Brach Poston

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.

NET EXCITATION OF THE MOTOR UNIT POOL VARIES WITH LOAD TYPE DURING FATIGUING CONTRACTIONS

To identify the underlying physiological mechanisms for the difference in the time to failure for two types of fatiguing contractions, 20 subjects performed force and position tasks with the elbow flexor muscles at a comparable net muscle torque for a similar duration. Prior to terminating each task, blood flow was occluded to estimate the relative amount of feedback transmitted by small‐diameter afferents to the spinal cord. Mean arterial pressure at the conclusion of the fatiguing contraction increased similarly for the two tasks (force: 119% ± 14%; position: 114% ± 15%). However, the final values for the electromyographic activity for the elbow flexor muscles (26% ± 14% and 21% ± 11%, respectively; P < 0.05), and the increase in the fluctuations in acceleration and force (225% ± 152% and 154% ± 53%, respectively; P < 0.05) in the sagittal plane, were significantly greater during the position task compared with the force task. These results suggest a different balance in the excitatory and inhibitory inputs to the spinal motor neurons for the two tasks, which has implications for the design of work tasks and exercise prescription in rehabilitation. Muscle Nerve, 2005

Movement structure in young and elderly adults during goal-directed movements of the left and right arm

Elderly adults often exhibit performance deficits during goal-directed movements of the dominant arm compared with young adults. Recent studies involving hemispheric lateralization have provided evidence that the dominant and non-dominant hemisphere-arm systems are specialized for controlling different movement parameters and that hemispheric specialization may be reduced during normal aging. The purpose was to examine age-related differences in the movement structure for the dominant (right) and non-dominant (left) during goal-directed movements. Young and elderly adults performed 72 aiming movements as fast and as accurately as possible to visual targets with both arms. The findings suggest that previous research utilizing the dominant arm can be generalized to the non-dominant arm because performance was similar for the two arms. However, as expected, the elderly adults showed shorter relative primary submovement lengths and longer relative primary submovement durations, reaction times, movement durations, and normalized jerk scores compared to the young adults.

Timing-dependent modulation of the posterior parietal cortex–primary motor cortex pathway by sensorimotor training

Interplay between posterior parietal cortex (PPC) and ipsilateral primary motor cortex (M1) is crucial during execution of movements. The purpose of the study was to determine whether functional PPC-M1 connectivity in humans can be modulated by sensorimotor training. Seventeen participants performed a sensorimotor training task that involved tapping the index finger in synchrony to a rhythmic sequence. To explore differences in training modality, one group (n = 8) learned by visual and the other (n = 9) by auditory stimuli. Transcranial magnetic stimulation (TMS) was used to assess PPC-M1 connectivity before and after training, whereas electroencephalography (EEG) was used to assess PPC-M1 connectivity during training. Facilitation from PPC to M1 was quantified using paired-pulse TMS at conditioning-test intervals of 2, 4, 6, and 8 ms by measuring motor-evoked potentials (MEPs). TMS was applied at baseline and at four time points (0, 30, 60, and 180 min) after training. For EEG, task-related power and coherence were calculated for early and late training phases. The conditioned MEP was facilitated at a 2-ms conditioning-test interval before training. However, facilitation was abolished immediately following training, but returned to baseline at subsequent time points. Regional EEG activity and interregional connectivity between PPC and M1 showed an initial increase during early training followed by a significant decrease in the late phases. The findings indicate that parietal-motor interactions are activated during early sensorimotor training when sensory information has to be integrated into a coherent movement plan. Once the sequence is encoded and movements become automatized, PPC-M1 connectivity returns to baseline.

