The Society for Integrative and Comparative Biology
From Single Motor Unit Activity to Multiple Grip Forces: Mini-review of Multi-digit Grasping1
1 Department of Kinesiology, Arizona State University, Tempe, Arizona 85287-0404
2 The Harrington Department of Bioengineering. Arizona State University, Tempe, Arizona 85287-0404
3 NSF-IGERT Program in Neural and Musculoskeletal Adaptations in Form and Function, Arizona State University, Tempe, Arizona 85287-0404
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This paper is a mini review of kinetic and kinematic evidence on the control of the hand with emphasis on grasping. It is not meant to be an exhaustive review, rather it summarizes current research examining the mechanisms through which specific patterns of coordination are elicited and observed during reach to grasp movements and static grasping. These coordination patterns include the spatial and temporal covariation of the rotation at multiple joints during reach to grasp movements. A basic coordination between grip forces produced by multiple digits also occurs during whole hand grasping such that normal forces tend to be produced in a synchronous fashion across pairs of digits. Finally, we address current research that suggests that motor unit synchrony across hand muscles and muscle compartments might be one of the neural mechanisms underlying the control of grasping.
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INTRODUCTION |
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Grasping with the entire hand requires coordination among multiple joints and muscles. The control required to produce a successful grasp may be complex due to the large number of muscle and joints involved. When an object is grasped and held against gravity, the control becomes more complex in order to hold the object against gravity and prevent slippage. The question arises as to what strategies the central nervous system (CNS) uses to control the large number of degrees of freedom of the hand, i.e., muscles, joints. The mechanism(s) through which this control may act is not yet well understood. This mini review examines research that has addressed this question using tasks requiring the control of individual and multiple digits. A more extensive review has recently been published (Schieber and Santello, 2004
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PATTERNS OF COORDINATION IN GRASPING |
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Kinematics
The temporal coordination of joint motion has been studied extensively during reach to grasp tasks. The maximum opening of the hand occurs at hand peak velocity and is linearly related to object size (Connolly and Goodale, 1999
; Jeannerod, 1981, 1984). During the reach to grasp objects of different shapes, the whole hand is shaped in a continuous fashion during the reach as a function of object geometry (Santello and Soechting, 1998; Santello et al., 1998, 2002; Winges et al., 2003). This behavior is characterized by consistent covariations in the angular excursion of the metacarpal and proximal interphalangeal joints (Santello et al., 1998, 2002). Principal components analysis of hand kinematics revealed the existence of a few coordination patterns describing the pre-shaping of the entire hand during the reach. The first pattern consisted of a common extension and flexion of the joints, which determined the maximum hand opening, while the second pattern was related to finger span near the end of the reach. Additionally, these patterns of pre-shaping of the hand to object shape occur without the need for continuous visual feedback (Santello et al., 2002; Schettino et al., 2003; Winges et al., 2003). These consistent kinematic patterns are the net result of biomechanical constraints (e.g., flexor and extensor muscles crossing several joints) and neural control (e.g., muscle activation patterns; see below).
Kinetics
The magnitude of normal forces produced by each digit used to grasp and hold an object varies with the object's weight and center of mass position and are dependent on surface texture (Edin et al., 1992; Santello and Soechting, 2000; Zatsiorsky et al., 2002). In any static grasping task, the sum of the forces and moments applied to the object must be equal to zero (Jenmalm and Johansson, 1997). In a two-digit precision grip task, this requires a symmetrical partition of grip (normal) forces between the thumb and one of the fingers involved in the grasp. When additional fingers are used to oppose the thumb force, i.e., three to five digit grasp, the total force produced by the fingers must equal that of the thumb. How the total force exerted by all fingers is shared among each finger (i.e., force sharing pattern), however, is indeterminate (Santello and Soechting, 2000). Nevertheless, when subjects lift and hold an object with five digits, a characteristic force-sharing pattern typically emerges where the index finger produces the largest amount of force followed by the middle, ring and little fingers (Santello and Soechting, 2000). This pattern is established early in the lift (Rearick and Santello, 2002; Reilmann et al., 2001), is modulated according to the object's center of mass also when this is not predictable on a trial-to-trial basis, and is preserved when grasping is performed by the non-preferred hand (Rearick et al., 2003; Salimi et al., 2000). Although general patterns of grip force magnitude exist based on object properties during multi-digit grasping, the grip forces exerted by each digit tend to fluctuate and must be controlled and coordinated in the temporal domain.
