The Nature of Finger Enslaving: New Results and Their Implications

Two aspects of feed-forward control of action stability: effects of action speed and unexpected events

We explored two types of anticipatory synergy adjustments (ASA) during accurate four-finger total force production task. The first type is a change in the index of force-stabilizing synergy during a steady state when a person is expecting a signal to produce a quick force change, which is seen even when the signal does not come (steady-state ASA). The other type is the drop in in the synergy index prior to a planned force change starting at a known time (transient ASA). The subjects performed a task of steady force production at 10% of maximal voluntary contraction (MVC) followed by a ramp to 20% MVC over 1 s, 3 s, and as a step function (0 s). In another task, in 50% of the trials during the steady-state phase, an unexpected signal could come requiring a quick force pulse to 20% MVC (0-surprise). Inter-trial variance in the finger force space was used to quantify the index of force-stabilizing synergy within the uncontrolled manifold hypothesis. We observed significantly lower synergy index values during the steady state in the 0-ramp trials compared to the 1-ramp and 3-ramp trials. There was also larger transient ASA during the 0-ramp trials. In the 0-surprise condition, the synergy index was significantly higher compared to the 0-ramp condition whereas the transient ASA was significantly larger. The finding of transient ASA scaling is of importance for clinical studies, which commonly involve populations with slower actions, which can by itself be associated with smaller ASAs. The participants varied the sharing pattern of total force across the fingers more in the task with "surprises". This was coupled to more attention to precision of performance, i.e., inter-trial deviations from the target as reflected in smaller variance affecting total force, possibly reflecting higher concentration on the task, which the participants perceived as more challenging compared to a similar task without surprise targets.

Three Levels of Neural Control Contributing to Performance-stabilizing Synergies in Multi-finger Tasks

We tested a hypothesis on force-stabilizing synergies during four-finger accurate force production at three levels: (1) The level of the reciprocal and coactivation commands, estimated as the referent coordinate and apparent stiffness of all four fingers combined; (2) The level of individual finger forces; and (3) The level of firing of individual motor units (MU). Young, healthy participants performed accurate four-finger force production at a comfortable, non-fatiguing level under visual feedback on the total force magnitude. Mechanical reflections of the reciprocal and coactivation commands were estimated using small, smooth finger perturbations applied by the "inverse piano" device. Firing frequencies of motor units in the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC) were estimated using surface recording. Principal component analysis was used to identify robust MU groups (MU-modes) with parallel changes in the firing frequency. The framework of the uncontrolled manifold hypothesis was used to compute synergy indices in the spaces of referent coordinate and apparent stiffness, finger forces, and MU-mode magnitudes. Force-stabilizing synergies were seen at all three levels. They were present in the MU-mode spaces defined for MUs in FDS, in EDC, and pooled over both muscles. No effects of hand dominance were seen. The synergy indices defined at different levels of analysis showed no correlations across the participants. The findings are interpreted within the theory of control with spatial referent coordinates for the effectors. We conclude that force stabilization gets contributions from three levels of neural control, likely associated with cortical, subcortical, and spinal circuitry.

Evolution, biomechanics, and neurobiology converge to explain selective finger motor control

Humans use their fingers to perform a variety of tasks, from simple grasping to manipulating objects, to typing and playing musical instruments, a variety wider than any other species. The more sophisticated the task, the more it involves individuated finger movements, those in which one or more selected fingers perform an intended action while the motion of other digits is constrained. Here we review the neurobiology of such individuated finger movements. We consider their evolutionary origins, the extent to which finger movements are in fact individuated, and the evolved features of neuromuscular control that both enable and limit individuation. We go on to discuss other features of motor control that combine with individuation to create dexterity, the impairment of individuation by disease, and the broad extent of capabilities that individuation confers on humans. We comment on the challenges facing the development of a truly dexterous bionic hand. We conclude by identifying topics for future investigation that will advance our understanding of how neural networks interact across multiple regions of the central nervous system to create individuated movements for the skills humans use to express their cognitive activity.

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.

Force matching: motor effects that are not reported by the actor

We explored unintentional drifts of finger forces during force production and matching task. Based on earlier studies, we predicted that force matching with the other hand would reduce or stop the force drift in instructed fingers while uninstructed (enslaved) fingers remain unaffected. Twelve young, healthy, right-handed participants performed two types of tasks with both hands (task hand and match hand). The task hand produced constant force at 20% of MVC level with the Index and Ring fingers pressing in parallel on strain gauge force sensors. The Middle finger force wasn't instructed, and its enslaved force was recorded. Visual feedback on the total force by the instructed fingers was either present throughout the trial or only during the first 5 s (no-feedback condition). The other hand matched the perceived force level of the task hand starting at either 4, 8, or 15 s from the trial initiation. No feedback was ever provided for the match hand force. After the visual feedback was removed, the task hand showed a consistent drift to lower magnitudes of total force. Contrary to our prediction, over all conditions, force matching caused a brief acceleration of force drift in the task hand, which then reached a plateau. There was no effect of matching on drifts in enslaved finger force. We interpret the force drifts within the theory of control with spatial referent coordinates as consequences of drifts in the command (referent coordinate) to the antagonist muscles. This command is not adequately incorporated into force perception.

