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Smoothness is a hallmark of healthy movement. Past research indicates that smoothness may be a side product of a control strategy that minimizes error. However, this is not the only reason for smooth movements. Our musculoskeletal system itself contributes to movement smoothness: the mechanical impedance (inertia, damping, and stiffness) of our limbs and joints resists sudden change, resulting in a natural smoothing effect. How the biomechanics and neural control interact to result in an observed level of smoothness is not clear. The purpose of this study is to 1 ) characterize the smoothness of wrist rotations, 2 ) compare it with the smoothness of planar shoulder-elbow (reaching) movements, and 3 ) determine the cause of observed differences in smoothness. Ten healthy subjects performed wrist and reaching movements involving different targets, directions, and speeds. We found wrist movements to be significantly less smooth than reaching movements and to vary in smoothness with movement direction. To identify the causes underlying these observations, we tested a number of hypotheses involving differences in bandwidth, signal-dependent noise, speed, impedance anisotropy, and movement duration. Our simulations revealed that proximal-distal differences in smoothness reflect proximal-distal differences in biomechanics: the greater impedance of the shoulder-elbow filters neural noise more than the wrist. In contrast, differences in signal-dependent noise and speed were not sufficiently large to recreate the observed differences in smoothness. We also found that the variation in wrist movement smoothness with direction appear to be caused by, or at least correlated with, differences in movement duration, not impedance anisotropy. NEW & NOTEWORTHY This article presents the first thorough characterization of the smoothness of wrist rotations (flexion-extension and radial-ulnar deviation) and comparison with the smoothness of reaching (shoulder-elbow) movements. We found wrist rotations to be significantly less smooth than reaching movements and determined that this difference reflects proximal-distal differences in biomechanics: the greater impedance (inertia, damping, stiffness) of the shoulder-elbow filters noise in the command signal more than the impedance of the wrist., (Copyright © 2017 the American Physiological Society.)

Human axons in vivo were subjected to subthreshold currents with a threshold impedance amplitude profile to allow the use of frequency domain techniques to determine the propensity for resonant behavior and to clarify the relative contributions of different ion channels to their low-frequency responsiveness. Twenty-four studies were performed on the motor and sensory axons of the median nerve in six subjects. The response to oscillatory currents was tested between direct current (DC) and 16 Hz. A resonant peak at ∼2-2.5 Hz was found in the response of hyperpolarized axons, but there was only a small broad response in axons at resting membrane potential (RMP). A mathematical model of axonal excitability developed using DC pulses provided a good fit to the frequency response for human axons and indicated that the hyperpolarization-activated current Ih and the slow potassium current IKs are principally responsible for the resonance. However, the results indicate that if axons are hyperpolarized by more than -60% of resting threshold, the only conductances that are appreciably active are Ih and the leak conductance, i.e., that the activity of these conductances can be studied in vivo virtually in isolation at hyperpolarized membrane potentials. Given that the leak conductance dampens resonance, it is suggested that the -60% hyperpolarization used here is optimal for Ih As expected, differences between the frequency responses of motor and sensory axons were present and best explained by reduced slow potassium conductance GKs, up-modulation of Ih, and increased persistent Na(+) current INaP (due to depolarization of RMP) in sensory axons., (Copyright © 2016 the American Physiological Society.)

During interaction with objects, we form an internal representation of their mechanical properties. This representation is used for perception and for guiding actions, such as in precision grip, where grip force is modulated with the predicted load forces. In this study, we explored the relationship between grip force adjustment and perception of stiffness during interaction with linear elastic force fields. In a forced-choice paradigm, participants probed pairs of virtual force fields while grasping a force sensor that was attached to a haptic device. For each pair, they were asked which field had higher level of stiffness. In half of the pairs, the force feedback of one of the fields was delayed. Participants underestimated the stiffness of the delayed field relatively to the nondelayed, but their grip force characteristics were similar in both conditions. We analyzed the magnitude of the grip force and the lag between the grip force and the load force in the exploratory probing movements within each trial. Right before answering which force field had higher level of stiffness, both magnitude and lag were similar between delayed and nondelayed force fields. These results suggest that an accurate internal representation of environment stiffness and time delay was used for adjusting the grip force. However, this representation did not help in eliminating the bias in stiffness perception. We argue that during performance of a perceptual task that is based on proprioceptive feedback, separate neural mechanisms are responsible for perception and action-related computations in the brain., (Copyright © 2015 the American Physiological Society.)

