Training and synchrony in the motor system

A dynamic subset of network interactions underlies tuning to natural movements in marmoset sensorimotor cortex

Mechanisms of computation in sensorimotor cortex must be flexible and robust to support skilled motor behavior. Patterns of neuronal coactivity emerge as a result of computational processes. Pairwise spike-time statistical relationships, across the population, can be summarized as a functional network (FN) which retains single-unit properties. We record populations of single-unit neural activity in forelimb sensorimotor cortex during prey-capture and spontaneous behavior and use an encoding model incorporating kinematic trajectories and network features to predict single-unit activity during forelimb movements. The contribution of network features depends on structured connectivity within strongly connected functional groups. We identify a context-specific functional group that is highly tuned to kinematics and reorganizes its connectivity between spontaneous and prey-capture movements. In the remaining context-invariant group, interactions are comparatively stable across behaviors and units are less tuned to kinematics. This suggests different roles in producing natural forelimb movements and contextualizes single-unit tuning properties within population dynamics.

Corticospinal properties are associated with sensorimotor performance in action video game players

Notwithstanding the apparent demands regarding fine motor skills that are required to perform in action video games, the motor nervous system of players has not been studied systematically. In the present study, we hypothesized to find differences in sensorimotor performance and corticospinal characteristics between action video game players (Players) and Controls. We tested sensorimotor performance in video games tasks and used transcranial magnetic stimulation (TMS) to measure motor map, input-output (IO) and short intra-cortical inhibition (SICI) curves in the first dorsal interosseous (FDI) muscle of Players (n = 18) and Control (n = 18). Players scored higher in performance tests and had stronger SICI and higher motor evoked potential (MEP) amplitudes. Multiple linear regressions showed that Players and Control differed with respect to their relation between reaction time and corticospinal excitability. However, we did not find different motor map topography or different IO curves for Players when compared to Controls. Action video game players showed an increased efficiency of motor cortical inhibitory and excitatory neural networks. Players also showed a different relation of MEPs with reaction time. The present study demonstrates the potential of action video game players as an ideal population to study the mechanisms underlying visuomotor performance and sensorimotor learning.

The human sensorimotor cortex fosters muscle synergies through cortico-synergy coherence

In neuromotor control, the dimensionality of complex muscular activation patterns is effectively reduced through the emergence of muscle synergies. Muscle synergies are tailored to task-specific biomechanical needs. Traditionally, they are considered as low-dimensional neural output of the spinal cord and as such their coherent cortico-muscular pathways have remained underexplored in humans. We investigated whether muscle synergies have a higher-order origin, especially, whether they are manifest in the cortical motor network. We focused on cortical muscle synergy representations involved in balance control and examined changes in cortico-synergy coherence accompanying short-term balance training. We acquired electromyography and electro-encephalography and reconstructed cortical source activity using adaptive spatial filters. The latter were based on three muscle synergies decomposed from the activity of nine unilateral leg muscles using non-negative matrix factorization. The corresponding cortico-synergy coherence displayed phase-locked activity at the Piper rhythm, i.e., cortico-spinal synchronization around 40 Hz. Our study revealed the presence of muscle synergies in the motor cortex, in particular, in the paracentral lobule, known for the representation of lower extremities. We conclude that neural oscillations synchronize between the motor cortex and spinal motor neuron pools signifying muscle synergies. The corresponding cortico-synergy coherence around the Piper rhythm decreases with training-induced balance improvement.

Advancing brain-machine interfaces: moving beyond linear state space models

Advances in recent years have dramatically improved output control by Brain-Machine Interfaces (BMIs). Such devices nevertheless remain robotic and limited in their movements compared to normal human motor performance. Most current BMIs rely on transforming recorded neural activity to a linear state space composed of a set number of fixed degrees of freedom. Here we consider a variety of ways in which BMI design might be advanced further by applying non-linear dynamics observed in normal motor behavior. We consider (i) the dynamic range and precision of natural movements, (ii) differences between cortical activity and actual body movement, (iii) kinematic and muscular synergies, and (iv) the implications of large neuronal populations. We advance the hypothesis that a given population of recorded neurons may transmit more useful information than can be captured by a single, linear model across all movement phases and contexts. We argue that incorporating these various non-linear characteristics will be an important next step in advancing BMIs to more closely match natural motor performance.

