The role of primary motor cortex in goal-directed movements: insights from neurophysiological studies on non-human primates

Motor cortical inactivation impairs corrective submovements in mice performing a hold-still center-out reach task

Holding still and aiming reaches to spatial targets may depend on distinct neural circuits. Using automated homecage training and a sensitive joystick, we trained freely moving mice to contact a joystick, hold their forelimb still, and then reach to rewarded target locations. Mice learned the task by initiating forelimb sequences with clearly resolved submillimeter-scale micromovements followed by millimeter-scale reaches to learned spatial targets. Hundreds of thousands of trajectories were decomposed into millions of kinematic submovements, while photoinhibition was used to test roles of motor cortical areas. Inactivation of both caudal and rostral forelimb areas preserved the ability to produce aimed reaches, but reduced reach speed. Inactivation specifically of contralateral caudal forelimb area (CFA) additionally impaired the ability to aim corrective submovements to remembered locations following target undershoots. Our findings show that motor cortical inactivations reduce the gain of forelimb movements but that inactivation specifically of contralateral CFA impairs corrective movements important for reaching a target location.NEW & NOTEWORTHY To test the role of different cortical areas in holding still and reaching to targets, this study combined home-cage training with optogenetic silencing as mice engaged in a learned center-out-reach task. Inactivation specifically of contralateral caudal forelimb area (CFA) impaired corrective movements necessary to reach spatial targets to earn reward.

Interplay between external inputs and recurrent dynamics during movement preparation and execution in a network model of motor cortex

The primary motor cortex has been shown to coordinate movement preparation and execution through computations in approximately orthogonal subspaces. The underlying network mechanisms, and the roles played by external and recurrent connectivity, are central open questions that need to be answered to understand the neural substrates of motor control. We develop a recurrent neural network model that recapitulates the temporal evolution of neuronal activity recorded from the primary motor cortex of a macaque monkey during an instructed delayed-reach task. In particular, it reproduces the observed dynamic patterns of covariation between neural activity and the direction of motion. We explore the hypothesis that the observed dynamics emerges from a synaptic connectivity structure that depends on the preferred directions of neurons in both preparatory and movement-related epochs, and we constrain the strength of both synaptic connectivity and external input parameters from data. While the model can reproduce neural activity for multiple combinations of the feedforward and recurrent connections, the solution that requires minimum external inputs is one where the observed patterns of covariance are shaped by external inputs during movement preparation, while they are dominated by strong direction-specific recurrent connectivity during movement execution. Our model also demonstrates that the way in which single-neuron tuning properties change over time can explain the level of orthogonality of preparatory and movement-related subspaces.

Deciphering Functional Connectivity Differences Between Motor Imagery and Execution of Target-Oriented Grasping

This study aimed to delineate overlapping and distinctive functional connectivity in visual motor imagery, kinesthetic motor imagery, and motor execution of target-oriented grasping action of the right hand. Functional magnetic resonance imaging data were obtained from 18 right-handed healthy individuals during each condition. Seed-based connectivity and multi-voxel pattern analyses were employed after selecting seed regions with the left primary motor cortex and supplementary motor area. There was equivalent seed-based connectivity during the three conditions in the bilateral frontoparietal and temporal areas. When the seed region was the left primary motor cortex, increased connectivity was observed in the left cuneus and superior frontal area during visual and kinesthetic motor imageries, respectively, compared with that during motor execution. Multi-voxel pattern analyses revealed that each condition was differentiated by spatially distributed connectivity patterns of the left primary motor cortex within the right cerebellum VI, cerebellum crus II, and left lingual area. When the seed region was the left supplementary motor area, the connectivity patterns within the right putamen, thalamus, cerebellar areas IV-V, and left superior parietal lobule were significantly classified above chance level across the three conditions. The present findings improve our understanding of the spatial representation of functional connectivity and its specific patterns among motor imagery and motor execution. The strength and fine-grained connectivity patterns of the brain areas can discriminate between motor imagery and motor execution.

Emergent Low-Frequency Activity in Cortico-Cerebellar Networks with Motor Skill Learning

The motor cortex controls skilled arm movement by recruiting a variety of targets in the nervous system, and it is important to understand the emergent activity in these regions as refinement of a motor skill occurs. One fundamental projection of the motor cortex (M1) is to the cerebellum. However, the emergent activity in the motor cortex and the cerebellum that appears as a dexterous motor skill is consolidated is incompletely understood. Here, we report on low-frequency oscillatory (LFO) activity that emerges in cortico-cerebellar networks with learning the reach-to-grasp motor skill. We chronically recorded the motor and the cerebellar cortices in rats, which revealed the emergence of coordinated movement-related activity in the local-field potentials as the reaching skill consolidated. Interestingly, we found this emergent activity only in the rats that gained expertise in the task. We found that the local and cross-area spiking activity was coordinated with LFOs in proficient rats. Finally, we also found that these neural dynamics were more prominently expressed during accurate behavior in the M1. This work furthers our understanding on emergent dynamics in the cortico-cerebellar loop that underlie learning and execution of precise skilled movement.

Distinctive phases and variability of vibration-induced postural reactions highlighted by center of pressure analysis

BACKGROUND

The vibration-induced postural reaction paradigm (VIB-PR) offers a unique way for investigating sensorimotor control mechanisms. Measures of VIB-PR are usually calculated from the whole VIB period, yet recent evidence proposed that distinctive mechanisms are likely at play between the early vs. later phases of the postural reaction.

OBJECTIVES

The present work verified if spatiotemporal analyses of center of pressure (COP) displacements can detect differences between these early/later phases of VIB-PR. Also, we further characterized the intra/inter-individual variability of COP measurements, since the underlying variability of VIB-PR remains largely unexplored.

METHODS

Twenty young volunteers realized two experimental conditions of bipodal stance with eyes closed: (i) bilateral VIB of tibialis anterior (TIB) and (ii) Achilles' (ACH) tendons. Each condition consisted of five trials and lasted 30 s as follows: 10 s baseline, 10 s VIB and 10 s post-VIB. Linear COP variables (antero-posterior (AP) amplitude & velocity) were computed for both VIB and post-VIB periods using the following time-windows: early 2 s, the later 8 s and the whole 10 s duration. Intra- and inter-individual variability were respectively estimated using the standard error of the measurement and the coefficient of variation. Both variability metrics were obtained using five vs. the first three trials.

RESULTS

Significant contrasts were found between time-windows for both VIB and post-VIB periods. COP variables were generally higher during the early 2 s phase compared to the later 8 s phase for both TIB [mean difference between 8 s- 2 s phases: Amplitude AP = -1.11 ± 1.14 cm during VIB and -2.99 ± 1.31 during post-VIB; Velocity AP = -1.17 ± 0.86 cm/s during VIB and -3.13 ± 1.31 cm/s during post-VIB] and ACH tendons [Amplitude AP = -0.37 ± 0.98 cm during VIB and -3.41 ± 1.20 during post-VIB; Velocity AP = -0.31 ± 0.59 cm/s during VIB and -3.89 ± 1.52 cm/s during post-VIB]. Most within- and between-subject variability scores were below 30% and using three instead of five trials had no impact on variability. VIB-PR patterns were quite similar within a same person, but variable behaviors were observed between individuals during the later phase.

