Mark Jesunathadas

Force-Independent Distribution of Correlated Neural Inputs to Hand Muscles During Three-Digit Grasping

The ability to modulate digit forces during grasping relies on the coordination of multiple hand muscles. Because many muscles innervate each digit, the CNS can potentially choose from a large number of muscle coordination patterns to generate a given digit force. Studies of single-digit force production tasks have revealed that the electromyographic (EMG) activity scales uniformly across all muscles as a function of digit force. However, the extent to which this finding applies to the coordination of forces across multiple digits is unknown. We addressed this question by asking subjects (n = 8) to exert isometric forces using a three-digit grip (thumb, index, and middle fingers) that allowed for the quantification of hand muscle coordination within and across digits as a function of grasp force (5, 20, 40, 60, and 80% maximal voluntary force). We recorded EMG from 12 muscles (6 extrinsic and 6 intrinsic) of the three digits. Hand muscle coordination patterns were quantified in the amplitude and frequency domains (EMG-EMG coherence). EMG amplitude scaled uniformly across all hand muscles as a function of grasp force (muscle x force interaction: P = 0.997; cosines of angle between muscle activation pattern vector pairs: 0.897-0.997). Similarly, EMG-EMG coherence was not significantly affected by force (P = 0.324). However, coherence was stronger across extrinsic than that across intrinsic muscle pairs (P = 0.0039). These findings indicate that the distribution of neural drive to multiple hand muscles is force independent and may reflect the anatomical properties or functional roles of hand muscle groups.

Influence of Fatigue on Hand Muscle Coordination and EMG-EMG Coherence During Three-Digit Grasping

Fingertip force control requires fine coordination of multiple hand muscles within and across the digits. While the modulation of neural drive to hand muscles as a function of force has been extensively studied, much less is known about the effects of fatigue on the coordination of simultaneously active hand muscles. We asked eight subjects to perform a fatiguing contraction by gripping a manipulandum with thumb, index, and middle fingers while matching an isometric target force (40% maximal voluntary force) for as long as possible. The coordination of 12 hand muscles was quantified as electromyographic (EMG) muscle activation pattern (MAP) vector and EMG-EMG coherence. We hypothesized that muscle fatigue would cause uniform changes in EMG amplitude across all muscles and an increase in EMG-EMG coherence in the higher frequency bands but with an invariant heterogeneous distribution across muscles. Muscle fatigue caused a 12.5% drop in the maximum voluntary contraction force (P < 0.05) at task failure and an increase in the SD of force (P < 0.01). Although EMG amplitude of all muscles increased during the fatiguing contraction (P < 0.001), the MAP vector orientation did not change, indicating that a similar muscle coordination pattern was used throughout the fatiguing contraction. Last, EMG-EMG coherence (0-35 Hz) was significantly greater at the end than at the beginning of the fatiguing contraction (P < 0.01) but was heterogeneously distributed across hand muscles. These findings suggest that similar mechanisms are involved for modulating and sustaining digit forces in nonfatiguing and fatiguing contractions, respectively.

Learned manipulation at unconstrained contacts does not transfer across hands.

Recent studies about sensorimotor control of the human hand have focused on how dexterous manipulation is learned and generalized. Here we address this question by testing the extent to which learned manipulation can be transferred when the contralateral hand is used and/or object orientation is reversed. We asked subjects to use a precision grip to lift a grip device with an asymmetrical mass distribution while minimizing object roll during lifting by generating a compensatory torque. Subjects were allowed to grasp anywhere on the object’s vertical surfaces, and were therefore able to modulate both digit positions and forces. After every block of eight trials performed in one manipulation context (i.e., using the right hand and at a given object orientation), subjects had to lift the same object in the second context for one trial (transfer trial). Context changes were made by asking subjects to switch the hand used to lift the object and/or rotate the object 180° about a vertical axis. Therefore, three transfer conditions, hand switch (HS), object rotation (OR), and both hand switch and object rotation (HS+OR), were tested and compared with hand matched control groups who did not experience context changes. We found that subjects in all transfer conditions adapted digit positions across multiple transfer trials similar to the learning of control groups, regardless of different changes of contexts. Moreover, subjects in both HS and HS+OR group also adapted digit forces similar to the control group, suggesting independent learning of the left hand. In contrast, the OR group showed significant negative transfer of the compensatory torque due to an inability to adapt digit forces. Our results indicate that internal representations of dexterous manipulation tasks may be primarily built through the hand used for learning and cannot be transferred across hands.

Discharge properties of motor units during steady isometric contractions performed with the dorsiflexor muscles

The purpose of this study was to record the discharge characteristics of tibialis anterior motor units over a range of target forces and to import these data, along with previously reported observations, into a computational model to compare experimental and simulated measures of torque variability during isometric contractions with the dorsiflexor muscles. The discharge characteristics of 44 motor units were quantified during brief isometric contractions at torques that ranged from recruitment threshold to an average of 22 ± 14.4% maximal voluntary contraction (MVC) torque above recruitment threshold. The minimal [range: 5.8-19.8 pulses per second (pps)] and peak (range: 8.6-37.5 pps) discharge rates of motor units were positively related to the recruitment threshold torque (R(2) ≥ 0.266; P < 0.001). The coefficient of variation for interspike interval at recruitment was positively associated with recruitment threshold torque (R(2) = 0.443; P < 0.001) and either decreased exponentially or remained constant as target torque increased above recruitment threshold torque. The variability in the simulated torque did not differ from the experimental values once the recruitment range was set to ∼85% MVC torque, and the association between motor twitch contraction times and peak twitch torque was defined as a weak linear association (R(2) = 0.096; P < 0.001). These results indicate that the steadiness of isometric contractions performed with the dorsiflexor muscle depended more on the distributions of mechanical properties than discharge properties across the population of motor units in the tibialis anterior.

