while counteracting constant resistance forces (4, 6 and 8 N) orthogonal to the fingertip. The other, non-instructed fingers were held in extension. EMG activities of the mm. flexor digitorum superficialis (FDS) and extensor digitorum (ED) in the regions corresponding to the index, middle and ring fingers were measured. Forces exerted by the non-instructed fingers increased substantially (by 0.2 to 1.4 N) with flexion of the index finger, increasing the enslaving effect with respect to the static, pre-movement phase. Such changes in force were found 260–370 ms after the initiation of index flexion. The estimated MCP joint angle of the index finger at which forces exerted by the non-instructed fingers started to increase varied between 4° and 6°. In contrast to the finger forces, no significant changes in EMG activity of the FDS regions corresponding to the non-instructed fingers upon index finger flexion were found. This mismatch between forces and EMG of the non-instructed fingers, as well as the delay in force development are in agreement with connective tissue linkages being slack when the positions of the fingers are similar, but pulled taut when one finger moves relative to the others. Although neural factors cannot be excluded, our results suggest that mechanical connections between muscle-tendon structures were (at least partly) responsible for the observed increase in force enslaving during index finger flexion.

Multi-Finger Interaction and Synergies in Finger Flexion and Extension Force Production

The aim of this study was to discover finger interaction indices during single-finger ramp tasks and multi-finger coordination during a steady state force production in two directions, flexion, and extension. Furthermore, the indices of anticipatory adjustment of elemental variables (i.e., finger forces) prior to a quick pulse force production were quantified. It is currently unknown whether the organization and anticipatory modulation of stability properties are affected by force directions and strengths of in multi-finger actions. We expected to observe a smaller finger independency and larger indices of multi-finger coordination during extension than during flexion due to both neural and peripheral differences between the finger flexion and extension actions. We also examined the indices of the anticipatory adjustment between different force direction conditions. The anticipatory adjustment could be a neural process, which may be affected by the properties of the muscles and by the direction of the motions. The maximal voluntary contraction (MVC) force was larger for flexion than for extension, which confirmed the fact that the strength of finger flexor muscles (e.g., flexor digitorum profundus) was larger than that of finger extensor (e.g., extensor digitorum). The analysis within the uncontrolled manifold (UCM) hypothesis was used to quantify the motor synergy of elemental variables by decomposing two sources of variances across repetitive trials, which identifies the variances in the uncontrolled manifold (V_UCM) and that are orthogonal to the UCM (V_ORT). The presence of motor synergy and its strength were quantified by the relative amount of V_UCM and V_ORT. The strength of motor synergies at the steady state was larger in the extension condition, which suggests that the stability property (i.e., multi-finger synergies) may be a direction specific quantity. However, the results for the existence of anticipatory adjustment; however, no difference between the directional conditions suggests that feed-forward synergy adjustment (changes in the stability property) may be at least independent of the magnitude of the task-specific apparent performance variables and its direction (e.g., flexion and extension forces).

Perceptually relevant remapping of human somatotopy in 24 hours

Experience-dependent reorganisation of functional maps in the cerebral cortex is well described in the primary sensory cortices. However, there is relatively little evidence for such cortical reorganisation over the short-term. Using human somatosensory cortex as a model, we investigated the effects of a 24 hr gluing manipulation in which the right index and right middle fingers (digits 2 and 3) were adjoined with surgical glue. Somatotopic representations, assessed with two 7 tesla fMRI protocols, revealed rapid off-target reorganisation in the non-manipulated fingers following gluing, with the representation of the ring finger (digit 4) shifted towards the little finger (digit 5) and away from the middle finger (digit 3). These shifts were also evident in two behavioural tasks conducted in an independent cohort, showing reduced sensitivity for discriminating the temporal order of stimuli to the ring and little fingers, and increased substitution errors across this pair on a speeded reaction time task.

DOI:http://dx.doi.org/10.7554/eLife.17280.001

The areas of the brain that receive inputs from our senses have a map-like structure. In an area called the visual cortex this map represents our field of vision; in the auditory cortex, it represents the range of different tones we can hear. The sense of touch is processed in the somatosensory cortex: an area of the brain that is organised around a map of the body, with adjacent regions of the cortex representing adjacent regions of the body. The clear structure of these brain regions makes them ideal for exploring how the organisation of the brain changes over time.

