Interchangeable Role of Motor Cortex and Reafference for the Stable Execution of an Orofacial Action.

Animals interact with their environment through mechanically active, mobile sensors. The efficient use of these sensory organs implies the ability to track their position; otherwise, perceptual stability or prehension would be profoundly impeded. The nervous system may keep track of the position of a sensorimotor organ via two complementary feedback mechanisms-peripheral reafference (external, sensory feedback) and efference copy (internal feedback). Yet, the potential contributions of these mechanisms remain largely unexplored. By training male rats to place one of their vibrissae within a predetermined angular range without contact, a task that depends on knowledge of vibrissa position relative to their face, we found that peripheral reafference is not required. The presence of motor cortex is not required either, except in the absence of peripheral reafference to maintain motor stability. Finally, the red nucleus, which receives descending inputs from motor cortex and cerebellum and projects to facial motoneurons, is critically involved in the execution of the vibrissa positioning task. All told, our results point toward the existence of an internal model that requires either peripheral reafference or motor cortex to optimally drive voluntary motion.SIGNIFICANCE STATEMENT How does an animal know where a mechanically active, mobile sensor lies relative to its body? We address this basic question in sensorimotor integration using the motion of the vibrissae in rats. We show that rats can learn to reliably position their vibrissae in the absence of sensory feedback or in the absence of motor cortex. Yet, when both sensory feedback and motor cortex are absent, motor precision is degraded. This suggests the existence of an internal model able to operate in closed- and open-loop modes, requiring either motor cortex or sensory feedback to maintain motor stability.

A Wireless Electro-Optic Platform for Multimodal Electrophysiology and Optogenetics in Freely Moving Rodents.

This paper presents the design and the utilization of a wireless electro-optic platform to perform simultaneous multimodal electrophysiological recordings and optogenetic stimulation in freely moving rodents. The developed system can capture neural action potentials (AP), local field potentials (LFP) and electromyography (EMG) signals with up to 32 channels in parallel while providing four optical stimulation channels. The platform is using commercial off-the-shelf components (COTS) and a low-power digital field-programmable gate array (FPGA), to perform digital signal processing to digitally separate in real time the AP, LFP and EMG while performing signal detection and compression for mitigating wireless bandwidth and power consumption limitations. The different signal modalities collected on the 32 channels are time-multiplexed into a single data stream to decrease power consumption and optimize resource utilization. The data reduction strategy is based on signal processing and real-time data compression. Digital filtering, signal detection, and wavelet data compression are used inside the platform to separate the different electrophysiological signal modalities, namely the local field potentials (1-500 Hz), EMG (30-500 Hz), and the action potentials (300-5,000 Hz) and perform data reduction before transmitting the data. The platform achieves a measured data reduction ratio of 7.77 (for a firing rate of 50 AP/second) and weights 4.7 g with a 100-mAh battery, an on/off switch and a protective plastic enclosure. To validate the performance of the platform, we measured distinct electrophysiology signals and performed optogenetics stimulation in vivo in freely moving rondents. We recorded AP and LFP signals with the platform using a 16-microelectrode array implanted in the primary motor cortex of a Long Evans rat, both in anesthetized and freely moving conditions. EMG responses to optogenetic Channelrhodopsin-2 induced activation of motor cortex via optical fiber were also recorded in freely moving rodents.

Neurostimulation for Stroke Rehabilitation.

Neurological injuries such as strokes can lead to important loss in motor function. Thanks to neuronal plasticity, some of the lost functionality may be recovered over time. However, the recovery process is often slow and incomplete, despite the most effective conventional rehabilitation therapies. As we improve our understanding of the rules governing activity-dependent plasticity, neuromodulation interventions are being developed to harness neural plasticity to achieve faster and more complete recovery. Here, we review the principles underlying stimulation-driven plasticity as well as the most commonly used stimulation techniques and approaches. We argue that increased spatiotemporal precision is an important factor to improve the efficacy of neurostimulation and drive a more useful neuronal reorganization. Consequently, closed-loop systems and optogenetic stimulation hold theoretical promise as interventions to promote brain repair after stroke.