Transcranial direct current stimulation (tDCS) is used as a noninvasive tool to modulate brain excitability in humans. Recently, several studies have demonstrated that tDCS applied over the motor cortex also modulates spinal neural network excitability and therefore can be used to explore the corticospinal control acting on spinal neurons. Previously, we showed that reciprocal inhibition directed to wrist flexor motoneurons is enhanced during contralateral anodal tDCS, but it is likely that the corticospinal control acting on spinal networks controlling wrist flexors and extensors is not similar. The primary aim of the study was to explore the effects of anodal tDCS on reciprocal inhibition directed to wrist extensor motoneurons. To further examine the supraspinal control acting on the reciprocal inhibition between wrist flexors and extensors, we also explored the effects of the tDCS applied to the ipsilateral hand motor area. In healthy volunteers, we tested the effects induced by sham and anodal tDCS on reciprocal inhibition pathways innervating wrist muscles. Reciprocal inhibition directed from flexor to extensor muscles and the reverse situation, i.e., reciprocal inhibition, directed from extensors to flexors were studied in parallel with the H reflex technique. Our main finding was that contralateral anodal tDCS induces opposing effects on reciprocal inhibition: it decreases reciprocal inhibition directed from flexors to extensors, but it increases reciprocal inhibition directed from extensors to flexors. The functional result of these opposite effects on reciprocal inhibition seems to favor wrist extension excitability, suggesting an asymmetric descending control onto the interneurons that mediate reciprocal inhibition., (Copyright © 2014 the American Physiological Society.)

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

It is well known that discharge of neurons in the primary motor cortex (M1) depends on end-point force and limb posture. However, the details of these relations remain unresolved. With the development of brain-machine interfaces (BMIs), these issues have taken on practical as well as theoretical importance. We examined how the M1 encodes movement by comparing single-neuron and electromyographic (EMG) preferred directions (PDs) and by predicting force and EMGs from multiple neurons recorded during an isometric wrist task. Monkeys moved a cursor from a central target to one of eight peripheral targets by exerting force about the wrist while the forearm was held in one of two postures. We fit tuning curves to both EMG and M1 activity measured during the hold period, from which we computed both PDs and the change in PD between forearm postures (ΔPD). We found a unimodal distribution of these ΔPDs, the majority of which were intermediate between the typical muscle response and an unchanging, extrinsic coordinate system. We also discovered that while most neuron-to-EMG predictions generalized well across forearm postures, end-point force measured in extrinsic coordinates did not. The lack of force generalization was due to musculoskeletal changes with posture. Our results show that the dynamics of most of the recorded M1 signals are similar to those of muscle activity and imply that a BMI designed to drive an actuator with dynamics like those of muscles might be more robust and easier to learn than a BMI that commands forces or movements in external coordinates.

Local field potentials (LFPs) in primary motor cortex include significant information about reach target location and upper limb movement kinematics. Some evidence suggests that they may be a more robust, longer-lasting signal than action potentials (spikes). Here we assess whether LFPs can also be used to decode upper limb muscle activity, a complex movement-related signal. We record electromyograms from both proximal and distal upper limb muscles from monkeys performing a variety of reach-to-grasp and isometric wrist force tasks. We show that LFPs can be used to decode activity from both proximal and distal muscles with performance rivaling that of spikes. Thus, motor cortical LFPs include information about more aspects of movement than has been previously demonstrated. This provides further evidence suggesting that LFPs could provide a highly informative, long-lasting signal source for neural prostheses.

When humans rotate their wrist in flexion-extension, radial-ulnar deviation, and combinations, the resulting paths (like the path of a laser pointer on a screen) exhibit a distinctive pattern of curvature. In this report we show that the passive stiffness of the wrist is sufficient to account for this pattern. Simulating the dynamics of wrist rotations using a demonstrably realistic model under a variety of conditions, we show that wrist stiffness can explain all characteristics of the observed pattern of curvature. We also provide evidence against other possible causes. We further demonstrate that the phenomenon is robust against variations in human wrist parameters (inertia, damping, and stiffness) and choice of model inputs. Our findings explain two previously observed phenomena: why faster wrist rotations exhibit more curvature and why path curvature rotates with pronation-supination of the forearm. Our results imply that, as in reaching, path straightness is a goal in the planning and control of wrist rotations. This requires humans to predict and compensate for wrist dynamics, but, unlike reaching, nonlinear inertial coupling (e.g., Coriolis acceleration) is insignificant. The dominant term to be compensated is wrist stiffness.