How quickly can changes to the touch inputs that the brain receives cause the map in the somatosensory cortex to reorganise? Can these effects be produced in just 24 hours? And would this remapping affect how we perceive touch? To investigate these questions, Kolasinski et al. glued together the right index and right middle fingers of healthy human volunteers. This separated the middle and ring fingers: a pair that usually move together due to the anatomical structure of the hand.

Functional magnetic resonance imaging of the brain’s activity revealed that within 24 hours of the gluing, the brain’s representation of the ring finger moved away from that of the middle finger, and towards the representation of the little finger. A perceptual judgment task mirrored this finding: after 24 hours of gluing, the participants became better at distinguishing between the middle and ring fingers and worse at distinguishing between the ring and little fingers. This is a powerful demonstration of the human brain’s potential to adapt and reorganise rapidly to changes to sensory inputs.

The sense of touch declines gradually with age and may also be reduced as a result of disease such as stroke. A long-term challenge is to understand how the sensory regions of the brain change during this loss of sensation. Further research could then investigate how to maintain the structure of the cortical map to prolong or restore high quality touch sensation.

DOI:http://dx.doi.org/10.7554/eLife.17280.002

Variable and Asymmetric Range of Enslaving: Fingers Can Act Independently over Small Range of Flexion

The variability in the numerous tasks in which we use our hands is very large. However, independent movement control of individual fingers is limited. To assess the extent of finger independency during full-range finger flexion including all finger joints, we studied enslaving (movement in non-instructed fingers) and range of independent finger movement through the whole finger flexion trajectory in single and multi-finger movement tasks. Thirteen young healthy subjects performed single- and multi-finger movement tasks under two conditions: active flexion through the full range of movement with all fingers free to move and active flexion while the non-instructed finger(s) were restrained. Finger kinematics were measured using inertial sensors (PowerGlove), to assess enslaving and range of independent finger movement. Although all fingers showed enslaving movement to some extent, highest enslaving was found in adjacent fingers. Enslaving effects in ring and little finger were increased with movement of additional, non-adjacent fingers. The middle finger was the only finger affected by restriction in movement of non-instructed fingers. Each finger showed a range of independent movement before the non-instructed fingers started to move, which was largest for the index finger. The start of enslaving was asymmetrical for adjacent fingers. Little finger enslaving movement was affected by multi-finger movement. We conclude that no finger can move independently through the full range of finger flexion, although some degree of full independence is present for smaller movements. This range of independent movement is asymmetric and variable between fingers and between subjects. The presented results provide insight into the role of finger independency for different types of tasks and populations.

Stability of multifinger action in different state spaces

We investigated stability of action by a multifinger system with three methods: analysis of intertrial variance, application of transient perturbations, and analysis of the system's motion in different state spaces. The "inverse piano" device was used to apply transient (lifting-and-lowering) perturbations to individual fingers during single- and two-finger accurate force production tasks. In each trial, the perturbation was applied either to a finger explicitly involved in the task or one that was not. We hypothesized that, in one-finger tasks, task-specific stability would be observed in the redundant space of finger forces but not in the nonredundant space of finger modes (commands to explicitly involved fingers). In two-finger tasks, we expected that perturbations applied to a nontask finger would not contribute to task-specific stability in mode space. In contrast to our expectations, analyses in both force and mode spaces showed lower stability in directions that did not change total force output compared with directions that did cause changes in total force. In addition, the transient perturbations led to a significant increase in the enslaving index. We consider these results within a theoretical scheme of control with referent body configurations organized hierarchically, using multiple few-to-many mappings organized in a synergic way. The observed volatility of enslaving, greater equifinality of total force compared with elemental variables, and large magnitude of motor equivalent motion in both force and mode spaces provide support for the concept of task-specific stability of performance and the existence of multiple neural loops, which ensure this stability.

Finger enslaving in the dominant and non-dominant hand

During single-finger force production, the non-instructed fingers unintentionally produce force (finger enslaving). In this study, enslaving effects were compared between the dominant and non-dominant hands. The test consisted of a series of maximum voluntary contractions with different finger combinations. Enslaving matrices were calculated by means of training an artificial neural network. The dominant hand was found to be stronger, but there was found to be no difference between the overall enslaving effects in the dominant and non-dominant hands. There was no correlation between the magnitude of finger enslaving and the performance in such tests as the Edinburgh Handedness Inventory, the Grooved Pegboard test, and the Jebsen-Taylor Hand Function test. Each one of those three tests showed a significant difference between the dominant and non-dominant hand performances. Eleven subjects were retested after two months, and it was found that enslaving effects did not fluctuate significantly between the two testing sessions. While the dominant and non-dominant hands are involved differently in everyday tasks, e.g. in writing or eating, this practice does not cause significant differences in enslaving between the hands.