Assessment of Corticospinal Excitability in Awake Rodents Using EMG-Controlled Intracortical Stimulation.

Assessment of corticospinal excitability (CSE) is an essential component of experiments designed to induce or study neuronal plasticity in the motor system. Common examples are paired associative stimulation (PAS), theta-burst stimulation (TBS), intensive motor training, or any methods aimed at potentiating the corticomotor system in the hope of promoting better recovery after neurological insult. To date, rodent models of CSE assessment have mostly been completed under anaesthesia, which greatly affects the level of CSE, as well as the mechanisms of plasticity. Experiments in awake animals are difficult because the ongoing state of behavior affects the excitability of the motor system and complicates the assessment of CSE. To address this issue, we have designed a novel approach for CSE assessment in awake behaving rodents, enabling a reliable measure of evoked motor responses obtained from cortical microstimulation in repeatable conditions of ongoing motor activity. The system relies on chronically implanted intracortical and intramuscular electrodes and a custom-made software control system, enabling the user to require that precise parameters of EMG activity be met before cortical stimulation probes are delivered. This approach could be used for further studies of PAS, TBS or other interventions requiring the assessment of CSE under repeatable conditions. We provide fabrication schematics and a list of materials for the implant, as well as instructions for running a custom-made MATLAB codebase, customizing the PAS protocol, and performing the complete analysis of experimental data. We hope these tools can further facilitate animal research in the field of neuroplasticity and neurorehabilitation.

Paired Associative Stimulation Fails to Induce Plasticity in Freely Behaving Intact Rats.

Paired associative stimulation (PAS) has been explored in humans as a noninvasive tool to drive plasticity and promote recovery after neurologic insult. A more thorough understanding of PAS-induced plasticity is needed to fully harness it as a clinical tool. Here, we tested the efficacy of PAS with multiple interstimulus intervals in an awake rat model to study the principles of associative plasticity. Using chronically implanted electrodes in motor cortex and forelimb, we explored PAS parameters to effectively drive plasticity. We assessed changes in corticomotor excitability using a closed-loop, EMG-controlled cortical stimulation paradigm. We tested 11 PAS intervals, chosen to force the coincidence of neuronal activity in the motor cortex and spinal cord of rats with timings relevant to the principles of Hebbian spike timing-dependent plasticity. However, despite a relatively large number of stimulus pairings (300), none of the tested intervals reliably changed corticospinal excitability relative to control conditions. Our results question PAS effectiveness under these conditions.

Impaired Motor Learning Following a Pain Episode in Intact Rats.

Motor learning and pain are important factors influencing rehabilitation. Despite being mostly studied independently from each other, important interactions exist between them in the context of spinal cord injury, whether to the spinal cord or the body. Ongoing or recent past episodes of nociceptive activity can prevent motor learning in spinalized rats. In intact animals, it has been proposed that supraspinal activity could counter the repressive effect of nociception on motor system plasticity, but this has not yet been verified in behavioral conditions. The aim of this study was to test whether a recent episode of nociception affects subsequent motor learning in intact animals. We trained rodents to walk on a custom-made horizontal ladder. After initial training, the rats underwent a week-long rest, during which they were randomly assigned to a control group, or one out of two pain conditions. Nociceptive stimuli of different durations were induced through capsaicin or Complete Freund's Adjuvant injections and timed so that the mechanical hypersensitivity had entirely subsided by the end of the resting period. Training then resumed on a modified version of the horizontal ladder. We evaluated the animals' ability to adapt to the modified task by measuring their transit time and paw misplacements over 4 days. Our results show that prior pain episodes do affect motor learning in neurologically intact rats. Motor learning deficits also seem to be influenced by the duration of the pain episode. Rats receiving a subcutaneous injection of capsaicin displayed immediate signs of mechanical hypersensitivity, which subsided rapidly. Nonetheless, they still showed learning deficits 24 h after injection. Rats who received a Complete Freund's Adjuvant injection displayed mechanical hypersensitivity for up to 7 days during the resting period. When trained on the modified ladder task upon returning to normal sensitivity levels, these rats exhibited more prolonged motor learning deficits, extending over 3 days. Our results suggest that prior pain episodes can negatively influence motor learning, and that the duration of the impairment relates to the duration of the pain episode. Our results highlight the importance of addressing pain together with motor training after injury.