Enhancements in the strength of corticospinal projections to muscles are induced in conscious humans by paired associative stimulation (PAS) to the motor cortex. Although most of the previous studies support the hypothesis that the increase of the amplitude of motor evoked potentials (MEPs) by PAS involves long-term potentiation (LTP)-like mechanism in cortical synapses, changes in spinal excitability after PAS have been reported, suggestive of parallel modifications in both cortical and spinal excitability. In a first series of experiments (experiment 1), we confirmed that both flexor carpi radialis (FCR) MEPs and FCR H reflex recruitment curves are enhanced by PAS. To elucidate the mechanism responsible for this change in the H reflex amplitude, we tested, using the same subjects, the hypothesis that enhanced H reflexes are caused by a down-regulation of the efficacy of mechanisms controlling Ia afferent discharge, including presynaptic Ia inhibition and postactivation depression. To address this question, amounts of both presynaptic Ia inhibition of FCR Ia terminals (D1 and D2 inhibitions methods; experiment 2) and postactivation depression (experiment 3) were determined before and after PAS. Results showed that PAS induces a significant decrease of presynaptic Ia inhibition of FCR terminals, which was concomitant with the facilitation of the H reflex. Postactivation depression was unaffected by PAS. It is argued that enhancement of segmental excitation by PAS relies on a selective effect of PAS on the interneurons controlling presynaptic inhibition of Ia terminals.

Functional neuroimaging studies have identified itch-related brain regions. However, no study has investigated the temporal aspect of itch-related brain processing. Here this issue was investigated using electrically evoked itch in ten healthy adults. Itch stimuli were applied to the left wrist and brain activity was measured using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). In the MEG experiment, the magnetic responses evoked by the itch stimuli were observed in the contralateral and ipsilateral frontotemporal regions. The dipoles associated with the magnetic responses were mainly located in the contralateral (nine subjects) and ipsilateral (eight subjects) secondary somatosensory cortex (SII)/insula, which were also activated by the itch stimuli in the fMRI experiment. We also observed an itch-related magnetic response in the posterior part of the centroparietal region in six subjects. MEG and fMRI data showed that the magnetic response in this region was mainly associated with itch-related activation of the precuneus. The latency was significantly longer in the ipsilateral than that in the contralateral SII/insula, suggesting the difference to be associated with transmission in the callosal fibers. The timing of activation of the precuneus was between those of the contralateral and ipsilateral SII/insula. Other sources were located in the premotor, primary motor, and anterior cingulate cortices (one subject each). This study is the first to demonstrate part of the time course of itch-related brain processing. Combining methods with high temporal and spatial resolution (e.g., MEG and fMRI) would be useful to investigate the temporal aspect of the brain mechanism of itch.

To elucidate the cortical circuitry controlling primate forelimb muscles we investigated the synaptic interactions between neighboring motor cortex cells that had postspike output effects in target muscles. In monkeys generating isometric ramp-and-hold wrist torques, pairs of cortical cells were recorded simultaneously with independent electrodes and corticomotoneuronal ("CM") cells were identified by their postspike effects on target forelimb muscles in spike-triggered averages (SpTAs) of electromyographs (EMGs). The response patterns of the cells were determined in response-aligned averages and their synaptic interactions were identified by cross-correlograms of action potentials. The possibility that synchronized firing between cortical cells could mediate spike-correlated effects in the SpTA of EMG was examined in several ways. Sixty-two pairs consisted of one CM cell and a non-CM cell; 15 of these had correlogram peaks of the same magnitude as that of other pairs, but the synchrony peaks did not mediate any postspike effect from the non-CM cell. Twelve pairs of simultaneously recorded CM cells were cross-correlated. Half had features (usually synchrony peaks) in their cross-correlograms and the cells of these pairs also shared some target muscles in common. The other half had flat correlograms and, in most of these pairs, the CM cells affected different muscles. The latter group included pairs of CM cells that facilitated synergistic muscles. These results indicate that common synaptic input specifically affects CM cells that have overlapping muscle fields. Reconstruction of the cortical locations of CM cells affecting 12 different muscles showed a wide and overlapping distribution of cortical colonies of forelimb muscles.

