The control of whole hand grasping relies on complex coordination of multiple forces. While many studies have characterized the coordination of finger forces and torques, the control of hand muscle activity underlying multi-digit grasping has not been studied to the same extent. Motor-unit synchrony across finger muscles or muscle compartments might be one of the factors underlying the limited individuation of finger forces. Such "unwanted" coupling among finger forces, however, might be desirable when a high level of force coupling is required to prevent object slip during grasping. The goal of this study was to quantify the strength of synchrony between single motor units from extrinsic hand muscles as subjects held a device with a five-digit grasp. During the hold phase, we recorded the normal force exerted by each digit and the electrical activity of single motor units from each of the four divisions of the muscle flexor digitorum profundus (FDP) and one thumb flexor muscle, m. flexor pollicis longus (FPL). The strength of motor-unit synchrony was quantified by the common input strength index (CIS). We found moderate to strong motor-unit synchrony between FPL and the index FDP compartment [CIS: 0.49 +/- 0.03 (SE)] and across most FDP compartments (0.34 +/- 0.02). Weak synchrony, however, was found between FPL and the middle, ring, and little finger FDP compartments (0.25 +/- 0.01). This difference might reflect the larger force contribution of the thumb-index finger pair relative to other thumb-finger combinations in five-digit grasping.

During reaching to grasp objects with different shapes hand posture is molded gradually to the object's contours. The present study examined the extent to which the temporal evolution of hand posture depends on continuous visual feedback. We asked subjects to reach and grasp objects with different shapes under five vision conditions (VCs). Subjects wore liquid crystal spectacles that occluded vision at four different latencies from onset of the reach. As a control, full-vision trials (VC5) were interspersed among the blocked vision trials. Object shapes and all VCs were presented to the subjects in random order. Hand posture was measured by 15 sensors embedded in a glove. Linear regression analysis, discriminant analysis, and information theory were used to assess the effect of removing vision on the temporal evolution of hand shape. We found that reach duration increased when vision was occluded early in the reach. This was caused primarily by a slower approach of the hand toward the object near the end of the reach. However, vision condition did not have a significant effect on the covariation patterns of joint rotations, indicating that the gradual evolution of hand posture occurs in a similar fashion regardless of vision. Discriminant analysis further supported this interpretation, as the extent to which hand posture resembled object shape and the rate at which hand posture discrimination occurred throughout the movement were similar across vision conditions. These results extend previous observations on memory-guided reaches by showing that continuous visual feedback of the hand and/or object is not necessary to allow the hand to gradually conform to object contours.

Winges SA, Furuya S, Faber NJ, Flanders M. Patterns of muscle activity for digital coarticulation.

Anatomical and physiological evidence suggests that common input to motor neurons of hand muscles is an important neural mechanism for hand control. To gain insight into the synaptic input underlying the coordination of hand muscles, significant effort has been devoted to describing the distribution of common input across motor units of extrinsic muscles. Much less is known, however, about the distribution of common input to motor units belonging to different intrinsic muscles and to intrinsic-extrinsic muscle pairs. To address this void in the literature, we quantified the incidence and strength of near-simultaneous discharges of motor units residing in either the same or different intrinsic hand muscles (m. first dorsal, FDI, and m. first palmar interosseus, FPI) during two-digit object hold. To extend the characterization of common input to pairs of extrinsic muscles (previous work) and pairs of intrinsic muscles (present work), we also recorded electromyographic (EMG) activity from an extrinsic thumb muscle (m. flexor pollicis longus, FPL). Motor-unit synchrony across FDI and FPI was weak (common input strength, CIS, mean +/- SE: 0.17 +/- 0.02). Similarly, motor units from extrinsic-intrinsic muscle pairs were characterized by weak synchrony (FPL-FDI: 0.25 +/- 0.02; FPL-FPI: 0.29 +/- 0.03) although stronger than FDI-FPI. Last, CIS from within FDI and FPI was more than three times stronger (0.70 +/- 0.06 and 0.66 +/- 0.06, respectively) than across these muscles. We discuss present and previous findings within the framework of muscle-pair specific distribution of common input to hand muscles based on their functional role in grasping.

