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Restoring cortical control of functional movement in a human with quadriplegia

Overview of attention for article published in Nature, April 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

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mendeley
457 Mendeley
citeulike
2 CiteULike
Title
Restoring cortical control of functional movement in a human with quadriplegia
Published in
Nature, April 2016
DOI 10.1038/nature17435
Pubmed ID
Authors

Chad E. Bouton, Ammar Shaikhouni, Nicholas V. Annetta, Marcia A. Bockbrader, David A. Friedenberg, Dylan M. Nielson, Gaurav Sharma, Per B. Sederberg, Bradley C. Glenn, W. Jerry Mysiw, Austin G. Morgan, Milind Deogaonkar, Ali R. Rezai, Bouton, Chad E, Shaikhouni, Ammar, Annetta, Nicholas V, Bockbrader, Marcia A, Friedenberg, David A, Nielson, Dylan M, Sharma, Gaurav, Sederberg, Per B, Glenn, Bradley C, Mysiw, W Jerry, Morgan, Austin G, Deogaonkar, Milind, Rezai, Ali R, Bouton CE, Shaikhouni A, Annetta NV, Bockbrader MA, Friedenberg DA, Nielson DM, Sharma G, Sederberg PB, Glenn BC, Mysiw WJ, Morgan AG, Deogaonkar M, Rezai AR

Abstract

Millions of people worldwide suffer from diseases that lead to paralysis through disruption of signal pathways between the brain and the muscles. Neuroprosthetic devices are designed to restore lost function and could be used to form an electronic 'neural bypass' to circumvent disconnected pathways in the nervous system. It has previously been shown that intracortically recorded signals can be decoded to extract information related to motion, allowing non-human primates and paralysed humans to control computers and robotic arms through imagined movements. In non-human primates, these types of signal have also been used to drive activation of chemically paralysed arm muscles. Here we show that intracortically recorded signals can be linked in real-time to muscle activation to restore movement in a paralysed human. We used a chronically implanted intracortical microelectrode array to record multiunit activity from the motor cortex in a study participant with quadriplegia from cervical spinal cord injury. We applied machine-learning algorithms to decode the neuronal activity and control activation of the participant's forearm muscles through a custom-built high-resolution neuromuscular electrical stimulation system. The system provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and hand motions. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Clinical assessment showed that, when using the system, his motor impairment improved from the fifth to the sixth cervical (C5-C6) to the seventh cervical to first thoracic (C7-T1) level unilaterally, conferring on him the critical abilities to grasp, manipulate, and release objects. This is the first demonstration to our knowledge of successful control of muscle activation using intracortically recorded signals in a paralysed human. These results have significant implications in advancing neuroprosthetic technology for people worldwide living with the effects of paralysis.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 457 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 25 5%
United Kingdom 8 2%
Spain 4 <1%
Germany 2 <1%
Italy 2 <1%
Switzerland 2 <1%
Japan 2 <1%
Singapore 2 <1%
Australia 1 <1%
Other 11 2%
Unknown 398 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 140 31%
Researcher 103 23%
Student > Master 54 12%
Student > Bachelor 43 9%
Professor 26 6%
Other 91 20%
Readers by discipline Count As %
Engineering 119 26%
Agricultural and Biological Sciences 81 18%
Neuroscience 73 16%
Medicine and Dentistry 59 13%
Computer Science 29 6%
Other 96 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 2430. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 July 2017.
All research outputs
#184
of 8,191,579 outputs
Outputs from Nature
#52
of 47,627 outputs
Outputs of similar age
#14
of 275,252 outputs
Outputs of similar age from Nature
#4
of 1,009 outputs
Altmetric has tracked 8,191,579 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 47,627 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 74.0. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 275,252 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 1,009 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.