Enslaving in a serial chain: interactions between grip force and hand force in isometric tasks

This study was motivated by the double action of extrinsic hand muscles that produce grip force and also contribute to wrist torque. We explored interactions between grip force and wrist torque in isometric force production tasks. In particular, we tested a hypothesis that an intentional change in one of the two kinetic variables would produce an unintentional change in the other (enslaving). When young healthy subjects produced accurate changes in the grip force, only minor effects on the force produced by the hand (by wrist flexion/extension action) were observed. In contrast, a change in the hand force produced consistent changes in grip force in the same direction. The magnitude of such unintentional grip force change was stronger for intentional hand force decrease as compared to hand force increase. These effects increased with the magnitude of the initial grip force. When the subjects were asked to produce accurate total force computed as the sum of the hand and grip forces, strong negative covariation between the two forces was seen across trials interpreted as a synergy stabilizing the total force. An index of this synergy was higher in the space of "modes," hypothetical signals to the two effectors that could be changed by the controller one at a time. We interpret the complex enslaving effects (positive force covariation) as conditioned by typical everyday tasks. The presence of synergic effects (negative, task-specific force covariation) can be naturally interpreted within the referent configuration hypothesis.

Neural bases of hand synergies

The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is “synergy control” which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of “fixed” vs. “flexible” synergies and mechanisms underlying the combination of synergies for hand control.

The force synergy of human digits in static and dynamic cylindrical grasps

This study explores the force synergy of human digits in both static and dynamic cylindrical grasping conditions. The patterns of digit force distribution, error compensation, and the relationships among digit forces are examined to quantify the synergetic patterns and coordination of multi-finger movements. This study recruited 24 healthy participants to perform cylindrical grasps using a glass simulator under normal grasping and one-finger restricted conditions. Parameters such as the grasping force, patterns of digit force distribution, and the force coefficient of variation are determined. Correlation coefficients and principal component analysis (PCA) are used to estimate the synergy strength under the dynamic grasping condition. Specific distribution patterns of digit forces are identified for various conditions. The compensation of adjacent fingers for the force in the normal direction of an absent finger agrees with the principle of error compensation. For digit forces in anti-gravity directions, the distribution patterns vary significantly by participant. The forces exerted by the thumb are closely related to those exerted by other fingers under all conditions. The index-middle and middle-ring finger pairs demonstrate a significant relationship. The PCA results show that the normal forces of digits are highly coordinated. This study reveals that normal force synergy exists under both static and dynamic cylindrical grasping conditions.

Dynamical degrees of freedom and correlations in isometric finger force production

Prior research has concluded that the correlations of isometric finger forces represent the extent to which the fingers are controlled as a single unit. If this is the case, finger force correlations should be consistent with estimates of the controlled (dynamical) degrees of freedom in finger forces. The present study examined the finger force correlations and the dynamical degrees of freedom in four isometric force tasks. The tasks were to produce a preferred level of force with the (a) Index, (b) Ring, (c) Both fingers and also to (d) Rest the fingers on the load cells. Dynamical degrees of freedom in finger forces were lowest in the Both finger force task and progressively higher in the Ring, Index and Resting finger force tasks. The finger force correlations were highest in the Resting and lowest in the Index and Ring finger tasks. The results for the dynamical degrees of freedom in finger forces were consistent with a reduction in degrees of freedom in response to the degrees of freedom problem and the task constraints. The results for the finger force correlations were inconsistent with a reduction in the dynamical degrees of freedom. These findings indicate that finger force correlations do not necessarily reflect the coupling of finger forces. The findings also highlight the value of time-domain analyses to reveal the organization of control in isometric finger forces.