In humans, it is well established that practicing simple, repetitive movements with the distal upper limb induces short-term plasticity in the neural pathways that control training. It is unknown how the neural response to similar training at more proximal joints differs. The purpose of this study was to quantify how ballistic training at proximal and distal upper limb joints influences measures of corticomotor plasticity. To accomplish this goal, we had subjects repetitively practice simple movements for 30 min using the index finger, wrist, or elbow. Before and after training, transcranial magnetic stimulation (TMS) was used to activate the corticomotor pathways innervating the trained joint. We assessed the effect of training by quantifying changes in TMS-elicited joint movements and motor-evoked potentials in the training agonists and antagonists. These measures of training-induced neural plasticity were graded from distal to proximal in the upper limb. Training had the greatest immediate effect on the pathways controlling the index finger and this effect decreased for more proximal joints. Our results suggest that the relative sizes and properties of the cortical areas controlling the proximal and distal upper limb influence the effect of training on the corticomotor pathways. These results have implications for how training influences the neural pathways controlling movement in the proximal and distal portions of the human upper limb and the degree to which these effects can be quantified using TMS.

Repetitive pairing of a peripheral stimulation with a magnetic transcortical stimulation (PAS) is widely used to induce plastic changes in the human motor cortex noninvasively. Based on the contrast between PAS-induced increase of corticospinal excitability and absence of PAS-induced increase of the spinal F wave size, it has been generally accepted that PAS-induced plasticity is cortical in origin. Here, instead of F waves, we used H reflex recruitment curves to assess spinal excitability, and we demonstrate that PAS induces parallel changes in cortical and spinal excitability.

In identical experiments in and out of a MR scanner, we recorded functional magnetic resonance imaging and electromyographic correlates of wrist stabilization against constant and time-varying mechanical perturbations. Positioning errors were greatest while stabilizing random torques. Wrist muscle activity lagged changes in joint angular velocity at latencies suggesting trans-cortical reflex action. Drift in stabilized hand positions gave rise to frequent, accurately directed, corrective movements, suggesting that the brain maintains separate representations of desired wrist angle for feedback control of posture and the generation of discrete corrections. Two patterns of neural activity were evident in the blood-oxygenation-level-dependent (BOLD) time series obtained during stabilization. A cerebello-thalamo-cortical network showed significant activity whenever position errors were present. Here, changes in activation correlated with moment-by-moment changes in position errors (not force), implicating this network in the feedback control of hand position. A second network, showing elevated activity during stabilization whether errors were present or not, included prefrontal cortex, rostral dorsal premotor and supplementary motor area cortices, and inferior aspects of parietal cortex. BOLD activation in some of these regions correlated with positioning errors integrated over a longer time-frame consistent with optimization of feedback performance via adjustment of the behavioral goal (feedback setpoint) and the planning and execution of internally generated motor actions. The finding that nonoverlapping networks demonstrate differential sensitivity to kinematic performance errors over different time scales supports the hypothesis that in stabilizing the hand, the brain recruits distinct neural systems for feedback control of limb position and for evaluation/adjustment of controller parameters in response to persistent errors.

Primary motor cortex (M1) neurons traditionally have been viewed as "upper motor neurons" that directly drive spinal motoneuron pools, particularly during finger movements. We used spike-triggered averages (SpikeTAs) of electromyographic (EMG) activity to select M1 neurons whose spikes signaled the arrival of input in motoneuron pools, and examined the degree of similarity between the activity patterns of these M1 neurons and their target muscles during 12 individuated finger and wrist movements. Neuron-EMG similarity generally was low. Similarity was unrelated to the strength of the SpikeTA effect, to whether the effect was pure versus synchrony, or to the number of muscles influenced by the neuron. Nevertheless, the sum of M1 neuron activity patterns, each weighted by the sign and strength of its SpikeTA effect, could be more similar to the EMG than the average similarity of individual neurons. Significant correlations between the weighted sum of M1 neuron activity patterns and EMG were obtained in six of 17 muscles, but showed R(2) values ranging from only 0.26 to 0.42. These observations suggest that additional factors-including inputs from sources other than M1 and nonlinear summation of inputs to motoneuron pools-also contributed substantially to EMG activity patterns. Furthermore, although each of these M1 neurons produced SpikeTA effects with a significant peak or trough 6-16 ms after the triggering spike, shifting the weighted sum of neuron activity to lead the EMG by 40-60 ms increased their similarity, suggesting that the influence of M1 neurons that produce SpikeTA effects includes substantial synaptic integration that in part may reach the motoneuron pools over less-direct pathways.