A Wireless Electro-Optic Headstage With a 0.13- µm CMOS Custom Integrated DWT Neural Signal Decoder for Closed-Loop Optogenetics.

We present a wireless electro-optic headstage that uses a 0.13- µm CMOS custom integrated circuit (IC) implementing a digital neural decoder (ND-IC) for enabling real-time closed-loop (CL) optogenetics. The ND-IC processes the neural activity data using three digital cores: 1) the detector core detects and extracts the action potential (AP) of individual neurons by using an adaptive threshold; 2) the data compression core compresses the detected AP by using an efficient Symmlet-2 discrete wavelet transform (DWT) processor for decreasing the amount of data to be transmitted by the low-power wireless link; and 3) the classification core sorts the compressed AP into separated clusters on the fly according to their wave shapes. The ND-IC encompasses several innovations: 1) the compression core decreases the complexity from O(n 2) to O(n · log(n)) compared to the previous solutions, while using two times less memory, thanks to the use of a new coefficient sorting tree; and 2) the AP classification core reuses both the compressed DWT coefficients to perform implicit dimensionality reduction, which allows for performing intensive signal processing on-chip, while increasing power and hardware efficiency. This core also reuses the signal standard deviation already computed by the AP detector core as threshold for performing automatic AP sorting. The headstage also introduces innovations by enabling a new wireless CL scheme between the neural data acquisition module and the optical stimulator. Our CL scheme uses the AP sorting and timing information produced by the ND-IC for detecting complex firing patterns within the brain. The headstage is also smaller (1.13 cm 3), lighter (3.0 g with a 40 mAh battery) and less invasive than the previous solutions, while providing a measured autonomy of 2h40, with the ND-IC. The whole system and the ND-IC are first validated in vivo in the LD thalamus of a Long-Evans rat, and then in freely-moving CL experiments involving a mouse virally expressing ChR2-mCherry in inhibitory neurons of the prelimbic cortex, and the results show that our system works well within an in vivo experimental setting with a freely moving mouse.

Cortical population activity within a preserved neural manifold underlies multiple motor behaviors.

Populations of cortical neurons flexibly perform different functions; for the primary motor cortex (M1) this means a rich repertoire of motor behaviors. We investigate the flexibility of M1 movement control by analyzing neural population activity during a variety of skilled wrist and reach-to-grasp tasks. We compare across tasks the neural modes that capture dominant neural covariance patterns during each task. While each task requires different patterns of muscle and single unit activity, we find unexpected similarities at the neural population level: the structure and activity of the neural modes is largely preserved across tasks. Furthermore, we find two sets of neural modes with task-independent activity that capture, respectively, generic temporal features of the set of tasks and a task-independent mapping onto muscle activity. This system of flexibly combined, well-preserved neural modes may underlie the ability of M1 to learn and generate a wide-ranging behavioral repertoire.

Adaptive neuron-to-EMG decoder training for FES neuroprostheses.