Do sensorimotor β-oscillations maintain muscle synergy representations in primary motor cortex?

Coherent β-oscillations are a dominant feature of the sensorimotor system yet their function remains enigmatic. We propose that, in addition to cell intrinsic and/or local network interactions, they are supported by activity propagating recurrently around closed neural 'loops' between primary motor cortex (M1), muscles, and back to M1 via somatosensory pathways. Individual loops reciprocally connect individual muscle synergies ('motor primitives') with their representations in M1, and the conduction time around each loop resonates with the periodic spiking of its constituent neurons/muscles. During β-oscillations, this resonance strengthens within-loop connectivity (via long-term potentiation, LTP), whereas non-resonance between different loops weakens connectivity (via long-term depression, LTD) between M1 representations of different muscle synergies. In this way, β-oscillations help maintain accurate and discrete representations of muscle synergies in M1.

Synchronization of low- and high-threshold motor units

INTRODUCTION

We examined the degree of synchronization for both low- and high-threshold motor unit (MU) pairs at high force levels.

METHODS

MU spike trains were recorded from the quadriceps during high-force isometric leg extensions. Short-term synchronization (between -6 and 6 ms) was calculated for every unique MU pair for each contraction.

RESULTS

At high force levels, earlier recruited motor unit pairs (low-threshold) demonstrated relatively low levels of short-term synchronization (approximately 7.3% extra firings than would have been expected by chance). However, the magnitude of synchronization increased significantly and linearly with mean recruitment threshold (reaching 22.1% extra firings for motor unit pairs recruited above 70% MVC).

CONCLUSIONS

Three potential mechanisms that could explain the observed differences in synchronization across motor unit types are proposed and discussed.

Evoked potentials in motor cortical local field potentials reflect task timing and behavioral performance

Evoked potentials (EPs) are observed in motor cortical local field potentials (LFPs) during movement execution (movement-related potentials [MRPs]) and in response to relevant visual cues (visual evoked potentials [VEPs]). Motor cortical EPs may be directionally selective, but little is known concerning their relation to other aspects of motor behavior, such as task timing and performance. We recorded LFPs in motor cortex of two monkeys during performance of a precued arm-reaching task. A time cue at the start of each trial signaled delay duration and thereby the pace of the task and the available time for movement preparation. VEPs and MRPs were strongly modulated by the delay duration, VEPs being systematically larger in short-delay trials and MRPs larger in long-delay trials. Despite these systematic modulations related to the task timing, directional selectivity was similar in short and long trials. The behavioral reaction time was positively correlated with MRP size and negatively correlated with VEP size, within sessions. In addition, the behavioral performance improved across sessions, in parallel with a slow decrease in the size of VEPs and MRPs. Our results clearly show the strong influence of the behavioral context and performance on motor cortical population activity during movement preparation and execution.

Peripheral and central changes combine to induce motor behavioral deficits in a moderate repetition task