The kinematics of movement of all five digits was analyzed during reach-and-grasp tasks for a variety of objects. Ten healthy subjects performed 20 trials involving the grasp of five objects of distinct size and shape. Joint angles were recorded, and digit trajectories were computed using forward kinematics. For a given subject, fingertip trajectories were consistent across trials. The different-sized objects largely produced movement along different portions of a stereotypical trajectory described by a logarithmic spiral. The spirals fit the actual finger positions with a mean error across all trials of 0.23 +/- 0.25 cm and accounted for over 98% of the variance in finger position. These patterns were consistent independent of initial finger posture. Subjects did not produce straight-line movements, either in Cartesian space or joint space. The direction of the thumb trajectories exhibited a greater dependence on object type than the finger trajectories, but still utilized a small percentage (<5%) of the available workspace. These results suggest that restoration of a small but specific part of the workspace could have significant impact on function following hand impairment.

This study was prompted by recent evidence for the existence of positive force feedback in feline locomotor control. Our aim was to establish some basic properties of positive force feedback in relation to load compensation, stability, intrinsic muscle properties, and interaction with displacement feedback. In human subjects, muscles acting about the wrist and ankle were activated by feedback-controlled electrical stimulation. The feedback signals were obtained from sensors monitoring force and displacement. The signals were filtered to mimic transduction by mammalian tendon organ and muscle spindle receptors. We found that when muscles under positive force feedback were loaded inertially, they responded in a stable manner with increased active force. The activation attenuated the muscle stretch (yield) that would otherwise occur in the absence of feedback. With enough positive force feedback gain, yield could actually reverse. This behavior, which we termed the affirming reaction, was reminiscent of the mammalian positive supporting reaction, a postural response elicited by contact of the foot with the ground. Muscles under positive force feedback remained stable, even when the loop gain (Gf) was set at levels of 2 or 3. In a linear system, if Gf > 1, instability occurs when the loop is closed. On further investigation, we found that Gf changed with joint angle: it declined as the load-bearing muscle actively shortened. We inferred that in closed-loop operation, the active muscles always shortened until Gf approached unity. In other words, the length-tension curve of active muscle ensures stability even when force-related excitation of motoneurons is very large. Concomitant negative displacement feedback reinforced and stabilized load compensation up to a certain gain, beyond which instability occurred. In further trials we included delays of up to 40 ms in the positive force feedback pathway, to model the delays recently described for tendon organ reflexes in cat locomotion. Contrary to expectations, this did not destabilize the loop. Indeed, when instability was deliberately evoked by setting displacement feedback gain high, delays in the positive force feedback pathway actually stabilized control. The stabilization of positive force feedback by inherent properties of the neuromuscular system increases the functional scope to be expected of feedback from force receptors in biological motor control. Our results provide a rationale for the delayed excitatory action of Ib heteronymous input on extensor motoneurons in cat locomotion.

It is well known that electrical stimulation of primary somatosensory cortex (SI) evokes movements that resemble those evoked from primary motor cortex. These findings have led to the concept that SI may possess motor capabilities paralleling those of motor cortex and speculation that SI could function as a robust relay mediating motor responses from central and peripheral inputs. The purpose of this study was to rigorously examine the motor output capabilities of SI areas with the use of the techniques of spike- and stimulus-triggered averaging of electromyographic (EMG) activity in awake monkeys. Unit recordings were obtained from primary motor cortex and SI areas 3a, 3b, 1, and 2 in three rhesus monkeys. Spike-triggered averaging was used to assess the output linkage between individual cells and motoneurons of the recorded muscles. Cells in motor cortex producing postspike facilitation (PSpF) in spike-triggered averages of rectified EMG activity were designated corticomotoneuronal (CM) cells. Motor output efficacy was also assessed by applying stimuli through the microelectrode and computing stimulus-triggered averages of rectified EMG activity. One hundred seventy-one sites in motor cortex and 68 sites in SI were characterized functionally and tested for motor output effects on muscle activity. The incidence, character, and magnitude of motor output effects from SI areas were in sharp contrast to effects from CM cell sites in primary motor cortex. Of 68 SI cells tested with spike-triggered averaging, only one area 3a cell produced significant PSpF in spike-triggered averages of EMG activity. In comparison, 20 of 171 (12%) motor cortex cells tested produced significant postspike effects. Single-pulse intracortical microstimulation produced effects at all CM cell sites in motor cortex but at only 14% of SI sites. The large fraction of SI effects that was inhibitory represented yet another marked difference between CM cell sites in motor cortex and SI sites (25% vs 93%). The fact that motor output effects from SI were frequently absent or very weak and predominantly inhibitory emphasizes the differing motor capabilities of SI compared with primary motor cortex.