OBJECTIVE: We have previously demonstrated a brain-machine interface neuroprosthetic system that provided continuous control of functional electrical stimulation (FES) and restoration of grasp in a primate model of spinal cord injury (SCI). Predicting intended EMG directly from cortical recordings provides a flexible high-dimensional control signal for FES. However, no peripheral signal such as force or EMG is available for training EMG decoders in paralyzed individuals. APPROACH: Here we present a method for training an EMG decoder in the absence of muscle activity recordings; the decoder relies on mapping behaviorally relevant cortical activity to the inferred EMG activity underlying an intended action. Monkeys were trained at a 2D isometric wrist force task to control a computer cursor by applying force in the flexion, extension, ulnar, and radial directions and execute a center-out task. We used a generic muscle force-to-endpoint force model based on muscle pulling directions to relate each target force to an optimal EMG pattern that attained the target force while minimizing overall muscle activity. We trained EMG decoders during the target hold periods using a gradient descent algorithm that compared EMG predictions to optimal EMG patterns. MAIN RESULTS: We tested this method both offline and online. We quantified both the accuracy of offline force predictions and the ability of a monkey to use these real-time force predictions for closed-loop cursor control. We compared both offline and online results to those obtained with several other direct force decoders, including an optimal decoder computed from concurrently measured neural and force signals. SIGNIFICANCE: This novel approach to training an adaptive EMG decoder could make a brain-control FES neuroprosthesis an effective tool to restore the hand function of paralyzed individuals. Clinical implementation would make use of individualized EMG-to-force models. Broad generalization could be achieved by including data from multiple grasping tasks in the training of the neuron-to-EMG decoder. Our approach would make it possible for persons with SCI to grasp objects with their own hands, using near-normal motor intent.

Comparing offline decoding performance in physiologically defined neuronal classes.

OBJECTIVE: Recently, several studies have documented the presence of a bimodal distribution of spike waveform widths in primary motor cortex. Although narrow and wide spiking neurons, corresponding to the two modes of the distribution, exhibit different response properties, it remains unknown if these differences give rise to differential decoding performance between these two classes of cells. APPROACH: We used a Gaussian mixture model to classify neurons into narrow and wide physiological classes. Using similar-size, random samples of neurons from these two physiological classes, we trained offline decoding models to predict a variety of movement features. We compared offline decoding performance between these two physiologically defined populations of cells. MAIN RESULTS: We found that narrow spiking neural ensembles decode motor parameters better than wide spiking neural ensembles including kinematics, kinetics, and muscle activity. SIGNIFICANCE: These findings suggest that the utility of neural ensembles in brain machine interfaces may be predicted from their spike waveform widths.

Brain-controlled muscle stimulation for the restoration of motor function.

Loss of the ability to move, as a consequence of spinal cord injury or neuromuscular disorder, has devastating consequences for the paralyzed individual, and great economic consequences for society. Functional electrical stimulation (FES) offers one means to restore some mobility to these individuals, improving not only their autonomy, but potentially their general health and well-being as well. FES uses electrical stimulation to cause the paralyzed muscles to contract. Existing clinical systems require the stimulation to be preprogrammed, with the patient typically using residual voluntary movement of another body part to trigger and control the patterned stimulation. The rapid development of neural interfacing in the past decade offers the promise of dramatically improved control for these patients, potentially allowing continuous control of FES through signals recorded from motor cortex, as the patient attempts to control the paralyzed body part. While application of these 'brain-machine interfaces' (BMIs) has undergone dramatic development for control of computer cursors and even robotic limbs, their use as an interface for FES has been much more limited. In this review, we consider both FES and BMI technologies and discuss the prospect for combining the two to provide important new options for paralyzed individuals.

On the functional organization and operational principles of the motor cortex.

