Patients with spinal cord injury lack the connections between brain and spinal cord circuits essential for voluntary movement. Clinical systems that achieve muscle contraction through functional electrical stimulation (FES) have proven to be effective in allowing patients with tetraplegia to regain control of hand movement and to achieve a greater measure of independence in activities of daily living 1,2. In typical systems, the patient uses residual proximal limb movements to trigger pre-programmed stimulation that causes the paralyzed muscles to contract, allowing use of one or two basic grasps. Instead, we have developed, in primates, an FES system that is controlled by recordings made from microelectrodes permanently implanted in the brain. We simulated some of the effects of the paralysis caused by C5-C6 spinal cord injury 3 by injecting a local anesthetic to block the median and ulnar nerves at the elbow. Then, using recordings from approximately 100 neurons in the motor cortex, we predicted the intended activity of several of the paralyzed muscles, and used these predictions to control the intensity of stimulation of the same muscles. This process essentially bypassed the spinal cord, restoring to the monkeys voluntary control of their paralyzed muscles. This achievement represents a major advance toward similar restoration of hand function in human patients through brain-controlled FES. We anticipate that in human patients, this neuroprosthesis would allow much more flexible and dexterous use of the hand than is possible with existing FES systems.

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.

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.

Recruitment of movement-related muscle synergies involves the functional linking of motor cortical points. We asked how the outputs of two simultaneously stimulated motor cortical points would interact. To this end, experiments were done in ketamine-anesthetized cats. When prolonged (e.g., 500 ms) trains of intracortical microstimulation were applied in the primary motor cortex, stimulus currents as low as 10 -20 A evoked coordinated movements of the contralateral forelimb. Paw kinematics in three dimensions and the electromyographic (EMG) activity of eight muscles were simultaneously recorded. We show that the EMG outputs of two cortical points simultaneously stimulated are additive. The movements were represented as displacement vectors pointing from initial to final paw position. The displacement vectors resulting from simultaneous stimulation of two cortical points pointed in nearly the same direction as the algebraic resultant vector. Linear summation of outputs was also found when inhibition at one of the cortical points was reduced by GABA A receptor antagonists. A simple principle emerges from these results. Notwithstanding the underlying complex neuronal circuitry, motor cortex outputs combine nearly linearly in terms of movement direction and muscle activation patterns. Importantly, simultaneous activation does not change the nature of the output at each point. An additional implication is that not all possible movements need be explicitly represented in the motor cortex; a large number of different movements may be synthesized from a smaller repertoire.

The purpose of this study was to determine the relative size and location of proximal and distal upper limb muscle representations in the human motor cortex. Motor-evoked potentials (MEPs) evoked by transcranial magnetic stimulation were recorded in the proximal muscle anterior deltoid (AD) and in the distal muscles extensor carpi radialis (ECR) and first dorsal interosseus (1DI). The coil was moved in steps of 1 cm along a grid drawn on a tight-fitting polyester cap placed on the subject's head. At each location, four stimuli were delivered at 1.2 times the active motor threshold (AMT), and MEPs averaged in real-time. The peak-to-peak amplitude of each muscle's mean MEP was measured at each stimulation site. The area of a muscle's representation was measured by a pixel-counting algorithm. The optimal point of each muscle's areal representation, which corresponds to the locus near which the largest MEPs are obtained, was determined by fitting a 3D Lorentzian function to the data points. The optimal point of distal muscles tended to be situated more laterally along the motor strip than that of proximal muscles. However, there was no statistically significant difference between the size of the areal representations and they overlapped considerably. Additionally, in another five subjects, using a small 45-mm coil placed in a hyper-focal orientation, maps were obtained at a stimulus intensity of 1.1-1.15 times the AMT of the muscle with the lowest threshold, usually the 1DI. Even in this very stringent condition, the mapped representations of the AD, ECR and 1DI overlapped, notwithstanding that sharp demarcations between borders were also apparent. These observations demonstrate that stimulus spread alone does not explain the overlap of muscle representations. These results show that commonly used proximal and distal upper-limb muscles, taken individually, are controlled by motor cortical territories of approximately equal size that significantly overlap despite differences in the location of their optimal points.

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

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.

There is mounting evidence that appropriately timed neuromuscular stimulation can induce neural plasticity and generate functional recovery from motor disorders. This review addresses the idea that coordinating stimulation with a patient’s voluntary effort might further enhance neurorehabilitation. Studies in cell cultures and behaving animals have delineated the rules underlying neural plasticity when single neurons are used as triggers. However, the rules governing more complex stimuli and larger networks are less well understood. We argue that functional recovery might be optimized if stimulation were modulated by a brain machine interface, to matched the details of the patient’s voluntary intent. The potential of this novel approach highlights the need for a better understanding of the complex rules underlying this form of plasticity.