CONCLUSION

Our study highlights the relevance of identifying and separately analyzing distinct phases within VIB-PR patterns, as well as characterizing how these patterns vary at the individual level.

The effects of repetitive transcranial magnetic stimulation on standing balance and walking in older adults with age-related neurological disorders: a systematic review and meta-analysis

BACKGROUND

Considerable evidence showed that repetitive transcranial magnetic stimulation (rTMS) can improve standing balance and walking performance in older adults with age-related neurological disorders. We here thus completed a systematic review and meta-analysis to quantitatively examine such benefits of rTMS.

METHODS

A search strategy based on the PICOS principle was used to obtain the literature in four databases. The screening and assessments of quality and risk of bias in the included studies were independently completed by two researchers. Outcomes included scales related to standing balance, Timed Up and Go (TUG) time, and walking speed/time/distance.

RESULTS

Twenty-three studies consisting of 532 participants were included, and the meta-analysis was completed on 21 of these studies. The study quality was good. Compared to control, rTMS induced both short-term (≤3 days after last intervention session) and long-term (≥1 month following last intervention session) significant improvements in balance scales (e.g., Berg Balance Scale), TUG time, and walking speed/time/distance (short-term: standardized mean difference [SMD]=0.26~0.34, 95% confidence interval [CI]=0.05~0.62; long-term: SMD=0.40~0.44, 95% CI=0.04~0.79) for both PD and stroke cohorts. Subgroup analyses suggested that greater than nine sessions of high-frequency rTMS targeting primary motor cortex with greater than 3000 pulses per week can maximize such benefits. Only few mild-to-moderate adverse events/side effects were reported, which were similar between rTMS and control group.

CONCLUSION

The results suggest that rTMS holds promise to improve balance and walking performance in older adults with age-related neurological disorders. Future studies with more rigorous design are needed to confirm the observations in this work.

Hybrid dedicated and distributed coding in PMd/M1 provides separation and interaction of bilateral arm signals

Pronounced activity is observed in both hemispheres of the motor cortex during preparation and execution of unimanual movements. The organizational principles of bi-hemispheric signals and the functions they serve throughout motor planning remain unclear. Using an instructed-delay reaching task in monkeys, we identified two components in population responses spanning PMd and M1. A “dedicated” component, which segregated activity at the level of individual units, emerged in PMd during preparation. It was most prominent following movement when M1 became strongly engaged, and principally involved the contralateral hemisphere. In contrast to recent reports, these dedicated signals solely accounted for divergence of arm-specific neural subspaces. The other “distributed” component mixed signals for each arm within units, and the subspace containing it did not discriminate between arms at any stage. The statistics of the population response suggest two functional aspects of the cortical network: one that spans both hemispheres for supporting preparatory and ongoing processes, and another that is predominantly housed in the contralateral hemisphere and specifies unilateral output.

The motor cortex of the brain primarily controls the opposite side of the body, yet neural activity in this area is often observed during movements of either arm. To understand the functional significance of these signals we must first characterize how they are organized across the neural network. Are there patterns of activity that are unique to a single arm? Are there other patterns that reflect shared functions? Importantly, these features may change across time as motor plans are developed and executed. In this study, we analyzed the responses of individual neurons in the motor cortex and modeled their patterns of co-activity across the population to characterize the changes that distinguish left and right arm use. Across preparation and execution phases of the task, we found that signals became gradually more segregated. Despite many neurons modulating in association with either arm, those that were more dedicated to a single (typically contralateral) limb accounted for a disproportionately large amount of the variance. However, there were also weaker patterns of activity that did not distinguish between the two arms at any stage. These results reveal a heterogeneity in the motor cortex that highlights both independent and interactive components of reaching signals.

Unfolding of spatial representation at systems level in infant rats

Spatial representations enable navigation from early life on. However, the brain regions essential to form spatial representations, like the hippocampus, are considered functionally immature before weaning. Here, we examined the formation of representations of space in rat pups on postnatal day (PD) 16, using a simple habituation paradigm where the pups were exposed to an arena on three occasions, separated by ~140 min. Whereas on the first two occasions the arena was the same, on the third "test" occasion either proximal cues (Prox group), or distal cues (Dist group), or proximal and distal cues (Prox-Dist group), or no cues (No-change group) were rearranged. Locomotion (distance traveled) was used as behavioral measure of habituation, and c-Fos expression to measure regional brain activity at test. Locomotion generally decreased across the first two occasions. At test, it reached a minimum in the No-change group, indicating familiarity with the spatial conditions. By contrast, the Prox-Dist group displayed a significant increase in locomotion which was less robust in the Prox group and absent in the Dist group, a pattern suggesting that the pups relied more on proximal than distal cues during spatial exploration. c-Fos activity in the No-change group was significantly suppressed in the hippocampus (CA1, CA3, dentate gyrus) but simultaneously enhanced in the prelimbic area (PL) of the medial prefrontal cortex, compared with untreated Home-cage controls, pointing to a possible involvement of the PL in regulating locomotion in familiar spaces. By contrast, in both Prox-Dist and Prox groups c-Fos activity was enhanced in hippocampal CA1 and CA3 regions, suggesting these regions might be particularly involved in regulating exploration of spatial novelty. Our findings show that functional representations of space at a systems level are formed already in pre-weanling rats.

Applications of brain-computer interfaces to the control of robotic and prosthetic arms

Brain-computer interfaces (BCIs) have the potential to improve the quality of life of individuals with severe motor disabilities. BCIs capture the user's brain activity and translate it into commands for the control of an effector, such as a computer cursor, robotic limb, or functional electrical stimulation device. Full dexterous manipulation of robotic and prosthetic arms via a BCI system has been a challenge because of the inherent need to decode high dimensional and preferably real-time control commands from the user's neural activity. Nevertheless, such functionality is fundamental if BCI-controlled robotic or prosthetic limbs are to be used for daily activities. In this chapter, we review how this challenge has been addressed by BCI researchers and how new solutions may improve the BCI user experience with robotic effectors.

Cortical pattern generation during dexterous movement is input-driven

Motor cortex controls skilled arm movement by sending temporal patterns of activity to lower motor centers¹. Local cortical dynamics are thought to shape these patterns throughout movement execution^2–4. External inputs have been implicated in setting the initial state of motor cortex^5,6, but they may also have a pattern-generating role. Here, we dissect the contribution of local dynamics and inputs to cortical pattern generation during a prehension task in mice. Perturbing cortex to an aberrant state prevented movement initiation, but after the perturbation was released, cortex either bypassed the normal initial state and immediately generated the pattern that controls reaching, or it failed to generate this pattern. The difference in these two outcomes was likely due to external inputs. We directly investigated the role of inputs by inactivating thalamus; this perturbed cortical activity and disrupted limb kinematics at any stage of the movement. Activation of thalamocortical axon terminals at different frequencies disrupted cortical activity and arm movement in a graded manner. Simultaneous recordings revealed that both thalamic activity and the current state of cortex predicted changes in cortical activity. Thus, the pattern generator for dexterous arm movement is distributed across multiple, strongly-interacting brain regions.