In everyday grasping the normal forces produced by each digit are selected based on the properties of the object and the context in which the grasp is taking place. When the entire hand is used to grasp an object the magnitude and temporal relationship between the forces must be adjusted to prevent object slip and maintain its desired position in space. Recent studies have demonstrated that a default strategy may exist where forces between pairs of digits are produced in a synchronous fashion while holding an object against gravity (Santello and Soechting, 2000; Rearick and Santello, 2002; Rearick, et al., 2003). This observation appears to be independent of the amount of force produced by a finger, i.e., force scaling due to changes in the center of mass position (Santello and Soechting, 2000) and the predictability of changes in center of mass as well as handedness (Rearick and Santello, 2002). This consistent tendency of forces to be produced synchronously appears to be specific to grasping and holding an object against gravity. When subjects are asked to produce the same total force without lifting the object, the tendency of forces to be produced synchronously is dramatically reduced (Rearick et al., 2003). These results suggest that the production of synchronous grip forces may serve a functional purpose such as acting as a safety mechanism to ensure grasp stability, i.e., to prevent object slip. This finding also suggests that the central nervous system uses task specific control strategies to coordinate multiple grip forces. One way in which the central nervous system may elicit this behavior is through common neural input to multiple motoneuron pools (see below).
Anatomical considerations
While the biomechanical architecture of the hand is well known, the neural mechanisms underlying the consistent kinematic and kinetic patterns described above is not well understood. Biomechanical constraints within a single digit result from the flexor and extensor tendons crossing multiple joints which produces coupled flexion/extension motion at these joints (Spoor and Landsmeer, 1976). Motion may also be coupled between digits due to webbing between the digits, intertendinous fascia and intertendinous structures such as the juncturae tendinum, which connects the tendons of the extensor digitorum on the dorsum of the hand (von Schroeder and Botte, 1993). Intertendinous connections among the tendons of the flexor digitorum profundus in the carpal tunnel along with the digastric nature of the superficial and deep flexor muscles may also contribute to coupled motion between pairs of digits (Leijnse et al., 1997; Brand and Hollister, 1999).
With regard to the neural control of hand muscles, experimental evidence suggests that simultaneous neural activation of motor units in different compartments of the multi-tendoned flexors and extensor of the digits may contribute to the inability to produce individuated finger forces (Kilbreath and Gandevia, 1994; Reilly and Schieber, 2003). This simultaneous activation of motor units, i.e., motor unit synchrony (see below), has been examined to better understand its effect on motion and forces within and across digits.
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The motor unit is the most basic level of force control. Firing rate and recruitment of motor units are well known mechanisms through which forces can be modulated. Motor unit synchrony has also been identified as a mechanism through which multiple forces may be coordinated (Santello and Fuglevand, 2004
). Motor unit synchronization is thought to occur due to common pre-synaptic input to motor neurons within the same or different muscles (within- and across-muscle synchrony, respectively; Sears and Stagg, 1976; Kirkwood and Sears, 1978; Nordstrom et al., 1992). This common input increases the probability that two motor neurons will fire at the same time. Synchronous firing of motor units could be regarded as a mere by-product of the motor unit recruitment mechanisms. Alternatively, however, motor unit synchrony might have a functional role in the control of grasping, i.e., coupling of finger motion or forces.
Strength of motor unit synchrony
Several studies have examined the extent to which motor units belonging to a single muscle receive common pre-synaptic input. The magnitude of this common input is indirectly measured using indices of motor unit synchrony. The most commonly used indices for quantifying the strength of motor unit synchrony are k' and common input strength (CIS). The k' index is the ratio of the total synchronous discharges to the number of synchronous discharges occurring by chance (Ellaway and Murthy, 1985). The CIS index is computed as the number of synchronous discharges above chance level, normalized by trial duration (Nordstrom et al., 1992). The k' index is more sensitive to fluctuations in motor unit firing rate, so for tasks in which motor unit firing rate is not held constant, the CIS is a more reliable measure of motor unit synchrony strength as it has been show to be uncorrelated with motor unit discharge rate. Motor unit synchrony has been examined primarily during force production tasks and has been compared both within and between muscles. Multi-tendoned muscles such as the m. flexor digitorum profundus (FDP) and m. extensor digitorum communis (EDC) are organized into compartments of muscle that insert on a single digit, although the degree of compartmentalization of these muscles is still controversial (e.g., Keen and Fuglevand, 2004).