Repetitive motion disorders, such as carpal tunnel syndrome and focal hand dystonia, can be associated with tasks that require prolonged, repetitive behaviors. Previous studies using animal models of repetitive motion have correlated cortical neuroplastic changes or peripheral tissue inflammation with fine motor performance. However, the possibility that both peripheral and central mechanisms coexist with altered motor performance has not been studied. In this study, we investigated the relationship between motor behavior changes associated with repetitive behaviors and both peripheral tissue inflammation and cortical neuroplasticity. A rat model of reaching and grasping involving moderate repetitive reaching with negligible force (MRNF) was used. Rats performed the MRNF task for 2 h/day, 3 days/week for 8 weeks. Reach performance was monitored by measuring reach rate/success, daily exposure, reach movement reversals/patterns, reach/grasp phase times, grip strength and grooming function. With cumulative task exposure, reach performance, grip strength and agility declined while an inefficient food retrieval pattern increased. In S1 of MRNF rats, a dramatic disorganization of the topographic forepaw representation was observed, including the emergence of large receptive fields located on both the wrist/forearm and forepaw with alterations of neuronal properties. In M1, there was a drastic enlargement of the overall forepaw map area, and of the cortex devoted to digit, arm-digits and elbow-wrist responses. In addition, unusually low current amplitude evoked digit movements. IL-1 beta and TNF-alpha increased in forearm flexor muscles and tendons of MRNF animals. The increases in IL-1 beta and TNF-alpha negatively correlated with grip strength and amount of current needed to evoke forelimb movements. This study provides strong evidence that both peripheral inflammation and cortical neuroplasticity jointly contribute to the development of chronic repetitive motion disorders.

Motor unit synchronization in FDI and biceps brachii muscles of strength-trained males

Motor unit (MU) synchronization is the simultaneous or near-simultaneous firing of two MUs which occurs more often than would be expected by chance. The present study sought to investigate the effects of exercise training, muscle group, and force level, by comparing the magnitude of synchronization in the biceps brachii (BB) and first dorsal interosseous (FDI) muscles of untrained and strength-trained college-aged males at two force levels, 30% of maximal voluntary contraction (MVC) and 80% MVC. MU action potentials were recorded directly via an intramuscular needle electrode. The magnitude of synchronization was assessed using previously-reported synchronization indices: k', E, and CIS. Synchronization was significantly higher in the FDI than in the BB. Greater synchronization was observed in the strength-trained group with CIS, but not with E or k'. Also, synchronization was significantly greater at 80% MVC than at 30% MVC with E, but only moderately greater with CIS and there was no force difference with k'. Synchronization prevalence was found to be greater in the BB (80.1%) than in the FDI (71.5%). Thus, although the evidence is a bit equivocal, it appears that MU synchronization is greater at higher forces, and greater in strength-trained individuals than in untrained subjects.

Comparing effects in spike-triggered averages of rectified EMG across different behaviors

Effects in spike-triggered averages (SpikeTAs) of rectified electromyographic activity (EMG) compiled for the same neuron-muscle pair during various behaviors often appear different. Do these differences represent significant changes in the effect of the neuron on the muscle activity? Quantitative comparison of such differences has been limited by two methodological problems, which we address here. First, although the linear baseline trend of many SpikeTAs can be adjusted with ramp subtraction, the curvilinear baseline trend of other SpikeTAs can not. To address this problem, we estimated baseline trends using a form of moving average. Artificial triggers were created in 1 ms increments from 40 ms before to 40 ms after each spike used to compile the SpikeTA. These 81 triggers were used to compile another average of rectified EMG, which we call a single-spike increment-shifted average (single-spike ISA). Single-spike ISAs were averaged to produce an overall ISA, which captured slow trends in the baseline EMG while distributing any spike-locked features evenly throughout the 80 ms analysis window. The overall ISA then was subtracted from the initial SpikeTA, removing any slow baseline trends for more accurate measurement of SpikeTA effects. Second, the measured amplitude and temporal characteristics of SpikeTA effects produced by the same neuron-muscle pair may vary during different behaviors. But whether or not such variation is significant has been difficult to ascertain. We therefore applied a multiple fragment approach to permit statistical comparison of the measured features of SpikeTA effects for the same neuron-muscle pair during different behavioral epochs. Spike trains recorded in each task were divided into non-overlapping fragments of 100 spikes each, and a separate, ISA-corrected, SpikeTA was compiled for each fragment. Measurements made on these fragment SpikeTAs then were used as test statistics for comparison of peak percent increase, mean percent increase, peak width at half maximum, onset latency, and offset latency. The average of each test statistic measured from the fragment SpikeTAs was well correlated with the single measurement made on the overall SpikeTA. The multiple fragment approach provides a sensitive means of identifying significant changes in SpikeTA effects.