Age-related changes in the control of finger force vectors

We explored changes in finger interaction in the process of healthy aging as a window into neural control strategies of natural movements. In particular, we quantified the amount of force produced by noninstructed fingers in different directions, the amount of force produced by the instructed finger orthogonally to the task direction, and the strength of multifinger synergies stabilizing the total force magnitude and direction during accurate force production. Healthy elderly participants performed accurate isometric force production tasks in five directions by individual fingers and by all four fingers acting together. Their data were compared with a dataset obtained in a similar earlier study of young subjects. Finger force vectors were measured using six-component force/torque sensors. Multifinger synergies were quantified using the framework of the uncontrolled manifold hypothesis. The elderly participants produced lower force magnitudes by noninstructed fingers and higher force magnitudes by instructed fingers in nontask directions. They showed strong synergies stabilizing the magnitude and direction of the total force vector. However, the synergy indexes were significantly lower than those observed in the earlier study of young subjects. The results are consistent with an earlier hypothesis of preferential weakening of intrinsic hand muscles with age. We interpret the findings as a shift in motor control from synergic to element-based, which may be causally linked to the documented progressive neuronal death at different levels of the neural axis.

Finger interaction in a three-dimensional pressing task

Accurate control of forces produced by the fingers is essential for performing object manipulation. This study examines the indices of finger interaction when accurate time profiles of force are produced in different directions, while using one of the fingers or all four fingers of the hand. We hypothesized that patterns of unintended force production among shear force components may involve features not observed in the earlier studies of vertical force production. In particular, we expected to see unintended forces generated by non-task fingers not in the direction of the instructed force but in the opposite direction as well as substantial force production in directions orthogonal to the instructed direction. We also tested a hypothesis that multi-finger synergies, quantified using the framework of the uncontrolled manifold hypothesis, will help reduce across-trials variance of both total force magnitude and direction. Young, healthy subjects were required to produce accurate ramps of force in five different directions by pressing on force sensors with the fingers of the right (dominant) hand. The index finger induced the smallest unintended forces in non-task fingers. The little finger showed the smallest unintended forces when it was a non-task finger. Task fingers showed substantial force production in directions orthogonal to the intended force direction. During four-finger tasks, individual force vectors typically pointed off the task direction, with these deviations nearly perfectly matched to produce a resultant force in the task direction. Multi-finger synergy indices reflected strong co-variation in the space of finger modes (commands to fingers) that reduced variability of the total force magnitude and direction across trials. The synergy indices increased in magnitude over the first 30% of the trial time and then stayed at a nearly constant level. The synergy index for stabilization of total force magnitude was higher for shear force components when compared to the downward pressing force component. The results suggest complex interactions between enslaving and synergic force adjustments, possibly reflecting the experience with everyday prehensile tasks. For the first time, the data document multi-finger synergies stabilizing both shear force magnitude and force vector direction. These synergies may play a major role in stabilizing the hand action during object manipulation.

Mechanical analysis and hierarchies of multidigit synergies during accurate object rotation

We studied the mechanical variables (the grip force and the total moment of force) and multidigit synergies at two levels (the virtual finger-thumb level, VF-TH, and the individual finger level, IMRL) of a hypothetical control hierarchy during accurate rotation of a hand-held instrumented handle. Synergies were defined as covaried changes in elemental variables (forces and moments of force) that stabilize the output at a particular level. Indices of multidigit synergies showed higher values at the hierarchically higher level (VF-TH) for both normal and tangential forces. The moment of force was stabilized at both hierarchical levels during the steady-state phases but not during the movement. The results support the principles of superposition and of mechanical advantage. They also support an earlier hypothesis on an inherent tradeoff between synergies at the two hierarchical levels, although the controller showed more subtle and versatile synergic control than the one hypothesized earlier.

A tactile stimulator for studying passive shape perception

We describe a computer-controlled tactile stimulator for use in human psychophysical and monkey neurophysiological studies of 3D shape perception. The stimulator is constructed primarily of commercially available parts, as well as a few custom-built pieces for which we will supply diagrams upon request. There are two components to the stimulator: a tactile component and a hand positioner component. The tactile component consists of multiple stimulating units that move about in a Cartesian plane above the restrained hand. Each stimulating unit contains a servo-controlled linear motor with an attached small rotary stepper motor, allowing arbitrary stimulus shapes to contact the skin through vibration, static indentation, or scanning. The hand positioner component modifies the conformation of the restrained hand through a set of mechanical linkages under motorized control. The present design controls the amount of spread between digits 2 and 3, the spread between digits 4 and 3, and the degree to which digit 3 is flexed or extended, thereby simulating different conformations of the hand in contact with objects. This design is easily modified to suit the needs of the experimenter. Because the two components of the stimulator are independently controlled, the stimulator allows for parametric study of the mechanoreceptive and proprioceptive contributions to 3D tactile shape perception.