1. The purpose of this study was 1) to characterize the decrease observed in mean firing rates of motor units in the first 8-15 s of isometric constant-force contractions and 2) to investigate possible mechanisms that could account for the ability to maintain force output in the presence of decreasing motor unit firing rates. 2. The decrease in mean firing rates was characterized by investigating myoelectric signals detected with a specialized quadrifilar needle electrode from the first dorsal interosseus (FDI) and the tibialis anterior (TA) muscles of 19 healthy subjects during a total of 85 constant-force isometric contractions at 30, 50, or 80% of maximal effort. The firing times of motor units were obtained from the myoelectric signals with the use of computer algorithms to decompose the signal into the constituent motor unit action potentials. Time-varying mean firing rates and recruitment thresholds were also calculated. 3. Motor units detected from the TA muscle were found to have a continual decrease in their mean firing rates in 36 of 44 trials performed during isometric ankle dorsiflexion at force values ranging from 30 to 80% of maximal effort and a duration of 8-15 s. Likewise, motor units detected in the FDI muscle displayed a decrease in firing rate in 32 of 41 trials performed during constant-force isometric index finger abduction for contractions ranging from 30 to 80% of maximal effort. In 14 contractions (16% of total), firing rates were essentially constant, whereas in 3 contractions (4%), firing rates appeared to increase. 4. Motor units with the higher recruitment thresholds and lower firing rates tended to display the greater decreases in firing rate over the constant-force interval, whereas motor units with lower recruitment thresholds and higher firing rates had lesser rates of decrease. Furthermore, increasing contraction levels tended to intensify the decrease in the motor unit firing rates. 5. Three possible mechanisms were considered as factors responsible for the maintaining of force output while motor units decreased their firing rates: motor unit recruitment, agonist/antagonist interaction, and twitch potentiation. Of these, motor unit recruitment was discarded first because none was observed during the 8-15 s duration of any of the 85 contractions. Furthermore, contractions outside the physiological range of motor unit recruitment (at 80% of maximal effort) revealed the same decreasing trend in firing rates, ruling out recruitment as the means of sustaining force output. 6. The role of agonist or antagonist muscle interaction was investigated with the use of the muscles controlling the wrist joint. Myoelectric signals were recorded with quadrifilar needle electrodes from the wrist extensor muscles while myoelectric activity in the wrist flexor muscles was concurrently monitored with surface electrodes during constant-force isometric wrist extension at 50% of maximal effort. Firing rates of the motor units in the wrist extensor muscles simultaneously decreased while the flexor muscles were determined to be inactive. 7. All the findings of this study regarding the behavior of the firing rates could be well explained by the reported characteristics of twitch potentiation that have been previously documented in animals and humans. 8. The results of this study, combined with the results of other investigators, provide the following scenario to explain how a constant-force isometric contraction is sustained. As the contraction progresses, the twitch force of the muscle fibers undergoes a potentiation followed by a decrease. Simultaneously, the "late adaptation" property of the motoneuron decreases the firing rate of the motor unit. Findings of this study suggest that voluntary reduction in firing rates also cannot be ruled out as a means to augment the adaptation in motoneurons. (ABSTRACT TRUNCATED)

