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A Brain-Machine Interface Enables Bimanual Arm Movements in Monkeys

Overview of attention for article published in Science Translational Medicine, November 2013
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About this Attention Score

  • 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 (96th percentile)

Mentioned by

news
28 news outlets
blogs
8 blogs
twitter
42 tweeters
facebook
8 Facebook pages
googleplus
2 Google+ users
video
1 video uploader

Readers on

mendeley
239 Mendeley
citeulike
1 CiteULike
Title
A Brain-Machine Interface Enables Bimanual Arm Movements in Monkeys
Published in
Science Translational Medicine, November 2013
DOI 10.1126/scitranslmed.3006159
Pubmed ID
Authors

P. J. Ifft, S. Shokur, Z. Li, M. A. Lebedev, M. A. L. Nicolelis

Abstract

Brain-machine interfaces (BMIs) are artificial systems that aim to restore sensation and movement to paralyzed patients. So far, BMIs have enabled only one arm to be moved at a time. Control of bimanual arm movements remains a major challenge. We have developed and tested a bimanual BMI that enables rhesus monkeys to control two avatar arms simultaneously. The bimanual BMI was based on the extracellular activity of 374 to 497 neurons recorded from several frontal and parietal cortical areas of both cerebral hemispheres. Cortical activity was transformed into movements of the two arms with a decoding algorithm called a fifth-order unscented Kalman filter (UKF). The UKF was trained either during a manual task performed with two joysticks or by having the monkeys passively observe the movements of avatar arms. Most cortical neurons changed their modulation patterns when both arms were engaged simultaneously. Representing the two arms jointly in a single UKF decoder resulted in improved decoding performance compared with using separate decoders for each arm. As the animals' performance in bimanual BMI control improved over time, we observed widespread plasticity in frontal and parietal cortical areas. Neuronal representation of the avatar and reach targets was enhanced with learning, whereas pairwise correlations between neurons initially increased and then decreased. These results suggest that cortical networks may assimilate the two avatar arms through BMI control. These findings should help in the design of more sophisticated BMIs capable of enabling bimanual motor control in human patients.

Twitter Demographics

The data shown below were collected from the profiles of 42 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 239 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 5%
Brazil 6 3%
Netherlands 2 <1%
Germany 2 <1%
United Kingdom 2 <1%
Switzerland 1 <1%
Russia 1 <1%
Italy 1 <1%
Japan 1 <1%
Other 0 0%
Unknown 212 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 65 27%
Researcher 42 18%
Student > Bachelor 41 17%
Student > Master 32 13%
Professor 14 6%
Other 34 14%
Unknown 11 5%
Readers by discipline Count As %
Engineering 63 26%
Agricultural and Biological Sciences 57 24%
Neuroscience 35 15%
Medicine and Dentistry 21 9%
Computer Science 12 5%
Other 28 12%
Unknown 23 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 312. 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 18 July 2019.
All research outputs
#48,299
of 15,462,543 outputs
Outputs from Science Translational Medicine
#188
of 4,186 outputs
Outputs of similar age
#550
of 189,049 outputs
Outputs of similar age from Science Translational Medicine
#3
of 98 outputs
Altmetric has tracked 15,462,543 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 4,186 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 64.3. This one has done particularly well, scoring higher than 95% 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 189,049 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 98 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 96% of its contemporaries.