Loss of finger control complexity and intrusion of flexor biases are dissociable in finger individuation impairment after stroke

The ability to control each finger independently is an essential component of human hand dexterity. A common observation of hand function impairment after stroke is the loss of this finger individuation ability, often referred to as enslavement, i.e., the unwanted coactivation of non-intended fingers in individuated finger movements. In the previous literature, this impairment has been attributed to several factors, such as the loss of corticospinal drive, an intrusion of flexor synergy due to upregulations of the subcortical pathways, and/or biomechanical constraints. These factors may or may not be mutually exclusive and are often difficult to tease apart. It has also been suggested, based on a prevailing impression, that the intrusion of flexor synergy appears to be an exaggerated pattern of the involuntary coactivations of task-irrelevant fingers seen in a healthy hand, often referred to as a flexor bias. Most previous studies, however, were based on assessments of enslavement in a single dimension (i.e., finger flexion/extension) that coincide with the flexor bias, making it difficult to tease apart the other aforementioned factors. Here, we set out to closely examine the nature of individuated finger control and finger coactivation patterns in all dimensions. Using a novel measurement device and a 3D finger-individuation paradigm, we aim to tease apart the contributions of lower biomechanical, subcortical constraints, and top-down cortical control to these patterns in both healthy and stroke hands. For the first time, we assessed all five fingers' full capacity for individuation. Our results show that these patterns in the healthy and paretic hands present distinctly different shapes and magnitudes that are not influenced by biomechanical constraints. Those in the healthy hand presented larger angular distances that were dependent on top-down task goals, whereas those in the paretic hand presented larger Euclidean distances that arise from two dissociable factors: a loss of complexity in finger control and the dominance of an intrusion of flexor bias. These results suggest that finger individuation impairment after stroke is due to two dissociable factors: the loss of finger control complexity present in the healthy hand reflecting a top-down neural control strategy and an intrusion of flexor bias likely due to an upregulation of subcortical pathways. Our device and paradigm are demonstrated to be a promising tool to assess all aspects of the dexterous capacity of the hand.

Quantifying Hand Strength and Isometric Pinch Individuation Using a Flexible Pressure Sensor Grid

Modulating force between the thumb and another digit, or isometric pinch individuation, is critical for daily tasks and can be impaired due to central or peripheral nervous system injury. Because surgical and rehabilitative efforts often focus on regaining this dexterous ability, we need to be able to consistently quantify pinch individuation across time and facilities. Currently, a standardized metric for such an assessment does not exist. Therefore, we tested whether we could use a commercially available flexible pressure sensor grid (Tekscan F-Socket [Tekscan Inc., Norwood, MA, USA]) to repeatedly measure isometric pinch individuation and maximum voluntary contraction (MVC) in twenty right-handed healthy volunteers at two visits. We developed a novel equation informed by the prior literature to calculate isometric individuation scores that quantified percentage of force on the grid generated by the indicated digit. MVC intra-class correlation coefficients (ICCs) for the left and right hands were 0.86 (p < 0.0001) and 0.88 (p < 0.0001), respectively, suggesting MVC measurements were consistent over time. However, individuation score ICCs, were poorer (left index ICC 0.41, p = 0.28; right index ICC -0.02, p = 0.51), indicating that this protocol did not provide a sufficiently repeatable individuation assessment. These data support the need to develop novel platforms specifically for repeatable and objective isometric hand dexterity assessments.

Generalization indicates asymmetric and interactive control networks for multi-finger dexterous movements

Finger dexterity is manifested by coordinated patterns of muscle activity and generalization of learning across contexts. Some fingers flex, others extend, and some are immobile. Whether or not the neural control processes of these direction-specific actions are independent remains unclear. We characterized behavioral principles underlying learning and generalization of dexterous flexion and extension movements, within and across hands, using an isometric dexterity task that precisely measured finger individuation, force accuracy, and temporal synchronization. Two cohorts of participants trained for 3 days in either the flexion or extension direction. All dexterity measures in both groups showed post-training improvement, although finger extension exhibited inferior dexterity. Surprisingly, learning of finger extension generalized to the untrained flexion direction, but not vice versa. This flexion bias was also evident in the untrained hand. Our study indicates direction-specific control circuits for learning of finger flexion and extension that interact by partially, but asymmetrically, transferring between directions.

