Direct control of paralysed muscles by cortical neurons pdf

Neurobiol Dis , , 28 Oct Review Free to read. J Neurophysiol , 88 5 , 01 Nov Cited by: 42 articles PMID: Nat Rev Neurosci , 15 5 , 01 May Prog Brain Res , , 01 Jan Cited by: 7 articles PMID: Contact us. Europe PMC requires Javascript to function effectively. Recent Activity. Search life-sciences literature Over 39 million articles, preprints and more Search Advanced search. Moritz CT 1 ,. Perlmutter SI ,. Fetz EE.

Affiliations 1 author 1. Share this article Share with email Share with twitter Share with linkedin Share with facebook. Abstract A potential treatment for paralysis resulting from spinal cord injury is to route control signals from the brain around the injury by artificial connections.

Such signals could then control electrical stimulation of muscles, thereby restoring volitional movement to paralysed limbs. In previously separate experiments, activity of motor cortex neurons related to actual or imagined movements has been used to control computer cursors and robotic arms, and paralysed muscles have been activated by functional electrical stimulation.

Here we show that Macaca nemestrina monkeys can directly control stimulation of muscles using the activity of neurons in the motor cortex, thereby restoring goal-directed movements to a transiently paralysed arm. Moreover, neurons could control functional stimulation equally well regardless of any previous association to movement, a finding that considerably expands the source of control signals for brain-machine interfaces. Monkeys learned to use these artificial connections from cortical cells to muscles to generate bidirectional wrist torques, and controlled multiple neuron-muscle pairs simultaneously.

These results are the first demonstration that direct artificial connections between cortical cells and muscles can compensate for interrupted physiological pathways and restore volitional control of movement to paralysed limbs.

Free full text. Author manuscript; available in PMC Aug PMID: Chet T. Moritz , Steve I. Perlmutter , and Eberhard E. Author information Copyright and License information Disclaimer.

Moritz, Ph. Copyright notice. The publisher's final edited version of this article is available at Nature. See other articles in PMC that cite the published article. Associated Data Supplementary Materials 1. Abstract A potential treatment for paralysis resulting from spinal cord injury is to route control signals from the brain around the injury via artificial connections.

Open in a separate window. Figure 1. Brain-controlled functional electrical stimulation FES of muscle A Schematic shows cortical cell activity converted to FES during peripheral nerve block.

Figure 2. Figure 3. Figure 4. Two neurons control FES Monkey L simultaneously modulated activity of two neurons, each controlling proportional stimulation of a different muscle group when above threshold. Methods summary See complete methods and supplementary information for additional methods.

Subjects Two male Macaca nemestrina monkeys participated in the experiments 4—5 years old, weight 4. Brain-controlled FES Cell activity controlled the intensity of stimuli delivered via bipolar electrodes implanted in one or more paralyzed wrist muscles.

Analysis Strength of directional tuning was calculated for cells during the initial torque tracking task using the vector method Methods Cortical recording Sterile surgeries were performed with isoflurane anesthesia 1—1. Nerve block implant Reversible paralysis of the right wrist was achieved with one of two nerve block methods. Experimental paradigm The monkey sat with his right elbow and hand immobilized by padded splints while a transducer measured the flexion-extension F-E and radial-ulnar R-U torques produced about the wrist see Figure 1A.

Nerve block We blocked nerves leading to wrist muscles with local anesthetic to create temporary motor paralysis. Data sampling Signals were digitized and stored to disk for offline analysis. Data Analysis Task difficulty was increased incrementally by raising levels of torque targets and increasing hold times. Supplementary Material 1 Click here to view. Acknowledgments We thank L. Footnotes Author Contributions C.

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There have also arm. Two paralyzed monkey subjects roughly doubled their been efforts to use electroencephalographic EEG signals to maximum voluntary wrist flexion force, and were able to grade the trigger similar preprogrammed sequences [6,7,8]. Despite these force with sufficient accuracy to match a cursor to targets at advances, the goal of achieving truly dexterous manipulation of different force levels.

We are currently working to refine this objects remains elusive. We anticipate that the approach could offer recordings from the primary motor cortex M1 can be used to significant advantages to paralyzed patients with injuries in the predict kinematic features of desired movement [9,10,11,12] and mid-cervical spinal cord, and potentially even greater benefits to PLoS ONE www.

Direct brain control of functional electrical stimulation FES for wrist movement. A force-controlled cursor and a target were displayed on a computer monitor. Real-time predictions of desired muscle activation were generated from motor cortical activity and used to control the electrical stimulation of four muscles. Two monkeys could generate wrist force voluntarily despite the paralysis of wrist muscles by peripheral nerve blocks. For monkey A, the average Blocked entire upper limb.

It seemed apparent by watching the monkeys that some of the Voluntary Control of Paralyzed Muscles remaining force in the blocked state resulted from the action of We performed a series of experiments with two rhesus macaque unblocked, proximal muscles that was inappropriately registered monkeys monkeys A and T. Figure 1 illustrates the essential by the wrist force transducer. Unfortunately, quantifying the components of these experiments.

Each monkey faced a video magnitude of this effect is difficult. The magnitude of EMG from monitor that displayed a circular cursor and a rectangular target. For monkey T, the induced by pharmacological blocks of the median and ulnar nerves at the elbow, which affected the intrinsic hand muscles and extrinsic wrist and finger flexor muscles, while leaving the extensors intact.