Neural correlates of sparse coding and dimensionality reduction

Supported by recent computational studies, there is increasing evidence that a wide range of neuronal responses can be understood as an emergent property of nonnegative sparse coding (NSC), an efficient population coding scheme based on dimensionality reduction and sparsity constraints. We review evidence that NSC might be employed by sensory areas to efficiently encode external stimulus spaces, by some associative areas to conjunctively represent multiple behaviorally relevant variables, and possibly by the basal ganglia to coordinate movement. In addition, NSC might provide a useful theoretical framework under which to understand the often complex and nonintuitive response properties of neurons in other brain areas. Although NSC might not apply to all brain areas (for example, motor or executive function areas) the success of NSC-based models, especially in sensory areas, warrants further investigation for neural correlates in other regions.

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.

Automated home cage training of mice in a hold-still center-out reach task

An obstacle to understanding neural mechanisms of movement is the complex, distributed nature of the mammalian motor system. Here we present a novel behavioral paradigm for high-throughput dissection of neural circuits underlying mouse forelimb control. Custom touch-sensing joysticks were used to quantify mouse forelimb trajectories with micron-millisecond spatiotemporal resolution. Joysticks were integrated into computer-controlled, rack-mountable home cages, enabling batches of mice to be trained in parallel. Closed loop behavioral analysis enabled online control of reward delivery for automated training. We used this system to show that mice can learn, with no human handling, a direction-specific hold-still center-out reach task in which a mouse first held its right forepaw still before reaching out to learned spatial targets. Stabilogram diffusion analysis of submillimeter-scale micromovements produced during the hold demonstrate that an active control process, akin to upright balance, was implemented to maintain forepaw stability. Trajectory decomposition methods, previously used in primates, were used to segment hundreds of thousands of forelimb trajectories into millions of constituent kinematic primitives. This system enables rapid dissection of neural circuits for controlling motion primitives from which forelimb sequences are built. NEW & NOTEWORTHY A novel joystick design resolves mouse forelimb kinematics with micron-millisecond precision. Home cage training is used to train mice in a hold-still center-out reach task. Analytical methods, previously used in primates, are used to decompose mouse forelimb trajectories into kinematic primitives.

Sensorimotor and executive function slowing in anesthesiology residents after overnight shifts

STUDY OBJECTIVE

Medical residents working overnight call shifts experience sleep deprivation and circadian clock disruption. This leads to deficits in sensorimotor function and increases in workplace accidents. Using quick tablet-based tasks, we investigate whether measureable executive function differences exist following a single overnight call versus routine shift, and whether factors like stress, rest and caffeine affect these measures.

DESIGN

A prospective, observational, longitudinal, comparison study was conducted.

SETTING

An academic tertiary hospital's main operating room suite staffed by attending anesthesiologists, anesthesiology residents, anesthesiologist assistants and nurse anesthetists.

PATIENTS

Subjects were 30 anesthesiology residents working daytime shifts and 30 peers working overnight call shifts from the University of Texas Health Science Center at Houston.

INTERVENTIONS

Before and after their respective work shifts, residents completed the Stanford Sleepiness Scale (SSS) and the ProPoint and AntiPoint tablet-based tasks. These latter tasks are designed to measure sensorimotor and executive functions, respectively.

MEASUREMENTS

The SSS is a self-reported measure of sleepiness. Response times (RTs) are measured in the pointing tasks.

MAIN RESULTS

Call residents exhibited increased RTs across their shifts (post-pre) on both ProPoint (p=0.002) and AntiPoint (p<0.002) tasks, when compared to Routine residents. Increased stress was associated with decreases in AntiPoint RT for Routine (p=0.007), but with greater increases in sleepiness for Call residents (p<0.001). Further, whether or not a Call resident consumed caffeine habitually was associated with ProPoint RT changes; with Call residents who habitually drink caffeine having a greater Pre-Post difference (i.e., more slowing, p<0.001) in ProPoint RT.

CONCLUSIONS

These results indicate that (1) overnight Call residents demonstrate both sensorimotor and cognitive slowing compared to routine daytime shift residents, (2) sensorimotor slowing is greater in overnight Call residents who drink caffeine habitually, and (3) increased stress during a shift reduces (improves) cognitive RTs during routine daytime but not overnight call shifts.

Preferential encoding of movement amplitude and speed in the primary motor cortex and cerebellum

Voluntary movements require control of multiple kinematic parameters, a task carried out by a distributed brain architecture. However, it remains unclear whether regions along the motor system encode single, or rather a mixture of, kinematic parameters during action execution. Here, rapid event-related functional magnetic resonance imaging was used to differentiate brain activity along the motor system during the encoding of movement amplitude, duration, and speed. We present cumulative evidence supporting preferential encoding of kinematic parameters along the motor system, based on blood-oxygenation-level dependent signal recorded in a well-controlled single-joint wrist-flexion task. Whereas activity in the left primary motor cortex (M1) showed preferential encoding of movement amplitude, the anterior lobe of the right cerebellum (primarily lobule V) showed preferential encoding of movement speed. Conversely, activity in the left supplementary motor area (SMA), basal ganglia (putamen), and anterior intraparietal sulcus was not preferentially modulated by any specific parameter. We found no preference in peak activation for duration encoding in any of the tested regions. Electromyographic data was mainly modulated by movement amplitude, restricting the distinction between amplitude and muscle force encoding. Together, these results suggest that during single-joint movements, distinct kinematic parameters are controlled by largely distinct brain-regions that work together to produce and control precise movements. Hum Brain Mapp 38:5970-5986, 2017. © 2017 Wiley Periodicals, Inc.

Perspectives on classical controversies about the motor cortex

Primary motor cortex has been studied for more than a century, yet a consensus on its functional contribution to movement control is still out of reach. In particular, there remains controversy as to the level of control produced by motor cortex ("low-level" movement dynamics vs. "high-level" movement kinematics) and the role of sensory feedback. In this review, we present different perspectives on the two following questions: What does activity in motor cortex reflect? and How do planned motor commands interact with incoming sensory feedback during movement? The four authors each present their independent views on how they think the primary motor cortex (M1) controls movement. At the end, we present a dialogue in which the authors synthesize their views and suggest possibilities for moving the field forward. While there is not yet a consensus on the role of M1 or sensory feedback in the control of upper limb movements, such dialogues are essential to take us closer to one.

Adopting an external focus of attention alters intracortical inhibition within the primary motor cortex

AIM

Although it is well established that an external (EF) compared to an internal (IF) or neutral focus of attention enhances motor performance, little is known about the underlying neural mechanisms. This study aimed to clarify whether the focus of attention influences not only motor performance but also activity of the primary motor cortex (M1) when executing identical fatiguing tasks of the right index finger (first dorsal interosseous). Transcranial magnetic stimulation (TMS) at intensities below motor threshold was applied over M1 to assess and compare the excitability of intracortical inhibitory circuits.