1. Fifty-nine rubromotoneuronal (RM) cells were identified in two rhesus monkeys on the basis of their postspike facilitation (PSpF) of rectified electromyographic (EMG) activity. These cells were studied in relation to a step tracking task requiring wrist movements between fixed target zones in flexion and extension. Movement away from a 0 position was opposed by spring-like loads (auxotonic). Additionally, nine cells were evaluated using an isometric task. Neuronal discharge could be divided into three basic components: background discharge in the absence of movement, phasic modulation during movement, and tonic modulation during sustained holding against external loads. 2. Four basic patterns of RM cell activity were observed in relation to ramp-and-hold wrist movements: phasic-tonic (44%), pure phasic (22%), pure tonic (2%), and unmodulated (24%). The discharge of unmodulated cells did not covary with movement parameters but, as with other RM cells, background discharge did increase in association with task performance. 3. The phasic discharge of RM cells led to the onset of target muscle EMG activity by an average of 89 +/- 82 ms (mean +/- SD, n = 104) in extensors and 88 +/- 74 ms (n = 30) in flexors. Target muscles are defined as ones showing PSpF of EMG activity. It was found that 94% of extensor and 87% of flexor RM cells discharged before or synchronous with the onset of target muscle EMG activity. 4. Thirty-one RM cells (53%) showed a tonic increase in cell activity during the static hold phase of the task. Twenty-three of these were tested for relations to static torque. Fifteen extension related cells and one flexion cell had significant, positive regression slopes for the relation between tonic discharge rate and static torque. The mean rate-torque slope for extension related cells was 160 Hz/Nm and 103 Hz/Nm for flexion related cells. These mean slopes are about one-third those of corticomotoneuronal (CM) cells. 5. Cell discharge rate was correlated with velocity and rate of change of torque (dT/dt) for 32 RM cells with a phasic component of discharge during movement. The peak increase in phasic discharge above tonic firing rate (PDI, peak dynamic index) was significantly correlated only with velocity in eight cells and only with dT/dt in five cells. The phasic discharge of four additional cells was correlated with both velocity and dT/dt, but for three of these cells, the correlation was stronger for velocity. The mean slope for the relation between velocity and PDI was 0.31 Hz.deg-1.s-1.(ABSTRACT TRUNCATED AT 400 WORDS)

1. Experiments were conducted on single motor units of two forearm muscles, extensor carpi radialis (ECR) and extensor digitorum communis (EDC) of human subjects. Our interest was whether or not task groups could be identified in these forearm muscles, and, if so, was there orderly recruitment within each task group. 2. To test for the presence of separate task groups within ECR, motor-unit recruitment was examined for two isometric contractions:wrist extension and radial deviation. Each of the ECR motor units tested repeatedly discharged during contractions in both directions, indicating the absence of separate task groups in ECR for contractions in these two directions. 3. Recruitment order between pairs of ECR motor-unit action potentials was examined for wrist extension and radial deviation. For 58 paired comparisons, the order of recruitment was the same in both directions. In terms of force output, plots of twitch torque versus recruitment threshold of ECR motor units showed a positive correlation for both directions, wrist extension and radial deviation, demonstrating size-ordered recruitment of ECR motoneurons for both contractions. 4. The EDC motoneuron pool exhibited two partially overlapping subpopulations of motoneurons on the basis of task, one subpopulation recruited for middle finger extension and the second one for ring finger extension. Contractions involving the index and little fingers were not examined. It is concluded that motor-unit task groups do exist within EDC motoneuron pool. Plots of twitch torque versus recruitment threshold showed positive correlations for each of these two task groups.(ABSTRACT TRUNCATED AT 250 WORDS)

1. The activity of globus pallidus (GP) neurons (n = 1,117) was studied in two monkeys to reexamine the relation of neuronal activity to movement type (slow vs. fast) while they performed both a visually guided step and ramp wrist tracking task. To select neurons specifically related to wrist movements, we employed both a somatosensory examination of individual body parts and a statistical analysis of the strength of temporal coupling of neuronal discharges to active wrist movement. 2. Neuronal responses to somatosensory stimulation were studied in 1,000 high-frequency GP neurons, of which 686 exhibited clear responses to manipulation of body parts. Of the latter, 336 responded to passive manipulation of forelimb joints and 58 selectively to passive flexion or extension of the wrist. 3. In the external segment of GP (GPe), most neurons responding to passive wrist movement were found to be clustered in four to five adjacent, closely positioned (separated by 200 microns) tracks in single coronal planes. The clusters were irregular in shape with a maximal width of 800-1,000 microns. Separate clusters of neurons responsive to passive wrist movement were identified in planes 3 mm apart in one monkey and in planes 500 microns apart in the other. Multiple clusters of neurons were also found for neurons responsive to joints other than the wrist. These findings suggest a more discrete and complex representation of individual joints in the primate GP than previously conceived. 4. During the performance of the wrist flexion and extension task, 92 neurons showed clear and consistent changes in activity. For these neurons we measured, with a statistical method on a trial-by-trial basis, the strength of temporal coupling between the onset of active wrist movement and the onset of change in neuronal discharge rate. Fifteen neurons showed changes in activity time-locked to the onset of active wrist movement. 5. Twelve pallidal neurons were classified as "wrist-related" based on their movement-locked changes in discharge during task performance and their clear responses to passive wrist joint rotation on examination. All of these neurons exhibited statistically significant modulation of their discharge rate during both fast (peak velocity 97-205 degrees/s) and slow (peak velocity 20-62 degrees/s) wrist movements in the task. The amplitudes of modulation were larger during fast wrist movement than slow movement. These results suggest that the basal ganglia motor circuit plays a similar, rather than an exclusive, role in the control of slow and fast limb movements.