We used recordings from a multi-electrode array chronically implanted in the primary motor cortex M1 to generate real-time predictions of intended muscle activation. These predictions were used to control the intensity of stimulation to four forearm flexor muscles, thus providing a brain interface by which the monkey could voluntarily control its paralyzed muscles. We quantified the effectiveness of this control in terms of: 1 the increase in voluntary force generating capacity, 2 the similarity in the time course of the force under normal and FES conditions, and 3 the precision with which the force was controlled.

The nerve block dramatically decreased the amount of wrist flexion force that the monkeys could generate voluntarily. Figure 2 summarizes this effectiveness, as well as the increase in force afforded by the brain-controlled FES.

We estimated maximum voluntary contraction MVC under normal, blocked, and FES conditions by measuring the maximum force that the monkey Figure 2. Nerve blocks could maintain for 0. Unless otherwise noted, all subsequent force-related results are tests in nine sessions was only 1. For monkey A, the average blocked EMG activity application. In this particular session, the monkey controlled the radialis.

The Even this small level of EMG might, nevertheless, have rectangles in Figure 3 indicate the upper and lower force limits of accounted for a disproportionate amount of the remaining force.

The force had to However, if this had been a significant effect, the magnitude of the be maintained within a target for 0. The 25 neurons used for control were related to the magnitude of the remaining EMG. This was not the clearly modulated during force generation. The individual case for any of the muscles from either monkey R2,0.

This logic leads us to conclude that the remaining force across neurons and across trials can be appreciated. None of the catch trials was successful in this particular Figure 3. Brain-controlled FES command signal and resulting force. Uppermost panel shows the modulation of the 25 neurons used for control. The discharge of each neuron has been normalized to the peak rate that occurred within this segment of data.

The FES-mediated force curve produced by monkey T during a continuous series of trials to different force targets rectangles is shown immediately below. Targets for successful trials are shown by open rectangles. Failed trials filled rectangles occurred only during random catch trials in which the brain interface and FES were not active gaps in the heavy black bar. Note however, that the monkey was clearly making an targets, aligned with respect to the onset of force under FES red effort to generate force on each of these trials, based on the curves and normal black curves conditions.

The thick curves accompanying patterns of neural discharge. Note also that force correspond to the medium height flexion target, indicated by the peaks generated during catch trials were much narrower than pink and gray rectangles representing FES and normal conditions, those during FES trials, as the monkey was unable to generate respectively.

The thin lines denote forces for the low and high force even low level sustained force without the FES; it appeared as targets corresponding targets not shown. Note that here and though the narrow force transients resulted primarily from inertial elsewhere, target height refers to the force level corresponding to the forces coupled to the hand as the proximal limb was accelerated.

These few successes occurred in a single time of occurrence of the go tone. Hence, distance from the left edge session in which the lowest edge of a target had been placed at the of a target to time 0 dashed line is the average reaction time RT. By contrast, when the brain interface The right edge of the target rectangles indicates the end of the and stimulators were active, both monkeys were consistently able average hold time for successful trials.

Because time to initial target entry, and the stabilization time within the of the additional complication of needing to inject lidocaine target. In the example in figure 4A, the FES trials had only slightly directly to the nerve, these sessions were shorter, averaging 80 longer average RT than normal. Across all six sessions for monkey trials in length. Although small, the 30 ms difference was monkey A for flexion targets. This Comparison of Normal and FES Force Control difference was target dependent, and is summarized in figure 4B as Figure 3 indicates that monkey T was able to control the a function of the target height.

The difference varied from roughly magnitude of brain-controlled stimulation sufficiently well to grade ms for the lowest targets to ms for the highest.

The wrist force according to several different target levels. For all sessions regression lines on panel B are fitted to the combined data from in which targets at multiple force levels were presented, the average both monkeys in each condition.

Figure 4. Time course of normal and FES-generated force. Pink and gray rectangles represent the top, bottom, and average duration of the targets in FES and normal conditions, respectively. Because the force traces are aligned to force onset vertical dashed line , the left edge of the target indicating the time of its appearance is dependent on the reaction time. Note that the left edge of the gray rectangle obscures much of the pink rectangle because of the very similar reaction times under normal and FES conditions.

The two thick curves represent the force trajectories for medium targets; the thin curves represent force trajectories for the high and low targets. B Average rise times for each session are plotted against the target height distance of target above zero force, normalized to the Blocked MVC. Rise time increased with target height under both normal and FES conditions, but the FES times red symbols were longer than normal black symbols for each monkey monkey T: circles, monkey A: squares. Variability of normal and FES-generated force.

A Examples of FES trials for monkey T include some that remained within the target from the time of entry until success red and green traces , and some that undershot purple trace or overshot blue trace the target. We quantified the variability of the force by calculating its standard deviation SD during the period between time of initial target entry and time of successful trial completion.

Variability was greater during FES than during normal trials for both monkeys monkey T: circles, monkey A: squares. During FES flexion trials, trials from monkey T. The red and green traces entered and stimulation typically preceded the onset of force.

However, during stayed within the target for more than the required ms. In extension trials, the monkeys typically began to generate normal contrast, the blue trace rapidly overshot the target before extension force somewhat before the onset of flexor muscle stabilizing within it.

Finally, the purple trace undershot the target stimulation, perhaps in part because of the relatively slow rise-time before being corrected. The high frequency tremor evident in of FES generated force described above.

These examples demonstrate that the monkey was activates only a subset of fibers in each muscle, that the able to achieve different force levels voluntarily, and to detect and recruitment order of these fibers is approximately reversed from modify incorrect force levels relatively quickly, although the normal, and that there is no rate modulation component at all.

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