Overall, motor unit synchrony appears to be stronger for motor units contained within a single muscle (Bremner et al., 1991a, b; Huesler et al., 2000) than different muscles or muscle compartments. The magnitude of motor unit synchrony has also been related to the amount of separation between the muscles such that increasing separation elicits lower levels of synchrony (Bremner et al., 1991b; Keen and Fuglevand, 2004; Reilly et al., 2004). Task dependency during two digit versus multi-digit force production has also suggested that motor unit synchrony may be decreased for precision versus power grips (Huesler et al., 1998). These results suggest that there may be a functional organization of the neural input to motor units. However, if motor unit synchrony can contribute to the control of forces produced during the grasp, it may be difficult to generalize the results of force production tasks to grasping since force production does not have the same mechanical constraints as grasping, i.e., equilibrium of forces and moments to maintain a stable grasp (Rearick et al., 2003).
Motor unit synchrony during grasping tasks has recently been studied across FDP compartments and a thumb muscle (m. flexor pollicis longus; FPL) to determine the strength of common input elicited by 5-digit grasping (Winges and Santello, 2004). We found moderate to strong synchrony across muscles and muscles compartments. However, the distribution of common input does not appear to be uniform across muscles (i.e., FPL vs. different FDP compartments) but appears to be more uniform across FDP muscle compartments. With regard to FPL vs. FDP compartment synchrony, strong synchrony was consistently found between motor units from FPL and the index finger compartment of FDP, whereas weak synchrony was found between FPL and the FDP compartments of middle, ring and little fingers. This difference might reflect differences in the connectivity patterns of common input to FPL and FDP compartments arising from the greater extent to which thumb and index fingers are involved in object grasping and manipulation. In a 5-digit grasp, however, the index finger also exerts the largest force among all the fingers, and therefore might play a prominent role in the maintenance of a stable grasp compared to the other fingers. Therefore, further research to determine the extent to which motor unit synchrony may be modulated to contribute to the coordination of grip forces is necessary to better understand the neural control of grasping.
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CONCLUSIONS AND FUTURE DIRECTIONS |
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The repertoire of skilled hand movements in humans relies on complex biomechanical architecture and neural activation patterns. Although the coordination of motion and forces of the digits has been studied extensively, the mechanisms through which these forces are produced are not well understood. Motor unit activity of hand muscles has been studied to provide further insight to how multiple muscles are coordinated during behavioral tasks, e.g., grasping. A motor unit simulation (Santello and Fuglevand, 2004
) has shown that a moderate level of motor unit synchrony between two muscles is sufficient to constrain the temporal relationships of grip forces. The issue of task dependency with respect to the strength of motor unit synchrony has not been addressed in a natural grasping task and is currently under investigation. Future research will include further examination of motor unit synchrony during different grasping tasks to better understand the functional aspects of motor unit synchrony and the extent to which it may be modulated according to task. It is possible that the distribution of common input to hand muscles is digit-pair specific, i.e., hard-wired for each muscle/muscle compartment pair. If this is the case, changing the functional role of a digit pair for a given task would not elicit changes in motor unit strength. However, if the central nervous system can modulate the common input to multiple muscles according to task requirements, this would support the notion of motor unit synchrony as a functional and flexible mechanism for the coordination of grip forces.
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ACKNOWLEDGMENTS |
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The authors would like to thank Dr. John F. Soechting for use of the grip apparatus and Dr. Andrew J. Fuglevand for consulting on the intramuscular EMG data acquisition and analysis. We would also like to thank Katherine Maurer, Jamie Johnston and Shailesh Kantak for helping with EMG data collection. The work described in this article was partially supported by NIH grants R01 AR47301 (M. Santello), NS-07309 (M.P. Rearick), and NSF-IGERT 9987619 (S. A. Winges).
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FOOTNOTES |
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1 From the Symposium Recent Developments in Neurobiology Presented at the Annual Meeting of the Society for Integrative and Comparative Biology, 5–9 Jannuary 2004, at New Orleans, Louisiana.
2 E-mail: marco.santello{at}asu.edu
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