Unintentional drifts in performance during one-hand and two-hand finger force production

We explored the phenomena of force drifts and unintentional finger force production (enslaving), and their dependence on visual feedback. Predictions have been drawn based on the theory of control with spatial referent coordinates for condition with feedback on instructed (master) finger force, enslaved finger force, and total force for one-hand and two-hand tasks. Subjects produced force under the different feedback conditions without their knowledge. No feedback condition was also used for the one-hand tasks. Overall, feedback of master finger force led to an increase in the enslaved force, feedback on the slave finger force led to a drop in the master force, feedback on the total force led to balanced drifts in the master force down and enslaved force up, and under the no-feedback condition, master and total force drifted down with large variability in the enslaved force drifts. The patterns were the same in both hands in the two-hand tasks when feedback was provided on the forces of one hand only (without subject's knowledge). The index of enslaving always drifted toward higher values. We interpret the findings as reflecting three main factors: drifts in the referent coordinates toward actual finger coordinates, spread of cortical excitation over representations of the fingers, and robust sharing of referent coordinates between the two hands in bimanual tasks. The large consistent drifts in enslaving toward higher values have to be considered in studies of multi-finger synergies.

Optimality, Stability, and Agility of Human Movement: New Optimality Criterion and Trade-Offs

This review of movement stability, optimality, and agility is based on the theory of motor control with changes in spatial referent coordinates for the effectors, the principle of abundance, and the uncontrolled manifold hypothesis. A new optimality principle is suggested based on the concept of optimal sharing corresponding to a vector in the space of elemental variables locally orthogonal to the uncontrolled manifold. Motion along this direction is associated with minimal components along the relatively unstable directions within the uncontrolled manifold leading to a minimal motor equivalent motion. For well-practiced actions, this task-specific criterion is followed in spaces of referent coordinates. Consequences of the suggested framework include trade-offs among stability, optimality, and agility, unintentional changes in performance, hand dominance, finger specialization, individual traits in performance, and movement disorders in neurological patients.

Unintentional force drifts across the human fingers: implications for the neural control of finger tasks

We explored the unintentional force drift across the four fingers of the dominant hand during accurate force production in isometric conditions caused by turning the visual feedback on force off. Our hypotheses were that the Index finger would show smallest drifts and best ability to eliminate the drifts with knowledge of performance in previous trials. Young healthy subjects produced force at 20% of the maximal force level by one finger at a time. There was no significant difference among the fingers in the root mean square error of force during performance with visual feedback. Turning visual feedback off caused force drift to lower magnitudes. The magnitude of force drift was the largest during tasks performed by the Index finger. After each block of twelve trials, the subjects were given feedback on the drift magnitude in that block and used it to correct performance in future trials. There was a total of six blocks. The magnitude of drift correction between consecutive blocks correlated with the magnitude of drift in the earlier block only after the second and fourth blocks. The Index finger failed to improve its performance more than other fingers and demonstrated significant residual drifts to lower force magnitudes in the sixth block of trials. These findings falsified both our hypotheses. Taken together with earlier studies showing advantage of the Index finger across a variety of tasks that require quick and accurate changes in performance, our results suggest that effector specialization along the stability-agility continuum is not limited to the phenomenon of cortical arm/hand dominance but can also be seen across fingers of a hand controlled by the same hemisphere, possibly reflecting the differences in the finger role in prehensile tasks.

Intramuscle Synergies: Their Place in the Neural Control Hierarchy

We accept a definition of synergy introduced by Nikolai Bernstein and develop it for various actions, from those involving the whole body to those involving a single muscle. Furthermore, we use two major theoretical developments in the field of motor control—the idea of hierarchical control with spatial referent coordinates and the uncontrolled manifold hypothesis—to discuss recent studies of synergies within spaces of individual motor units (MUs) recorded within a single muscle. During the accurate finger force production tasks, MUs within hand extrinsic muscles form robust groups, with parallel scaling of the firing frequencies. The loading factors at individual MUs within each of the two main groups link them to the reciprocal and coactivation commands. Furthermore, groups are recruited in a task-specific way with gains that covary to stabilize muscle force. Such force-stabilizing synergies are seen in MUs recorded in the agonist and antagonist muscles but not in the spaces of MUs combined over the two muscles. These observations reflect inherent trade-offs between synergies at different levels of a control hierarchy. MU-based synergies do not show effects of hand dominance, whereas such effects are seen in multifinger synergies. Involuntary, reflex-based, force changes are stabilized by intramuscle synergies but not by multifinger synergies. These observations suggest that multifinger (multimuscle synergies) are based primarily on supraspinal circuitry, whereas intramuscle synergies reflect spinal circuitry. Studies of intra- and multimuscle synergies promise a powerful tool for exploring changes in spinal and supraspinal circuitry across patient populations.