Experience dependent plasticity alters cortical synchronization

Theories of temporal coding by cortical neurons are supported by observations that individual neurons can respond to sensory stimulation with millisecond precision and that activity in large populations is often highly correlated. Synchronization is highest between neurons with overlapping receptive fields and modulated by both sensory stimulation and behavioral state. It is not yet clear whether cortical synchronization is an epiphenomenon or a critical component of efficient information transmission. Experimental manipulations that generate receptive field plasticity can be used to test the relationship between synchronization and receptive fields. Here we demonstrate that increasing receptive field size in primary auditory cortex by repeatedly pairing a train of tones with nucleus basalis (NB) stimulation increases synchronization, and decreasing receptive field size by pairing different tone frequencies with NB stimulation decreases synchronization. These observations seem to support the conclusion that neural synchronization is simply an artifact caused by common inputs. However, pairing tone trains of different carrier frequencies with NB stimulation increases receptive field size without increasing synchronization, and environmental enrichment increases synchronization without increasing receptive field size. The observation that receptive fields and synchronization can be manipulated independently suggests that common inputs are only one of many factors shaping the strength and temporal precision of cortical synchronization and supports the hypothesis that precise neural synchronization contributes to sensory information processing.

Partial reconstruction of muscle activity from a pruned network of diverse motor cortex neurons

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.

Finger movements during reach-to-grasp in the monkey: amplitude scaling of a temporal synergy

To reduce the complexity of controlling hand-shaping, recent evidence suggests that the central nervous system uses synergies. In this study, two Rhesus monkeys reached-to-grasp 15 objects, varying in geometric properties, at five grasp force levels. Hand kinematics were recorded using a video-based tracking system. Individual finger movements were described as vectors varying in length and angle. Inflection points (i.e., stereotypic minima/maxima in the temporal profile of each finger vector) exhibited a temporal synchrony for individual fingers and in the coupling across fingers. Inflection point amplitudes varied significantly across objects grasped, scaling linearly with the object grasp dimension. Thus, differences in the vectors as a function of the objects were in the relative scaling of the vector parameters over time rather than a change in the temporal structure. Mahalanobis distance analysis of the inflection points confirmed that changes in inflection point amplitude as a function of objects were greater than changes in timing. Inflection points were independent of the grasp force, consistent with the observation that reach-to-grasp kinematics and grasp force are controlled independently. In summary, the shaping of the hand during reach-to-grasp involves scaling the amplitude of highly stereotypic temporal movements of the fingers.

A spectrum from pure post-spike effects to synchrony effects in spike-triggered averages of electromyographic activity during skilled finger movements

During individuated finger movements, a high proportion of synchrony effects was found in spike-triggered averages (SpikeTAs) of rectified electromyographic activity aligned on the spikes discharged by primary motor cortex (M1) neurons. Because synchrony effects can be produced even if the trigger neuron itself provides no direct synaptic connections to motoneurons, such nonoscillatory synchrony effects often are discounted when considering control of motoneuron pools. We therefore examined the distinctions between pure postspike effects and synchrony effects. The criteria usually applied to distinguish pure and synchrony effects-onset latency and peak width-failed to separate the present SpikeTA effects objectively into distinct subpopulations. Synchrony effects generally were larger than pure effects. Many M1 neurons produced pure effects in some muscles while producing synchrony effects in others. M1 neurons producing no effects, only pure effects, only synchrony effects, or both pure and synchrony effects did not fall into different groups based on discharge characteristics during finger movements. Nor were neurons producing different types of SpikeTA effects segregated spatially in M1. These observations suggest that neurons producing pure and synchrony SpikeTA effects come from similar M1 populations. We discuss potential mechanisms that might have produced a continuous spectrum of variation from pure to synchrony effects in the present monkeys. Although synchrony effects cannot be taken as evidence of mono- or disynaptic connections from the recorded neuron to the motoneuron pool, the functional linkages indicated by synchrony effects represent a substantial fraction of M1 input to motoneuron pools during skilled, individuated finger movements.