Recent studies on the functional organization and operational principles of the motor cortex (MCx), taken together, strongly support the notion that the MCx controls the muscle synergies subserving movements in an integrated manner. For example, during pointing the shoulder, elbow and wrist muscles appear to be controlled as a coupled functional system, rather than singly and separately. The recurrent pattern of intrinsic synaptic connections between motor cortical points is likely part of the explanation for this operational principle. So too is the reduplicated, non-contiguous and intermingled representation of muscles in the MCx. A key question addressed in this article is whether the selection of movement related muscle synergies is a dynamic process involving the moment to moment functional linking of a variety of motor cortical points, or rather the selection of fixed patterns embedded in the MCx circuitry. It will be suggested that both operational principles are probably involved. We also discuss the neural mechanisms by which cortical points may be dynamically linked to synthesize movement related muscle synergies. Separate corticospinal outputs sum linearly and lead to a blending of the movements evoked by activation of each point on its own. This operational principle may simplify the synthesis of motor commands. We will discuss two possible mechanisms that may explain linear summation of outputs. We have observed that the final posture of the arm when pointing to a given spatial location is relatively independent of its starting posture. From this observation and the recurrent nature of the MCx intrinsic connectivity we hypothesize that the basic mode of operation of the MCx is to associate spatial location to final arm posture. We explain how the recurrent network connectivity operates to generate the muscle activation patterns (synergies) required to move the arm and hold it in its final position.

Intrafascicular stimulation of monkey arm nerves evokes coordinated grasp and sensory responses.

High-count microelectrode arrays implanted in peripheral nerves could restore motor function after spinal cord injury or sensory function after limb loss. In this study, we implanted Utah Slanted Electrode Arrays (USEAs) intrafascicularly at the elbow or shoulder in arm nerves of rhesus monkeys (n = 4) under isoflurane anesthesia. Input-output curves indicated that pulse-width-modulated single-electrode stimulation in each arm nerve could recruit single muscles with little or no recruitment of other muscles. Stimulus trains evoked specific, natural, hand movements, which could be combined via multielectrode stimulation to elicit coordinated power or pinch grasp. Stimulation also elicited short-latency evoked potentials (EPs) in primary somatosensory cortex, which might be used to provide sensory feedback from a prosthetic limb. These results demonstrate a high-resolution, high-channel-count interface to the peripheral nervous system for restoring hand function after neural injury or disruption or for examining nerve structure.

Movement representation in the primary motor cortex and its contribution to generalizable EMG predictions.

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

Local field potentials allow accurate decoding of muscle activity.

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

EMG prediction from motor cortical recordings via a nonnegative point-process filter.

A constrained point-process filtering mechanism for prediction of electromyogram (EMG) signals from multichannel neural spike recordings is proposed here. Filters from the Kalman family are inherently suboptimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train observations by using a generalized linear model that encapsulates covariates of neural activity, including the neurons' own spiking history, concurrent ensemble activity, and extrinsic covariates (EMG signals). In order to predict the envelopes of EMGs, we reformulated the Kalman filter in an optimization framework and utilized a nonnegativity constraint. This structure characterizes the nonlinear correspondence between neural activity and EMG signals reasonably. The EMGs were recorded from 12 forearm and hand muscles of a behaving monkey during a grip-force task. In the case of limited training data, the constrained point-process filter improved the prediction accuracy when compared to a conventional Wiener cascade filter (a linear causal filter followed by a static nonlinearity) for different bin sizes and delays between input spikes and EMG output. For longer training datasets, results of the proposed filter and that of the Wiener cascade filter were comparable.

Electrical conduction block in large nerves: high-frequency current delivery in the nonhuman primate.

Recent studies have made significant progress toward the clinical implementation of high-frequency conduction block (HFB) of peripheral nerves. However, these studies were performed in small nerves, and questions remain regarding the nature of HFB in large-diameter nerves. This study in nonhuman primates shows reliable conduction block in large-diameter nerves (up to 4.1 mm) with relatively low-threshold current amplitude and only moderate nerve discharge prior to the onset of block.

Neural mechanism of activity spread in the cat motor cortex and its relation to the intrinsic connectivity.