Anticipatory postural adjustments stabilise the whole upper-limb prior to a gentle index finger tap

Little is known about anticipatory postural adjustments (APAs) developing when body segments of tiny mass are moved. Thus, APAs in the human upper-limb were investigated during a gentle and small index finger tap (35 mm stroke in 50 ms). This task was fulfilled by ten subjects either with prone or supine hand. EMG was recorded from Flexor Digitorum Superficialis (FDS), the prime mover, and from several upper-limb muscles under slight tonic contraction. Regardless of hand posture, EMG was inhibited in Flexor Carpi Radialis and facilitated in Extensor Carpi Radialis well before the FDS burst. With the prone hand, the prime mover activity was preceded by Biceps inhibition and Triceps facilitation; this effect reverted in sign with the supine hand. A postural reversal was also observed in Anterior Deltoid and Trapezius which were both inhibited with the prone hand. The effect in Trapezius was present only with the unsupported forearm. It is thus demonstrated that a gentle small finger tap produces well-defined anticipatory natural synergies behaving as the most "classical" APAs: (1) they are distributed to several upper-limb muscles creating a postural chain aiming to prevent the effects of the interaction torques generated by the voluntary movement; (2) they change in amplitude according to the level of postural stability and (3) they revert in sign when movement direction is reverted. These results are also corroborated by data obtained from a simple mechanical model simulating finger tapping in a fictive upper-limb. A possible role of APAs in controlling movements' accuracy is also discussed.

Interaction of finger enslaving and error compensation in multiple finger force production

Previous studies have documented two patterns of finger interaction during multi-finger pressing tasks, enslaving and error compensation, which do not agree with each other. Enslaving is characterized by positive correlation between instructed (master) and non-instructed (slave) finger(s) while error compensation can be described as a pattern of negative correlation between master and slave fingers. We hypothesize that pattern of finger interaction, enslaving or compensation depends on the initial force level and the magnitude of the targeted force change. Subjects were instructed to press with four fingers (I index, M middle, R ring, and L little) from a specified initial force to target forces following a ramp target line. Force-force relations between master and each of three slave fingers were analyzed during the ramp phase of trials by calculating correlation coefficients within each master-slave pair and then two-factor ANOVA was performed to determine effect of initial force and force increase on the correlation coefficients. It was found that, as initial force increased, the value of the correlation coefficient decreased and in some cases became negative, i.e. the enslaving transformed into error compensation. Force increase magnitude had a smaller effect on the correlation coefficients. The observations support the hypothesis that the pattern of inter-finger interaction--enslaving or compensation--depends on the initial force level and, to a smaller degree, on the targeted magnitude of the force increase. They suggest that the controller views tasks with higher steady-state forces and smaller force changes as implying a requirement to avoid large changes in the total force.

Do synergies decrease force variability? A study of single-finger and multi-finger force production

We tested a hypothesis that force production by multi-finger groups leads to lower indices of force variability as compared to similar single-finger tasks. Three experiments were performed with quick force production, steady-state force production under visual feedback, and steady-state force production without visual feedback. In all experiments, a range of force levels was used computed as percentages of the maximal voluntary contraction force for each involved finger combination. Force standard deviation increased linearly with force magnitude across all three experiments and all finger combinations. There were modest differences between multi-finger and single-finger tasks in the indices of force variability, significant only in the tasks with steady-state force production under visual feedback. When fingers acted in groups, each finger showed significantly higher force variability as compared to its single-finger task and as compared to the multi-finger group as a whole. Fingers that were not instructed to produce force also showed close to linear relations between force standard deviation and force magnitude. For these fingers, indices of force variability were much higher as compared to those computed for the forces produced by instructed fingers. We interpret the findings within a feed-forward scheme of multi-finger control with two inputs only one of which is related to the explicit task. The total force variability reflects variability in only the task-related component, while variability of the finger forces is also due to variability of the component that is not related to the task. The findings tentatively suggest that total force variability originates at an upper level of the control hierarchy in accordance to the Weber-Fechner law rather than reflects a "neural noise" at the segmental level.