METHODS

In session 1, 14 subjects performed an isometric finger abduction at 30% of their maximal force to measure the time to task failure (TTF) with either an IF or EF. In session 2, the same task was performed with the other focus. In sessions 3 and 4, subthreshold TMS (subTMS) and paired-pulse TMS were applied to the contralateral M1 to compare the activity of cortical inhibitory circuits within M1 during EF and IF.

RESULTS

With an EF, TTF was significantly prolonged (P = 0.01), subTMS-induced electromyographical suppression enhanced (P = 0.001) and short-interval intracortical inhibition (SICI) increased (P = 0.004).

CONCLUSION

The level of intracortical inhibition was previously shown to influence motor performance. Our data shed new light on the ability to instantly modulate the activity of inhibitory circuits within M1 by changing the type of attentional focus. The increased inhibition with EF might contribute to the better movement efficiency, which is generally associated with focusing externally.

Beta Band Corticomuscular Drive Reflects Muscle Coordination Strategies

During force production, hand muscle activity is known to be coherent with activity in primary motor cortex, specifically in the beta-band (15–30 Hz) frequency range. It is not clear, however, if this coherence reflects the control strategy selected by the nervous system for a given task, or if it instead reflects an intrinsic property of cortico-spinal communication. Here, we measured corticomuscular and intermuscular coherence between muscles of index finger and thumb while a two-finger pinch grip of identical net force was applied to objects which were either stable (allowing synergistic activation of finger muscles) or unstable (requiring individuated finger control). We found that beta-band corticomuscular coherence with the first dorsal interosseous (FDI) and abductor pollicis brevis (APB) muscles, as well as their beta-band coherence with each other, was significantly reduced when individuated control of the thumb and index finger was required. We interpret these findings to show that beta-band coherence is reflective of a synergistic control strategy in which the cortex binds task-related motor neurons into functional units.

Force and Position Control in Humans - The Role of Augmented Feedback

During motor behaviour, humans interact with the environment by for example manipulating objects and this is only possible because sensory feedback is constantly integrated into the central nervous system and these sensory inputs need to be weighted in order meet the task specific goals. Additional feedback presented as augmented feedback was shown to have an impact on motor control and motor learning. A number of studies investigated whether force or position feedback has an influence on motor control and neural activation. However, as in the previous studies the presentation of the force and position feedback was always identical, a recent study assessed whether not only the content but also the interpretation of the feedback has an influence on the time to fatigue of a sustained submaximal contraction and the (inhibitory) activity of the primary motor cortex using subthreshold transcranial magnetic stimulation. This paper describes one possible way to investigate the influence of the interpretation of feedback on motor behaviour by investigating the time to fatigue of submaximal sustained contractions together with the neuromuscular adaptations that can be investigated using surface EMG. Furthermore, the current protocol also describes how motor cortical (inhibitory) activity can be investigated using subthreshold TMS, a method known to act solely on the cortical level. The results show that when participants interpret the feedback as position feedback, they display a significantly shorter time to fatigue of a submaximal sustained contraction. Furthermore, subjects also displayed an increased inhibitory activity of the primary cortex when they believed to receive position feedback compared when they believed to receive force feedback. Accordingly, the results show that interpretation of feedback results in differences on a behavioural level (time to fatigue) that is also reflected in interpretation-specific differences in the amount of inhibitory M1 activity.

Primary motor cortex neurons classified in a postural task predict muscle activation patterns in a reaching task

Primary motor cortex (M1) activity correlates with many motor variables, making it difficult to demonstrate how it participates in motor control. We developed a two-stage process to separate the process of classifying the motor field of M1 neurons from the process of predicting the spatiotemporal patterns of its motor field during reaching. We tested our approach with a neural network model that controlled a two-joint arm to show the statistical relationship between network connectivity and neural activity across different motor tasks. In rhesus monkeys, M1 neurons classified by this method showed preferred reaching directions similar to their associated muscle groups. Importantly, the neural population signals predicted the spatiotemporal dynamics of their associated muscle groups, although a subgroup of atypical neurons reversed their directional preference, suggesting a selective role in antagonist control. These results highlight that M1 provides important details on the spatiotemporal patterns of muscle activity during motor skills such as reaching.

Cortex commands the performance of skilled movement

Mammalian cerebral cortex is accepted as being critical for voluntary motor control, but what functions depend on cortex is still unclear. Here we used rapid, reversible optogenetic inhibition to test the role of cortex during a head-fixed task in which mice reach, grab, and eat a food pellet. Sudden cortical inhibition blocked initiation or froze execution of this skilled prehension behavior, but left untrained forelimb movements unaffected. Unexpectedly, kinematically normal prehension occurred immediately after cortical inhibition, even during rest periods lacking cue and pellet. This 'rebound' prehension was only evoked in trained and food-deprived animals, suggesting that a motivation-gated motor engram sufficient to evoke prehension is activated at inhibition's end. These results demonstrate the necessity and sufficiency of cortical activity for enacting a learned skill.

Selection of cortical dynamics for motor behaviour by the basal ganglia

The basal ganglia and cortex are strongly implicated in the control of motor preparation and execution. Re-entrant loops between these two brain areas are thought to determine the selection of motor repertoires for instrumental action. The nature of neural encoding and processing in the motor cortex as well as the way in which selection by the basal ganglia acts on them is currently debated. The classic view of the motor cortex implementing a direct mapping of information from perception to muscular responses is challenged by proposals viewing it as a set of dynamical systems controlling muscles. Consequently, the common idea that a competition between relatively segregated cortico-striato-nigro-thalamo-cortical channels selects patterns of activity in the motor cortex is no more sufficient to explain how action selection works. Here, we contribute to develop the dynamical view of the basal ganglia-cortical system by proposing a computational model in which a thalamo-cortical dynamical neural reservoir is modulated by disinhibitory selection of the basal ganglia guided by top-down information, so that it responds with different dynamics to the same bottom-up input. The model shows how different motor trajectories can so be produced by controlling the same set of joint actuators. Furthermore, the model shows how the basal ganglia might modulate cortical dynamics by preserving coarse-grained spatiotemporal information throughout cortico-cortical pathways.

Neurons in red nucleus and primary motor cortex exhibit similar responses to mechanical perturbations applied to the upper-limb during posture

Primary motor cortex (M1) and red nucleus (RN) are brain regions involved in limb motor control. Both structures are highly interconnected with the cerebellum and project directly to the spinal cord, although the contribution of RN is smaller than M1. It remains uncertain whether RN and M1 serve similar or distinct roles during posture and movement. Many neurons in M1 respond rapidly to mechanical disturbances of the limb, but it remains unclear whether RN neurons also respond to such limb perturbations. We have compared discharges of single neurons in RN (n = 49) and M1 (n = 109) of one monkey during a postural perturbation task. Neural responses to whole-limb perturbations were examined by transiently applying (300 ms) flexor or extensor torques to the shoulder and/or elbow while the monkeys attempted to maintain a static hand posture. Relative to baseline discharges before perturbation onset, perturbations evoked rapid (<100 ms) changes of neural discharges in many RN (28 of 49, 57%) and M1 (43 of 109, 39%) neurons. In addition to exhibiting a greater proportion of perturbation-related neurons, RN neurons also tended to exhibit higher peak discharge frequencies in response to perturbations than M1 neurons. Importantly, neurons in both structures exhibited similar response latencies and tuning properties (preferred torque directions and tuning widths) in joint-torque space. Proximal arm muscles also displayed similar tuning properties in joint-torque space. These results suggest that RN is more sensitive than M1 to mechanical perturbations applied during postural control but both structures may play a similar role in feedback control of posture.