Motor cortical points are linked by intrinsic horizontal connections having a recurrent network topology. However, it is not known whether neural activity can propagate over the area covered by these intrinsic connections and whether there are spatial anisotropies of synaptic strength, as opposed to synaptic density. Moreover, the mechanisms by which activity spreads have yet to be determined. To address these issues, an 8 × 8 microelectrode array was inserted in the forelimb area of the cat motor cortex (MCx). The centre of the array had a laser etched hole ∼500 µm in diameter. A microiontophoretic pipette, with a tip diameter of 2-3 µm, containing bicuculline methiodide (BIC) was inserted in the hole and driven to a depth of 1200-1400 µm from the cortical surface. BIC was ejected for ∼2min from the tip of the micropipette with positive direct current ranging between 20 and 40 nA in different experiments. This produced spontaneous nearly periodic bursts (0.2-1.0 Hz) of multi-unit activity in a radius of about 400 µm from the tip of the micropipette. The bursts of neural activity spread at a velocity of 0.11-0.24 ms⁻¹ (mean=0.14 mm ms⁻¹, SD=0.05)with decreasing amplitude.The area activated was on average 7.22 mm² (SD=0.91 mm²), or ∼92% of the area covered by the recording array. The mode of propagation was determined to occur by progressive recruitment of cortical territory, driven by a central locus of activity of some 400 µm in radius. Thus, activity did not propagate as a wave. Transection of the connections between the thalamus and MCx did not significantly alter the propagation velocity or the size of the recruited area, demonstrating that the bursts spread along the routes of intrinsic cortical connectivity. These experiments demonstrate that neural activity initiated within a small motor cortical locus (≤ 400 µm in radius) can recruit a relatively large neighbourhood in which a variety of muscles acting at several forelimb joints are represented. These results support the hypothesis that the MCx controls the forelimb musculature in an integrated and anticipatory manner based on a recurrent network topology

On the nature of the intrinsic connectivity of the cat motor cortex: evidence for a recurrent neural network topology.

The details and functional significance of the intrinsic horizontal connections between neurons in the motor cortex (MCx) remain to be clarified. To further elucidate the nature of this intracortical connectivity pattern, experiments were done on the MCx of three cats. The anterograde tracer biocytin was ejected iontophoretically in layers II, III, and V. Some 30-50 neurons within a radius of approximately 250 microm were thus stained. The functional output of the motor cortical point at which biocytin was injected, and of the surrounding points, was identified by microstimulation and electromyographic recordings. The axonal arborizations of the stained neurons were traced under camera lucida. The axon collaterals were extensive, reaching distances of

Corticospinal control of antagonistic muscles in the cat.

We recently suggested that movement-related inter-joint muscle synergies are recruited by selected excitation and selected release from inhibition of cortical points. Here we asked whether a similar cortical mechanism operates in the functional linking of antagonistic muscles. To this end experiments were done on ketamine-anesthetized cats. Intracortical microstimulation (ICMS) and intramuscular electromyographic recordings were used to find and characterize wrist, elbow and shoulder antagonistic motor cortical points. Simultaneous ICMS applied at two cortical points, each evoking activity in one of a pair of antagonistic muscles, produced co-contraction of antagonistic muscle pairs. However, we found an obvious asymmetry in the strength of reciprocal inhibition; it was always significantly stronger on physiological extensors than flexors. Following intravenous injection of a single bolus of strychnine, a cortical point at which only a physiological flexor was previously activated also elicited simultaneous activation of its antagonist. This demonstrates that antagonistic corticospinal neurons are closely grouped, or intermingled. To test whether releasing a cortical point from inhibition allows it to be functionally linked with an antagonistic cortical point, one of three GABA(A) receptor antagonists, bicuculline, gabazine or picrotoxin, was injected iontophoretically at one cortical point while stimulation was applied to an antagonistic cortical point. This coupling always resulted in co-contraction of the represented antagonistic muscles. Thus, antagonistic motor cortical points are linked by excitatory intracortical connections held in check by local GABAergic inhibition, with reciprocal inhibition occurring at the spinal level. Importantly, the asymmetry of cortically mediated reciprocal inhibition would appear significantly to bias muscle maps obtained by ICMS in favor of physiological flexors.