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A functional model and simulation of spinal motor pools and intrafascicular recordings of motoneuron activity in peripheral nerve

Overview of attention for article published in Frontiers in Neuroscience, November 2014
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Title
A functional model and simulation of spinal motor pools and intrafascicular recordings of motoneuron activity in peripheral nerve
Published in
Frontiers in Neuroscience, November 2014
DOI 10.3389/fnins.2014.00371
Pubmed ID
Authors

Mohamed N. Abdelghani, James J. Abbas, Kenneth W. Horch, Ranu Jung

Abstract

Decoding motor intent from recorded neural signals is essential for the development of effective neural-controlled prostheses. To facilitate the development of online decoding algorithms we have developed a software platform to simulate neural motor signals recorded with peripheral nerve electrodes, such as longitudinal intrafascicular electrodes (LIFEs). The simulator uses stored motor intent signals to drive a pool of simulated motoneurons with various spike shapes, recruitment characteristics, and firing frequencies. Each electrode records a weighted sum of a subset of simulated motoneuron activity patterns. As designed, the simulator facilitates development of a suite of test scenarios that would not be possible with actual data sets because, unlike with actual recordings, in the simulator the individual contributions to the simulated composite recordings are known and can be methodically varied across a set of simulation runs. In this manner, the simulation tool is suitable for iterative development of real-time decoding algorithms prior to definitive evaluation in amputee subjects with implanted electrodes. The simulation tool was used to produce data sets that demonstrate its ability to capture some features of neural recordings that pose challenges for decoding algorithms.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
Singapore 1 3%
Unknown 27 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 24%
Researcher 6 21%
Student > Bachelor 5 17%
Professor 4 14%
Student > Master 3 10%
Other 5 17%
Readers by discipline Count As %
Engineering 13 45%
Medicine and Dentistry 4 14%
Agricultural and Biological Sciences 3 10%
Unspecified 2 7%
Computer Science 2 7%
Other 3 10%
Unknown 2 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 14 November 2014.
All research outputs
#19,944,994
of 25,374,647 outputs
Outputs from Frontiers in Neuroscience
#8,669
of 11,542 outputs
Outputs of similar age
#185,365
of 269,850 outputs
Outputs of similar age from Frontiers in Neuroscience
#99
of 115 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 269,850 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.