Effects of motor imagery on finger force responses to transcranial magnetic stimulation

The purpose of this study was to investigate whether characteristics of finger interaction seen in voluntary finger force production tasks could also be observed during motor imagery. Transcranial magnetic stimulation (TMS) was applied over the contralateral M1 hand area. Three conditions were tested in eight young healthy volunteers: At rest, during motor imagery of maximal force production by the index finger (ImIn), and during motor imagery of maximal force production by all four fingers simultaneously (ImAll). We obtained measures of motor threshold (MT), motor-evoked potentials (MEP) from the contralateral flexor digitorium superficialis, and TMS-induced forces from individual fingers. Increased MEP and decreased MT during motor imagery tasks suggested enhanced excitability of structures involved in the generation of TMS-induced responses. TMS-induced forces were larger during motor imagery tasks than at rest. This effect was present, albeit significantly smaller, in the middle, ring, and little fingers during ImIn as compared to ImAll. This finding has been interpreted as a correlate of the phenomenon of unintended finger force production (enslaving). The motor imagery effect on finger forces evoked by TMS was significantly larger during ImIn (4% MVC) than during ImAll (2.8% MVC) tasks, corresponding to the phenomenon of force deficit. These results provide direct evidence of the neural origin of the main phenomena of finger interaction. Furthermore, the similarities between characteristics of finger interaction during motor imagery and during voluntary movement suggest the involvement of similar neural structures (including M1).

Neuromuscular characteristics of endurance- and power-trained athletes

In response to chronic physical training, the human neuromuscular system undergoes significant and specific adaptations. More importantly, these influences are the result of the type and quantity of physical activity. One of the simplest neuromuscular mechanisms is the spinal stretch reflex. The reflex system was previously viewed as inflexible, with a relatively fixed response that could vary only slightly. However, more recent data have identified an adaptive plasticity in the reflex system. In this respect, the reflex system can be used to assess training and aging adaptations of the human neuromuscular system. Due to their methodological simplicity, both the tendon-tap reflex and the electrically evoked Hoffmann reflex (H-reflex) can be used to assess training adaptations of the human neuromuscular system. The purpose of this paper is to review briefly the tendon-tap and H-reflex paradigms and delineate the research findings pertaining to changes in the reflex system with physical training. For purposes of clarity, this discussion will be divided into the following: (a) differences observed in the tendon-tap reflex, (b) differences observed in the H-reflex, and (c) role of interneurons in mediating these changes.

Monkey hand postural synergies during reach-to-grasp in the absence of vision of the hand and object

Understanding how the CNS controls reach-to-grasp will require behavioral and neurophysiological studies of reach-to-grasp in the monkey, including the evaluation of whole-hand grasp with explicit force requirements. In this study, monkeys performed a reach-to-grasp task in which the size, shape, and orientation of the objects were varied. The monkeys were required to grasp each object at five force levels based on visual feedback. Seventeen positions on the wrist and hand were monitored to quantify kinematics. Hand shaping began with initiation of reach and continued throughout the reach, matching object properties even without vision of the hand or object. Grasp aperture scaled to object size. Singular value decomposition analysis of the marker positions identified two dominant hand postures. The first eigenvector or "eigenposture" consisted of an open hand configuration midway between flexion and extension that explained >93% of the variance. The second eigenposture consisted of hyperextension of all joints that accounted for another 4-5% of the variance. The two eigenpostures were similar across force levels and between monkeys. Reach kinematics consisted of a U-shaped hand path with a bell-shaped velocity profile. Trajectory and speed were independent of grasp force and object properties. In summary, hand shaping during the reach occurred without vision of the hand or object, and hand kinematics were not dependent on grasp force. Furthermore, the reach was independent of grasp force and object properties. These observations imply that the kinematics of reach-to-grasp and grasp force are controlled independently. Similar to humans, monkeys may use a simplifying strategy to reduce the degrees of freedom of the hand during reach-to-grasp.