Nonlinear viscous properties of stretch and unloading reflexes in the human wrist were examined using constant-velocity ramp stretches and releases in the range between 5 and 500 mm/s. Subjects were asked to oppose an initial flexor preload and were instructed not to intervene voluntarily when the changes in position were applied. Electromyographic (EMG) activity and net force exerted by the wrist were measured. Although subjects were instructed not to intervene to the applied stretches, even well-practiced subjects sometimes showed unintended triggered reactions, which character could be assisting or resisting. A trial comparison method was used to detect and eliminate responses contaminated by unintended reactions. Ramp stretches further loaded the preloaded flexor muscles. Responses of EMG and force increased steeply initially but after about 1-cm displacement, the slope of these responses decreased to a lower value and remained constant during the remainder of the 5-cm ramp. For higher stretch velocities, the magnitudes and slopes of the responses of EMG and force increased but less than proportionally with ramp velocity. Except for the initial transient, EMG in the loaded flexor muscles and force responses could be described by a product relationship between a linear position-related term and a low fractional power of velocity, after a correction was made for delays in the reflex arc. Mean value of the exponent in the power function of velocity was 0.3 for EMG and 0.17 for force. For higher preloads, incremental responses of force to constant-velocity stretches, plotted as a function of wrist position, shifted to higher values and the slope of increase of force with position became somewhat steeper. This upward shift of the force trace reflects a change of apparent threshold of the stretch reflex. Ramp releases shortened and unloaded the preloaded flexor muscles and stretched the initially inactive extensor muscles. Flexor EMG activity declined progressively with a time course that was independent of velocity. Extensor EMG response depended on preload. At high preloads, there was no activity except for some bursting at the highest velocities. At low preloads, EMG activity was initially absent but started part way through the ramp. The increase of activity was somewhat greater for higher ramp velocities. Force responses to shortening ramps depended on preload. At high preloads, force responses superimposed at all of the low velocities but fell to slightly lower forces at the higher velocities. At low preloads, force traces again superimposed for low velocities and at high velocities only during the initial part of the response.(ABSTRACT TRUNCATED AT 400 WORDS)

1. Transcranial cortical stimuli (TCCS) were used to elicit motor responses in contralateral wrist flexor and extensor muscles of healthy adult subjects. The motor responses were assessed by surface EMG recordings, by needle recordings of single motor-unit discharges, and by measurements of wrist twitch force. Our main aim was to analyze the single-unit events underlying those changes in latency, amplitude, and duration of the compound EMG responses, which could be induced by voluntary preactivation of target muscles and by changes in stimulation strength. 2. Different stimulus strengths were tested with and without background contractions in the flexor or extensor muscles. For each test (consisting of a series of 20 stimuli) the compound EMG responses were averaged and displayed together with the averaged wrist force signals. Responses of individual flexor and extensor motor units were displayed in raster diagrams and peristimulus time histograms. For units exhibiting a background firing, the mean background interdischarge interval was calculated and compared with the subsequent poststimulus intervals. 3. In relaxed muscles, a shortening of onset latency of evoked compound EMG responses was observed when raising stimulation strength. A similar latency reduction was not seen in any of the single-unit recordings. This would be consistent with the size principle of motoneuron recruitment. 4. A shortening of onset latency of evoked EMG potentials was observed also as a result of a voluntary preactivation. Such latency shifts, which were seen also in single-unit recordings, might be attributed to variations in the time required for D and I wave temporal summation at the anterior horn cell. 5. When raising stimulation strength or when adding voluntary background contraction, the evoked compound EMG potential grew not only in amplitude but also in duration, as later peaks of activity were added to the initial ones. Under optimal conditions (strong stimulus + background contraction), the period of excitation (termed E1) had an onset latency of approximately 15 ms and a duration of approximately 35 ms and was similar for wrist flexor and extensor muscles. 6. We never saw the same flexor or extensor unit fire more than once during the E1 period. For units preactivated by a background contraction, the stimulus-triggered impulse exhibited latency shifts, which, to a large extent, depended on the timing of the stimulus in relation to a preceding background discharge and which could be influenced by a change in stimulation strength.(ABSTRACT TRUNCATED AT 400 WORDS)