Cell categories and K-nearest neighbor algorithm based decoding of primary motor cortical activity during reach-to-grasp task

Neural decoding is a procedure to acquire intended movement information from neural activity and generate movement commands to control external devices such as intelligent prostheses. In this study, monkey Astra was trained to accomplish a 3-D reach-to-grasp task, and we recorded neural signals from its primary motor cortex (M1) during the task. The task-related cells were divided into four classes based on their correlation with two movement parameters: movement direction and orientation. We adopted the simple k-nearest neighbor (KNN) algorithm as the classifier, and chose cells from appropriate cell classes for movement parameter decoding. Cell classification was shown improving decoding accuracy with relatively less cells, even during movement planning stage (CRT). High decoding accuracy before movement actually performed is of great significance for intelligent prostheses control, and provides evidence that M1 is more than accepting ready-made movement commands but also participating in movement planning. We also found that population of task-related cells in M1 had a preference for specific direction and orientation, and this preference was more significant when it came to population of direction-related cells and orientation-related cells.

Signal-independent timescale analysis (SITA) and its application for neural coding during reaching and walking

What are the relevant timescales of neural encoding in the brain? This question is commonly investigated with respect to well-defined stimuli or actions. However, neurons often encode multiple signals, including hidden or internal, which are not experimentally controlled, and thus excluded from such analysis. Here we consider all rate modulations as the signal, and define the rate-modulations signal-to-noise ratio (RM-SNR) as the ratio between the variance of the rate and the variance of the neuronal noise. As the bin-width increases, RM-SNR increases while the update rate decreases. This tradeoff is captured by the ratio of RM-SNR to bin-width, and its variations with the bin-width reveal the timescales of neural activity. Theoretical analysis and simulations elucidate how the interactions between the recovery properties of the unit and the spectral content of the encoded signals shape this ratio and determine the timescales of neural coding. The resulting signal-independent timescale analysis (SITA) is applied to investigate timescales of neural activity recorded from the motor cortex of monkeys during: (i) reaching experiments with Brain-Machine Interface (BMI), and (ii) locomotion experiments at different speeds. Interestingly, the timescales during BMI experiments did not change significantly with the control mode or training. During locomotion, the analysis identified units whose timescale varied consistently with the experimentally controlled speed of walking, though the specific timescale reflected also the recovery properties of the unit. Thus, the proposed method, SITA, characterizes the timescales of neural encoding and how they are affected by the motor task, while accounting for all rate modulations.

Distant functional connectivity for bimanual finger coordination declines with aging: an fMRI and SEM exploration

Although bimanual finger coordination is known to decline with aging, it still remains unclear how exactly the neural substrates underlying the coordination differ between young and elderly adults. The present study focused on: (1) characterization of the functional connectivity within the motor association cortex which is required for successful bimanual finger coordination, and (2) to elucidate upon its age-related decline. To address these objectives, we utilized functional magnetic resonance imaging (fMRI) in combination with structural equation modeling (SEM). This allowed us to compare functional connectivity models between young and elderly age groups during a visually guided bimanual finger movement task using both stable in-phase and complex anti-phase modes. Our SEM exploration of functional connectivity revealed significant age-related differences in connections surrounding the PMd in the dominant hemisphere. In the young group who generally displayed accurate behavior, the SEM model for the anti-phase mode exhibited significant connections from the dominant PMd to the non-dominant SPL, and from the dominant PMd to the dominant S1. However, the model for the elderly group's anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions. These results suggest that: (1) the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2) the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode. The latter may underlie the elderly's decreased performance in the complex anti-phase mode of the bimanual finger movement task.

Motor cortical control of movement speed with implications for brain-machine interface control

Motor cortex plays a substantial role in driving movement, yet the details underlying this control remain unresolved. We analyzed the extent to which movement-related information could be extracted from single-trial motor cortical activity recorded while monkeys performed center-out reaching. Using information theoretic techniques, we found that single units carry relatively little speed-related information compared with direction-related information. This result is not mitigated at the population level: simultaneously recorded population activity predicted speed with significantly lower accuracy relative to direction predictions. Furthermore, a unit-dropping analysis revealed that speed accuracy would likely remain lower than direction accuracy, even given larger populations. These results suggest that the instantaneous details of single-trial movement speed are difficult to extract using commonly assumed coding schemes. This apparent paucity of speed information takes particular importance in the context of brain-machine interfaces (BMIs), which rely on extracting kinematic information from motor cortex. Previous studies have highlighted subjects' difficulties in holding a BMI cursor stable at targets. These studies, along with our finding of relatively little speed information in motor cortex, inspired a speed-dampening Kalman filter (SDKF) that automatically slows the cursor upon detecting changes in decoded movement direction. Effectively, SDKF enhances speed control by using prevalent directional signals, rather than requiring speed to be directly decoded from neural activity. SDKF improved success rates by a factor of 1.7 relative to a standard Kalman filter in a closed-loop BMI task requiring stable stops at targets. BMI systems enabling stable stops will be more effective and user-friendly when translated into clinical applications.

Cue to action processing in motor cortex populations

The primary motor cortex (MI) commands motor output after kinematics are planned from goals, thought to occur in a larger premotor network. However, there is a growing body of evidence that MI is involved in processes beyond action generation, and neuronal subpopulations may perform computations related to cue-to-action processing. From multielectrode array recordings in awake behaving Macaca mulatta monkeys, our results suggest that early MI ensemble activity during goal-directed reaches is driven by target information when cues are closely linked in time to action. Single-neuron activity spanned cue presentation to movement, with the earliest responses temporally aligned to cue and the later responses better aligned to arm movements. Population decoding revealed that MI's coding of cue direction evolved temporally, likely going from cue to action generation. We confirmed that a portion of MI activity is related to visual target processing by showing changes in MI activity related to the extinguishing of a continuously pursued visual target. These findings support a view that MI is an integral part of a cue-to-action network for immediate responses to environmental stimuli.