Recruitment and derecruitment characteristics of motor units in a hand muscle of young and old adults

The significant decline in motor neuron number after approximately 60 yr of age is accompanied by a remodeling of the neuromuscular system so that average motor unit force increases and the ability of old adults to produce an intended force declines. One possible explanation for the loss of movement precision is that the remodeling increases the difference in recruitment forces between successively recruited motor units in old adults and this augments force variability at motor unit recruitment. The purpose of the study was to compare the forces and discharge characteristics of motor units in a hand muscle of young and old adults at motor unit recruitment and derecruitment. The difference in recruitment force between pairs of motor units did not differ between young (n=54) and old adults (n=56; P=0.702). However, old adults had a greater proportion of contractions in which motor units discharged action potentials transiently before discharging continuously during the ramp increase in force (young: 0.32; old: 0.41; P=0.045). Force variability at motor unit recruitment was greater for old adults compared with young adults (P<or=0.010), but discharge rate and discharge variability did not differ between age groups (P>or=0.729). These results suggest that the difference in force between the recruitment of successive motor units does not differ between age groups, but that motor unit recruitment may be more transient and could contribute to the greater variability in force observed in old adults during graded ramp contractions.

Influence of amplitude cancellation on the accuracy of determining the onset of muscle activity from the surface electromyogram

The purpose of the study was to quantify the influence of amplitude cancellation on the accuracy of detecting the onset of muscle activity based on an analysis of simulated surface electromyographic (EMG) signals. EMG activity of a generic lower limb muscle was simulated during the stance phase of human gait. Surface EMG signals were generated with and without amplitude cancellation by summing simulated motor unit potentials either before (cancellation EMG) or after (no-cancellation EMG) the potentials had been rectified. The two sets of EMG signals were compared at forces of 30% and 80% of maximum voluntary contraction (MVC) and with various low-pass filter cut-off frequencies. Onset time was determined both visually and by an algorithm that identified when the mean amplitude of the signal within a sliding window exceeded a specified standard deviation (SD) above the baseline mean. Onset error was greater for the no-cancellation conditions when determined automatically and by visual inspection. However, the differences in onset error between the two cancellation conditions appear to be clinically insignificant. Therefore, amplitude cancellation does not appear to limit the ability to detect the onset of muscle activity from the surface EMG.

Long-range correlations in motor unit discharge times at low forces are modulated by visual gain and age

•  What is the central question of this study? Changes in visual gain do not influence the time‐dependent structure of motor unit discharge variability in young adults; however, the influence of visual gain on the regularity of motor unit discharge times in old adults is unknown. •  What is the main finding and its importance? We examined the association between visual information and the size and temporal structure of the variability in index finger force and motor unit discharge times when young and old adults performed isometric contractions with a hand muscle. We showed that the regularity with which motor units discharged action potentials decreased with increased gain of visual feedback, regardless of age.

Across-muscle coherence is modulated as a function of wrist posture during two-digit grasping.

The purpose of this study was to investigate the extent to which correlated neural inputs, quantified as EMG-EMG coherence across intrinsic and extrinsic hand muscles, varied as a function of wrist angle during a constant force precision grip task. Eight adults (5 males; mean age 29 years) participated in the experiment. Subjects held an object using a two-digit precision grip at a constant force at a flexed, neutral, and extended wrist posture, while the EMG activity from intrinsic and extrinsic hand muscles was recorded through intramuscular fine-wire electrodes. The integral of z-transformed coherence computed across muscles pairs was greatest in the flexed wrist posture and significantly greater than EMG-EMG coherence measured in the neutral and extended wrist posture (P < 0.01 and 0.05, respectively). Furthermore, EMG-EMG coherence did not differ statistically between the extrinsic and intrinsic muscle pairs, even though it tended to be greater for the extrinsic muscle pair (P ≥ 0.063). These findings lend support to the notion of a functional role of correlated neural inputs to hand muscles for the task-dependent coordination of hand muscle activity that is likely mediated by somatosensory feedback.

A Subject-Independent Method for Automatically Grading Electromyographic Features During a Fatiguing Contraction

Many studies have attempted to monitor fatigue from electromyogram (EMG) signals. However, fatigue affects EMG in a subject-specific manner. We present here a subject-independent framework for monitoring the changes in EMG features that accompany muscle fatigue based on principal component analysis and factor analysis. The proposed framework is based on several time- and frequency-domain features, unlike most of the existing work, which is based on two to three features. Results show that latent factors obtained from factor analysis on these features provide a robust and unified framework. This framework learns a model from EMG signals of multiple subjects, that form a reference group, and monitors the changes in EMG features during a sustained submaximal contraction on a test subject on a scale from zero to one. The framework was tested on EMG signals collected from 12 muscles of eight healthy subjects. The distribution of factor scores of the test subject, when mapped onto the framework was similar for both the subject-specific and subject-independent cases.