Early skill learning is expressed through selection and tuning of cortically represented muscle synergies

Skill learning may be based on integrating and adapting movement building blocks organized in the CNS. We examined at what level integration and adaptation occur during early skill learning, the level of individual muscles, muscle synergies or combinations of synergies through time, and whether these operations are expressed through the primary motor cortex (M1). Forelimb muscle and M1 cell activity were recorded over the first day of training on a reach-to-grasp task in rodents. Independent components analysis was used to assess how well muscle activation patterns could be described as time-varying combinations of synergies. In 3 of 11 animals, prereach M1 activity predicted the activation of different combinations of independent components (ICs) to perform the task. With training, animals increasingly adopted postures and prereach patterns of M1 activity that supported activation of the more successful combination. With training, animals also adjusted the activation magnitude (6 of 11 animals) and weights (11 of 11) of specific ICs that constituted the selected combination. Weights represent how IC activation patterns were distributed to forelimb muscles; this distribution pattern was adapted with training. M1 cells (37 of 100) had task-related firing rates that were significantly correlated with IC activation patterns. Changes in M1 firing rates were associated with corresponding changes in either the activation magnitude or weights of the correlated IC. Our data suggest that early skill learning is expressed through selection and tuning of M1 firing rates, which specify time-varying patterns of synergistic muscle contractions in the limb.

Modeling Reaching Impairment After Stroke Using a Population Vector Model of Movement Control That Incorporates Neural Firing-Rate Variability

The directional control of reaching after stroke was simulated by including cell death and firing-rate noise in a population vector model of movement control. In this model, cortical activity was assumed to cause the hand to move in the direction of a population vector, defined by a summation of responses from neurons with cosine directional tuning. Two types of directional error were analyzed: the between-target variability, defined as the standard deviation of the directional error across a wide range of target directions, and the within-target variability, defined as the standard deviation of the directional error for many reaches to a single target.

Both between and within-target variability increased with increasing cell death. The increase in between-target variability arose because cell death caused a nonuniform distribution of preferred directions. The increase in within-target variability arose because the magnitude of the population vector decreased more quickly than its standard deviation for increasing cell death, provided appropriate levels of firing-rate noise were present. Comparisons to reaching data from 29 stroke subjects revealed similar increases in between and within-target variability as clinical impairment severity increased. Relationships between simulated cell death and impairment severity were derived using the between and within-target variability results. For both relationships, impairment severity increased similarly with decreasing percentage of surviving cells, consistent with results from previous imaging studies. These results demonstrate that a population vector model of movement control that incorporates cosine tuning, linear summation of unitary responses, firing-rate noise, and random cell death can account for some features of impaired arm movement after stroke.

Neocortical mechanisms in motor learning

The ability to learn novel motor skills has fundamental importance for adaptive behavior. Neocortical mechanisms support human motor skill learning, from simple practice to adaptation and arbitrary sensory-motor associations. Behavioral and neural manifestations of motor learning evolve in time and involve multiple structures across the neocortex. Modifications of neural properties, synchrony and synaptic efficacy are all related to the development and maintenance of motor skill.

Invited review: Neural network plasticity in respiratory control

Respiratory network plasticity is a modification in respiratory control that persists longer than the stimuli that evoke it or that changes the behavior produced by the network. Different durations and patterns of hypoxia can induce different types of respiratory memories. Lateral pontine neurons are required for decreases in respiratory frequency that follow brief hypoxia. Changes in synchrony and firing rates of ventrolateral and midline medullary neurons may contribute to the long-term facilitation of breathing after brief intermittent hypoxia. Long-term changes in central respiratory motor control may occur after spinal cord injury, and the brain stem network implicated in the production of the respiratory rhythm could be reconfigured to produce the cough motor pattern. Preliminary analysis suggests that elements of brain stem respiratory neural networks respond differently to hypoxia and hypercapnia and interact with areas involved in cardiovascular control. Plasticity or alterations in these networks may contribute to the chronic upregulation of sympathetic nerve activity and hypertension in sleep apnea syndrome and may also be involved in sudden infant death syndrome.