Motor control abnormalities in Parkinson's disease

The primary manifestations of Parkinson's disease are abnormalities of movement, including movement slowness, difficulties with gait and balance, and tremor. We know a considerable amount about the abnormalities of neuronal and muscle activity that correlate with these symptoms. Motor symptoms can also be described in terms of motor control, a level of description that explains how movement variables, such as a limb's position and speed, are controlled and coordinated. Understanding motor symptoms as motor control abnormalities means to identify how the disease disrupts normal control processes. In the case of Parkinson's disease, movement slowness, for example, would be explained by a disruption of the control processes that determine normal movement speed. Two long-term benefits of understanding the motor control basis of motor symptoms include the future design of neural prostheses to replace the function of damaged basal ganglia circuits, and the rational design of rehabilitation strategies. This type of understanding, however, remains limited, partly because of limitations in our knowledge of normal motor control. In this article, we review the concept of motor control and describe a few motor symptoms that illustrate the challenges in understanding such symptoms as motor control abnormalities.

Human sensorimotor cortex represents conflicting visuomotor mappings

Behavioral studies have shown that humans can adapt to conflicting sensorimotor mappings that cause interference after intensive training. While previous research works indicate the involvement of distinct brain regions for different types of motor learning (e.g., kinematics vs dynamics), the neural mechanisms underlying joint adaptation to conflicting mappings within the same type of perturbation (e.g., different angles of visuomotor rotation) remain unclear. To reveal the neural substrates that represent multiple sensorimotor mappings, we examined whether different mappings could be classified with multivoxel activity patterns of functional magnetic resonance imaging data. Participants simultaneously adapted to opposite rotational perturbations (+90° and - 90°) during visuomotor tracking. To dissociate differences in movement kinematics with rotation types, we used two distinct patterns of target motion and tested generalization of the classifier between different combinations of rotation and motion types. Results showed that the rotation types were classified significantly above chance using activities in the primary sensorimotor cortex and the supplementary motor area, despite no significant difference in averaged signal amplitudes within the region. In contrast, low-level sensorimotor components, including tracking error and movement speed, were best classified using activities of the early visual cortex. Our results reveal that the sensorimotor cortex represents different visuomotor mappings, which permits joint learning and switching between conflicting sensorimotor skills.

Where one hand meets the other: limb-specific and action-dependent movement plans decoded from preparatory signals in single human frontoparietal brain areas

Planning object-directed hand actions requires successful integration of the movement goal with the acting limb. Exactly where and how this sensorimotor integration occurs in the brain has been studied extensively with neurophysiological recordings in nonhuman primates, yet to date, because of limitations of non-invasive methodologies, the ability to examine the same types of planning-related signals in humans has been challenging. Here we show, using a multivoxel pattern analysis of functional MRI (fMRI) data, that the preparatory activity patterns in several frontoparietal brain regions can be used to predict both the limb used and hand action performed in an upcoming movement. Participants performed an event-related delayed movement task whereby they planned and executed grasp or reach actions with either their left or right hand toward a single target object. We found that, although the majority of frontoparietal areas represented hand actions (grasping vs reaching) for the contralateral limb, several areas additionally coded hand actions for the ipsilateral limb. Notable among these were subregions within the posterior parietal cortex (PPC), dorsal premotor cortex (PMd), ventral premotor cortex, dorsolateral prefrontal cortex, presupplementary motor area, and motor cortex, a region more traditionally implicated in contralateral movement generation. Additional analyses suggest that hand actions are represented independently of the intended limb in PPC and PMd. In addition to providing a unique mapping of limb-specific and action-dependent intention-related signals across the human cortical motor system, these findings uncover a much stronger representation of the ipsilateral limb than expected from previous fMRI findings.

Whole-body isometric force/torque measurements for functional assessment in neuro-rehabilitation: user interface and data pre-processing techniques

A diagnostic platform for the early functional assessment of post-stroke patients was designed in order to perform isometric measurements during activities of daily living (ADL) tasks. The outcome of these measurements can contribute to verify the integrity of a post-stroke existing or altered "internal model" for a particular functional task. A complete and reliable software application for the diagnostic platform was designed, developed and tested in three European hospitals. The software application was divided into two main modules: a graphical user interface (GUI) and the data pre-processing techniques for the interpretation of recorded biomedical and clinical data. This paper presents the software application associated to the platform, aimed at analysing and interpreting the huge amount of data recorded and collected during the experimental trials. Its main objective is related to validating the onset detection and data reduction. The software application presented in this paper has been working and validated with success in three different clinical centres in Europe and it can be effectively used both as assessment tool in rehabilitation and as research tool in neuroscience.

Specific interpretation of augmented feedback changes motor performance and cortical processing

It is well established that the presence of external feedback, also termed augmented feedback, can be used to improve performance of a motor task. The present study aimed to elucidate whether differential interpretation of the external feedback signal influences the time to task failure of a sustained submaximal contraction and modulates motor cortical activity. In Experiment 1, subjects had to maintain a submaximal contraction (30% of maximum force) performed with their thumb and index finger. Half of the tested subjects were always provided with feedback about joint position (pF-group), whereas the other half of the subjects were always provided with feedback about force (fF-group). Subjects in the pF-group were led to belief in half of their trials that they would receive feedback about the applied force, and subjects in the fF-group to receive feedback about the position. In both groups (fF and pF), the time to task failure was increased when subjects thought to receive feedback about the force. In Experiment 2, subthreshold transcranial magnetic stimulation was applied over the right motor cortex and revealed an increased motor cortical activity when subjects thought to receive feedback about the joint position. The results showed that the interpretation of feedback influences motor behavior and alters motor cortical activity. The current results support previous studies suggesting a distinct neural control of force and position.

Cerebellar damage diminishes long-latency responses to multijoint perturbations

Damage to the cerebellum can cause significant problems in the coordination of voluntary arm movements. One prominent idea is that incoordination stems from an inability to predictively account for the complex mechanical interactions between the arm's several joints. Motivated by growing evidence that corrective feedback control shares important capabilities and neural substrates with feedforward control, we asked whether cerebellar damage impacts feedback stabilization of the multijoint arm appropriate for the arm's intersegmental dynamics. Specifically, we tested whether cerebellar dysfunction impacts the ability of posterior deltoid to incorporate elbow motion in its long-latency response (R2 = 45-75 ms and R3 = 75-100 ms after perturbation) to an unexpected torque perturbation. Healthy and cerebellar-damaged subjects were exposed to a selected pattern of shoulder-elbow displacements to probe the response pattern from this shoulder extensor muscle. The healthy elderly subjects expressed a long-latency response linked to both shoulder and elbow motion, including an increase/decrease in shoulder extensor activity with elbow flexion/extension. Critically, cerebellar-damaged subjects displayed the normal pattern of activity in the R3 period indicating an intact ability to rapidly integrate multijoint motion appropriate to the arm's intersegmental dynamics. However, cerebellar-damaged subjects had a lower magnitude of activity that was specific to the long-latency period (both R2 and R3) and a slightly delayed onset of multijoint sensitivity. Taken together, our results suggest that the basic motor pattern of the long-latency response is housed outside the cerebellum and is scaled by processes within the cerebellum.