Time to failure of a sustained contraction is predicted by target torque and initial electromyographic bursts in elbow flexor muscles

The purpose of the study was to identify factors that could predict differences among individuals in the time to failure of a submaximal contraction. Twenty subjects (10 men, 25 ± 6 years) supported an inertial load equivalent to 20% of the maximal voluntary contraction (MVC) force with the elbow flexor muscles for as long as possible. The time to failure was predicted by the frequency of electromyographic bursts in the long head of biceps brachii during the first 20% of the contraction, the amplitude of bursts in the brachioradialis during the first 20% of the contraction, and the target torque. Subjects who could sustain the task longer exhibited greater initial (first 20% of contraction) electromyographic burst frequency in the long head of biceps brachii, lower initial burst amplitudes in the brachioradialis muscle, and lower target torque. Knowing the main predictors of a submaximal fatiguing contraction with the elbow flexor muscles may assist clinicians in personalizing therapeutic interventions. Muscle Nerve, 2007

Practice and endpoint accuracy with the left and right hands of old adults: The right-hemisphere aging model

The purpose of the study was to quantify the aging‐related differences in endpoint accuracy during isometric contractions of the left and right hands based on the prediction that declines in motor performance with aging may be greater for muscles controlled by the right hemisphere. Twelve young (6 men, 25 ± 5 years) and 12 old (6 men, 76 ± 6 years) adults performed a task that involved matching the peak of a force–time trajectory to a target. The old adults were less accurate than the young men and exhibited greater endpoint error with the left hand than the right hand on day 1, but not on days 2 and 3. Although electromyographic amplitude was similar between hands, old adults exhibited greater timing variability. These findings indicate that given sufficient practice there was no difference in endpoint accuracy between the left and right hands of old adults, which is not consistent with the prediction of an asymmetrical decline in motor performance by the right‐hemisphere aging model. Conversely, an inability by an old adult to achieve similar accuracy with both hands during such tasks likely indicates an underlying motor impairment. Muscle Nerve, 2007

Movement trajectory smoothness is not associated with the endpoint accuracy of rapid multi-joint arm movements in young and older adults

The minimum variance theory proposes that motor commands are corrupted by signal-dependent noise and smooth trajectories with low noise levels are selected to minimize endpoint error and endpoint variability. The purpose of the study was to determine the contribution of trajectory smoothness to the endpoint accuracy and endpoint variability of rapid multi-joint arm movements. Young and older adults performed arm movements (4 blocks of 25 trials) as fast and as accurately as possible to a target with the right (dominant) arm. Endpoint accuracy and endpoint variability along with trajectory smoothness and error were quantified for each block of trials. Endpoint error and endpoint variance were greater in older adults compared with young adults, but decreased at a similar rate with practice for the two age groups. The greater endpoint error and endpoint variance exhibited by older adults were primarily due to impairments in movement extent control and not movement direction control. The normalized jerk was similar for the two age groups, but was not strongly associated with endpoint error or endpoint variance for either group. However, endpoint variance was strongly associated with endpoint error for both the young and older adults. Finally, trajectory error was similar for both groups and was weakly associated with endpoint error for the older adults. The findings are not consistent with the predictions of the minimum variance theory, but support and extend previous observations that movement trajectories and endpoints are planned independently.

The Influence of Whole-Body Vibration on Creatine Kinase Activity and Jumping Performance in Young Basketball Players

Purpose To quantify creatine kinase (CK) activity changes across time following an acute bout of whole-body vibration (WBV) and determine the association between changes in CK activity and jumping performance. Method Twenty-six elite young basketball players were assigned to 3 groups: 36-Hz and 46-Hz vibration groups (G36 and G46, respectively) and a control group. The study quantified CK activity and jumping performance following an acute bout of WBV at 2 vibration frequencies. Both WBV groups performed a protocol that consisted of 10 sets of 60 s of WBV while standing on a vibration plate in a quarter-squat position. CK activity, countermovement jumps (CMJ), and squat jumps (SJ) were measured immediately before and 24 hr and 48 hr after WBV. In addition, CMJ and SJ were also measured 5 min after WBV. Results CK activity was statistically significantly increased 24 hr following WBV in G36 and G46. At 48 hr after WBV, CK activity was similar to baseline levels in G36 but remained statistically significantly above baseline levels in G46. The CMJ and SJ heights were statistically significantly decreased at 5 min following the protocol for both WBV groups. Overall, the changes in CK activity did not present a strong relationship with the changes in jump heights for any of the comparisons. Conclusions These findings suggest that WBV protocols with such characteristics may not cause excessive muscle damage and may partly explain why many WBV training studies have failed to elicit increases in strength performance.

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.