. Musclepair specific distribution and grip-type modulation of neural common input to extrinsic digit flexors. J Neurophysiol 96: 1258 -1266, 2006. First published May 24, 2006 doi:10.1152/jn.00327.2006. To gain insight into the synergistic control of hand muscles, we have recently quantified the strength of correlated neural activity across motor units from extrinsic digit flexors during a five-digit object-hold task. We found stronger synchrony and coherence across motor units from thumb and index finger flexor muscle compartment than between the thumb flexor and other finger flexor muscle compartments. The present study of two-digit object hold was designed to determine the extent to which such distribution of common input among thumbfinger flexor muscle compartments, revealed by holding an object with five digits, is preserved when varying the functional role of a given digit pair. We recorded normal force exerted by the digits and electrical activity of single motor units from muscle flexor pollicis longus (FPL) and two compartments of the m. flexor digitorum profundus (FDP2 and FDP3; index and middle finger, respectively). Consistent with our previous results from five-digit grasping, synchrony and coherence across motor units from FPL-FDP2 was significantly stronger than in FPL-FDP3 during object hold with two digits [common input strength: 0.49 Ϯ 0.02 and 0.35 Ϯ 0.02 (means Ϯ SE), respectively; peak coherence: 0.0054 and 0.0038, respectively]. This suggests that the distribution of common neural input is muscle-pair specific regardless of grip type. However, the strength of coherence, but not synchrony, was significantly stronger in two-versus five-digit object hold for both muscle combinations, suggesting the periodicity of common input is sensitive to grip type.

We recently examined the extent to which motor units of digit flexor muscles receive common input during multidigit grasping. This task elicited moderate to strong motor-unit synchrony (common input strength, CIS) across muscles (flexor digitorum profundus, FDP, and flexor pollicis longus, FPL) and across FDP muscle compartments, although the strength of this common input was not uniform across digit pairs. To further characterize the neural mechanisms underlying the control of multidigit grasping, we analyzed the relationship between firing of single motor units from these hand muscles in the frequency domain by computing coherence. We report three primary findings. First, in contrast to what has been reported in intrinsic hand muscles, motor units belonging to different muscles and muscle compartments of extrinsic digit flexors exhibited significant coherence in the 0- to 5- and 5- to 10-Hz frequency ranges and much weaker coherence in the higher 10–20 Hz range (maximum 0.0025 and 0.0008, respectively, pooled across all FDP compartment pairs). Second, the strength and incidence of coherence differed considerably across digit pairs. Third, contrary to what has been reported in the literature, across-muscle coherence can be stronger and more prevalent than within-muscle coherence, as FPL–FDP2 (thumb-index digit pair) exhibited the strongest and most prevalent coherence in our data (0.010 and 43% at 3 Hz, respectively). The heterogeneous organization of common input to these muscles and muscle compartments is discussed in relation to the functional role of individual digit pairs in the coordination of multiple digit forces in grasping.

In the past two decades a large number of studies have successfully characterized important features of the kinetics and kinematics of object grasping and manipulation, providing significant insight into how the Central Nervous System (CNS) controls the hand, one of the most complex motor systems, in a variety of behaviors. In this chapter we briefly review studies of hand kinematics and kinetics and highlight their major findings and open questions. The major focus of this chapter is on the neural control of the hand, an objective that has been pursued by studies on electromyography (EMG) of hand muscles. Here we review what has been learned through different yet complementary methodological approaches. In particular, the study of single motor unit activity has revealed how the distribution of common neural input within and across hand muscles might reflect a muscle-pair specific organization. Studies of motor unit population have revealed important synergistic patterns of muscle activity while also revealing muscle-pair specific patterns of neural coupling. We conclude the chapter with the results of recent simulation studies aiming at combining advantages of single and multi-unit recordings to maximize the amount of information that can be extracted from EMG signal analysis.

Compared with rigid objects, grasping and lifting compliant objects presents additional uncertainties. For any static grasp, forces at the fingertips depend on factors including the locations of the contact points and the contact forces must be coordinated to maintain equilibrium. For compliant objects, the locations and orientations of the contact surfaces change in a force-dependent manner, thus changing the force requirements. Furthermore, every force adjustment then results in additional changes in object shape. This study characterized force and muscle activation patterns in this situation. Fingertip forces were measured as subjects grasped and lifted a 200-g object using their thumb, index, and ring fingers. A spring was sometimes placed under the index and/or ring finger contact surface. Surface electromyographic activity was recorded from ten hand muscles and one proximal arm muscle. The patterns of grip (normal) force and muscle activity were similar across conditions during the load and lift phases, but their amplitude depended on whether the contact surface was compliant. Specifically, the grip force increased smoothly during the load phase of the task under all conditions. To the contrary, the tangential contact (load) force did not increase monotonically when one or more of the contact surfaces were compliant, resulting in a decoupling of the grip and load forces.