Simulating the cortical 3D visuomotor transformation of reach depth

We effortlessly perform reach movements to objects in different directions and depths. However, how networks of cortical neurons compute reach depth from binocular visual inputs remains largely unknown. To bridge the gap between behavior and neurophysiology, we trained a feed-forward artificial neural network to uncover potential mechanisms that might underlie the 3D transformation of reach depth. Our physiologically-inspired 4-layer network receives distributed 3D visual inputs (1^st layer) along with eye, head and vergence signals. The desired motor plan was coded in a population (3^rd layer) that we read out (4^th layer) using an optimal linear estimator. After training, our network was able to reproduce all known single-unit recording evidence on depth coding in the parietal cortex. Network analyses predict the presence of eye/head and vergence changes of depth tuning, pointing towards a gain-modulation mechanism of depth transformation. In addition, reach depth was computed directly from eye-centered (relative) visual distances, without explicit absolute depth coding. We suggest that these effects should be observable in parietal and pre-motor areas.

Time to task failure and motor cortical activity depend on the type of feedback in visuomotor tasks

The present study aimed to elucidate whether the type of feedback influences the performance and the motor cortical activity when executing identical visuomotor tasks. For this purpose, time to task failure was measured during position- and force-controlled muscular contractions. Subjects received either visual feedback about the force produced by pressing a force transducer or about the actual position between thumb and index finger. Participants were instructed to either match the force level of 30% MVC or the finger position corresponding to the thumb and index finger angle at this contraction intensity. Subjects demonstrated a shorter time to task failure when they were provided with feedback about their joint position (11.5±6.2 min) instead of force feedback (19.2±12.8 min; P = 0.01). To test differences in motor cortical activity between position- and force-controlled contractions, subthreshold transcranial magnetic stimulation (subTMS) was applied while executing submaximal (20% MVC) contractions. SubTMS resulted in a suppression of the first dorsal interosseus muscle (FDI) EMG in both tasks. However, the mean suppression for the position-controlled task was significantly greater (18.6±9.4% vs. 13.3±7.5%; P = 0.025) and lasted longer (13.9±7.5 ms vs. 9.3±4.3 ms; P = 0.024) compared to the force-controlled task. The FDI background EMG obtained without stimulation was comparable in all conditions. The present results demonstrate that the presentation of different feedback modalities influences the time to task failure as well as the cortical activity. As only the feedback was altered but not the mechanics of the task, the present results add to the body of evidence that suggests that the central nervous system processes force and position information in different ways.

Three-dimensional transformations for goal-directed action

Much of the central nervous system is involved in visuomotor transformations for goal-directed gaze and reach movements. These transformations are often described in terms of stimulus location, gaze fixation, and reach endpoints, as viewed through the lens of translational geometry. Here, we argue that the intrinsic (primarily rotational) 3-D geometry of the eye-head-reach systems determines the spatial relationship between extrinsic goals and effector commands, and therefore the required transformations. This approach provides a common theoretical framework for understanding both gaze and reach control. Combined with an assessment of the behavioral, neurophysiological, imaging, and neuropsychological literature, this framework leads us to conclude that (a) the internal representation and updating of visual goals are dominated by gaze-centered mechanisms, but (b) these representations must then be transformed as a function of eye and head orientation signals into effector-specific 3-D movement commands.

Vibrissae motor cortex unit activity during whisking

Rats generate stereotyped exploratory (5-12 Hz) vibrissa movements when navigating through their environment. Like other rhythmic behaviors, the production of whisking relies on a subcortical pattern generator. However, the relatively large vibrissae representation in motor cortex (vMCx) suggests that cortex also contributes to the control of whisker movements. The goal of this study was to examine the relationship between neuronal activity in vMCx and the kinematics of vibrissae movements. We recorded multiunit activity (MUA) and single units in the rhythmic region of vMCx while measuring vibrissa position in awake, head-restrained rats. The rats were engaged in one of two behavioral tasks where they were rewarded for either 1) producing noncontact whisking epochs that met specified criteria (epochs ≥4 Hz, whisks >5 mm) or 2) whisking to contact an object. There was significant coherence between the frequency of MUA and vibrissae movements during free-air whisking but not when animals were using their vibrissae to contact an object. Spike rate in vMCx was most frequently correlated with the amplitude of vibrissa movements; correlations with movement frequency did not exceed chance levels. These findings suggest that the specific parameter under cortical control may be the amplitude of whisker movements.

Primary motor cortex underlies multi-joint integration for fast feedback control

A basic difficulty for the nervous system is integrating locally ambiguous sensory information to form accurate perceptions about the outside world^1–4. This local-to-global problem is also fundamental to motor control of the arm since complex mechanical interactions between the shoulder and elbow allow a particular amount of motion at one joint to arise from an infinite combination of shoulder and elbow torques⁵ (Fig. 1a). Here we show that a transcortical pathway through primary motor cortex (M1) resolves this ambiguity during fast feedback control. We demonstrate that single M1 neurons of behaving monkeys can integrate shoulder and elbow motion information into motor commands which appropriately counter the underlying torque within ~50 ms of a mechanical perturbation. Moreover, we reveal a causal link between M1 processing and multi-joint integration in humans by showing that shoulder muscle responses occurring ~50 ms after pure elbow displacement can be potentiated by transcranial magnetic stimulation. Our results show that M1 underlies multi-joint integration during fast feedback control, demonstrating that transcortical processing permits feedback responses to express a level of sophistication previously reserved for voluntary control and providing neurophysiological support for influential theories positing that voluntary movement is generated by the intelligent manipulation of sensory feedback^6,7.

Inference from populations: going beyond models

How are abstract signals, like intent, represented in neural populations? By creating a direct link between neural activity and behavior, brain-computer interfaces (BCIs) can help answer this question. Early instantiations of these devices sought mainly to mimic arm movements: by building models of arm tuning for the neurons, desired arm movements could be read out and used to control various prosthetic devices. However, as the functionality of these devices increases, a more general approach that relies less on endogenous control signals may be required. Here we review some of the current, model-based approaches for finding volitional control signals for spiking-based BCIs, and present some new approaches for finding control signals without resorting to parametric models of neural activity.

Latent inputs improve estimates of neural encoding in motor cortex

Typically, tuning curves in motor cortex are constructed by fitting the firing rate of a neuron as a function of some observed action, such as arm direction or movement speed. These tuning curves are then often interpreted causally as representing the firing rate as a function of the desired movement, or intent. This interpretation implicitly assumes that the motor command and the motor act are equivalent. However, any kind of perturbation, be it external, such as a visuomotor rotation, or internal, such as muscle fatigue, can create a difference between the motor intent and the action. How do we estimate the tuning curve under these conditions? Furthermore, it is well known that, during learning or adaptation, the relationship between neural firing and the observed movement can change. Does this change indicate a change in the inputs to the population, or a change in the way those inputs are processed? In this work, we present a method to infer the latent, unobserved inputs into the population of recorded neurons. Using data from nonhuman primates performing brain-computer interface experiments, we show that tuning curves based on these latent directions fit better than tuning curves based on actual movements. Finally, using data from a brain-computer interface learning experiment in which half of the units were decoded incorrectly, we demonstrate how this method might differentiate various aspects of motor adaptation.

