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Brain-machine interfaces (BMIs) use signals recorded directly from the brain to control an external device, such as a computer cursor or a prosthetic limb. These control signals have been recorded from different levels of the brain, from field potentials at the scalp or cortical surface to single neuron action potentials. At present, the more invasive(More)
The loss of a limb or paralysis resulting from spinal cord injury has devastating consequences on quality of life. One approach to restoring lost sensory and motor abilities in amputees and patients with tetraplegia is to supply them with implants that provide a direct interface with the CNS. Such brain-machine interfaces might enable a patient to exert(More)
In this study we investigated pointing movements made with an extended arm. Despite the large number of mechanical degrees of freedom, limb orientation adopted during pointing could be described by rotation axes contained on a two-dimensional curved surface. As a result of the curvature, the orientation of a linear plane approximating a small region of the(More)
The recent explosion of interest in brain-machine interfaces (BMIs) has spurred research into choosing the optimal input signal source for a desired application. The signals with highest bandwidth--single neuron action potentials or spikes--typically are difficult to record for more than a few years after implantation of intracortical electrodes.(More)
1. We recorded from 239 neurons located in the magnocellular division of the red nucleus of four alert macaque monkeys. At the same time, we recorded electromyographic (EMG) signals from as many as twenty electrodes chronically implanted on muscles of the shoulder, arm, forearm and hand. We recorded EMG signals for periods ranging from several months to a(More)
Plasticity is a crucial component of normal brain function and a critical mechanism for recovery from injury. In vitro, associative pairing of presynaptic spiking and stimulus-induced postsynaptic depolarization causes changes in the synaptic efficacy of the presynaptic neuron, when activated by extrinsic stimulation. In vivo, such paradigms can alter the(More)
A robust identification algorithm has been developed for linear, time-invariant, multiple-input single-output systems, with an emphasis on how this algorithm can be used to estimate the dynamic relationship between a set of neural recordings and related physiological signals. The identification algorithm provides a decomposition of the system output such(More)
The activation of muscles can be studied by measuring the activity of a representative set of single motor units in a muscle or by measuring the surface electromyographic (EMG) activity of a muscle that results from the contribution of a large number of motor units. In this study we have developed a model showing how the direction dependence of the(More)
Despite the abundant experimental evidence for the irregular, multipeaked velocity profiles that often characterize rapid human limb movements, there is currently little agreement on how to interpret these phenomena. While in some studies these irregularities have been interpreted as reflecting a continuous control process, in others the irregularities are(More)
Loss of hand use is considered by many spinal cord injury survivors to be the most devastating consequence of their injury. Functional electrical stimulation (FES) of forearm and hand muscles has been used to provide basic, voluntary hand grasp to hundreds of human patients. Current approaches typically grade pre-programmed patterns of muscle activation(More)