Increased sensorimotor network activity in DYT1 dystonia: a functional imaging study

Neurophysiological studies have provided evidence of primary motor cortex hyperexcitability in primary dystonia, but several functional imaging studies suggest otherwise. To address this issue, we measured sensorimotor activation at both the regional and network levels in carriers of the DYT1 dystonia mutation and in control subjects. We used (15)Oxygen-labelled water and positron emission tomography to scan nine manifesting DYT1 carriers, 10 non-manifesting DYT1 carriers and 12 age-matched controls while they performed a kinematically controlled motor task; they were also scanned in a non-motor audio-visual control condition. Within- and between-group contrasts were analysed with statistical parametric mapping. For network analysis, we first identified a normal motor-related activation pattern in a set of 39 motor and audio-visual scans acquired in an independent cohort of 18 healthy volunteer subjects. The expression of this pattern was prospectively quantified in the motor and control scans acquired in each of the gene carriers and controls. Network values for the three groups were compared with ANOVA and post hoc contrasts. Voxel-wise comparison of DYT1 carriers and controls revealed abnormally increased motor activation responses in the former group (P < 0.05, corrected; statistical parametric mapping), localized to the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and the inferior parietal cortex. Network analysis of the normative derivation cohort revealed a significant normal motor-related activation pattern topography (P < 0.0001) characterized by covarying neural activity in the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and cerebellum. In the study cohort, normal motor-related activation pattern expression measured during movement was abnormally elevated in the manifesting gene carriers (P < 0.001) but not in their non-manifesting counterparts. In contrast, in the non-motor control condition, abnormal increases in network activity were present in both groups of gene carriers (P < 0.001). In this condition, normal motor-related activation pattern expression in non-manifesting carriers was greater than in controls, but lower than in affected carriers. In the latter group, measures of normal motor-related activation pattern expression in the audio-visual condition correlated with independent dystonia clinical ratings (r = 0.70, P = 0.04). These findings confirm that overexcitability of the sensorimotor system is a robust feature of dystonia. The presence of elevated normal motor-related activation pattern expression in the non-motor condition suggests that abnormal integration of audio-visual input with sensorimotor network activity is an important trait feature of this disorder. Lastly, quantification of normal motor-related activation pattern expression in individual cases may have utility as an objective descriptor of therapeutic response in trials of new treatments for dystonia and related disorders.

Low-dimensional neural features predict muscle EMG signals

Understanding the relationship between neural activity in motor cortex and muscle activity during movements is important both for basic science and for the design of neural prostheses. While there has been significant work in decoding muscle EMG from neural data, decoders often require many parameters which make the analysis susceptible to overfitting, which reduces generalizability and makes the results difficult to interpret. To address this issue, we recorded simultaneous neural activity from the motor cortices (M1/PMd) of rhesus monkeys performing an arm-reaching task while recording EMG from arm muscles. In this work, we focused on relating the mean neural activity (averaged across reach trials to one target) to the corresponding mean EMG. We reduced the dimensionality of the neural data and found that the curvature of the low-dimensional (low-D) neural activity could be used as a signature of muscle activity. Using this signature, and without directly fitting EMG data to the neural activity, we derived neural axes based on reaches to only one reach target (< 5% of the data) that could explain EMG for reaches across multiple targets (average R(2) = 0.65). Our results suggest that cortical population activity is tightly related to muscle EMG measurements, predicting a lag between cortical activity and movement generation of 47.5 ms. Furthermore, our ability to predict EMG features across different movements suggests that there are fundamental axes or directions in the low-D neural space along which the neural population activity moves to activate particular muscles.

Long-Latency Responses During Reaching Account for the Mechanical Interaction Between the Shoulder and Elbow Joints

Although considerable research indicates that reaching movements rely on knowledge of the arm's mechanical properties and environment to anticipate and counter predictable loads, far less research has examined whether this degree of sophistication is present for on-line corrections during reaching. Here we examine the R2/3 response to mechanical perturbations (45–100 ms, also called the long-latency reflex), which is highly flexible and includes the fastest possible contribution from primary motor cortex, a key neural substrate for self-initiated action. Torque perturbations were occasionally and unexpectedly applied to the subject's shoulder and/or elbow in the course of performing reaching movements. Critically, these perturbations would evoke different patterns of feedback corrections from a shoulder extensor muscle if it countered only the local shoulder displacement relative to unperturbed motion or accounted for the mechanical interactions between the shoulder and elbow joints and countered the underlying shoulder torque. Our results show that the earliest response (R1: 20–45 ms) reflected local shoulder displacement, whereas the R2/3 response (45–100 ms) reflected knowledge of multijoint dynamics. Moreover, the same pattern of feedback occurred whether the shoulder muscle helped initiate the movement (during its agonist phase) or helped terminate the movement (during its antagonist phase). These results contribute to the accumulating evidence that highly sophisticated feedback control underlies motor behavior and are consistent with a shared neural substrate, such as primary motor cortex, for feedforward and feedback control.

Optimal Integration of Gravity in Trajectory Planning of Vertical Pointing Movements

The planning and control of motor actions requires knowledge of the dynamics of the controlled limb to generate the appropriate muscular commands and achieve the desired goal. Such planning and control imply that the CNS must be able to deal with forces and constraints acting on the limb, such as the omnipresent force of gravity. The present study investigates the effect of hypergravity induced by parabolic flights on the trajectory of vertical pointing movements to test the hypothesis that motor commands are optimized with respect to the effect of gravity on the limb. Subjects performed vertical pointing movements in normal gravity and hypergravity. We use a model based on optimal control to identify the role played by gravity in the optimal arm trajectory with minimal motor costs. First, the simulations in normal gravity reproduce the asymmetry in the velocity profiles (the velocity reaches its maximum before half of the movement duration), which typically characterizes the vertical pointing movements performed on Earth, whereas the horizontal movements present symmetrical velocity profiles. Second, according to the simulations, the optimal trajectory in hypergravity should present an increase in the peak acceleration and peak velocity despite the increase in the arm weight. In agreement with these predictions, the subjects performed faster movements in hypergravity with significant increases in the peak acceleration and peak velocity, which were accompanied by a significant decrease in the movement duration. This suggests that movement kinematics change in response to an increase in gravity, which is consistent with the hypothesis that motor commands are optimized and the action of gravity on the limb is taken into account. The results provide evidence for an internal representation of gravity in the central planning process and further suggest that an adaptation to altered dynamics can be understood as a reoptimization process.

Exploiting multiple sensory modalities in brain-machine interfaces

Recent improvements in cortically-controlled brain-machine interfaces (BMIs) have raised hopes that such technologies may improve the quality of life of severely motor-disabled patients. However, current generation BMIs do not perform up to their potential due to the neglect of the full range of sensory feedback in their strategies for training and control. Here we confirm that neurons in the primary motor cortex (MI) encode sensory information and demonstrate a significant heterogeneity in their responses with respect to the type of sensory modality available to the subject about a reaching task. We further show using mutual information and directional tuning analyses that the presence of multi-sensory feedback (i.e. vision and proprioception) during replay of movements evokes neural responses in MI that are almost indistinguishable from those responses measured during overt movement. Finally, we suggest how these playback-evoked responses may be used to improve BMI performance.