↓ Skip to main content

Encoding of forelimb forces by corticospinal tract activity in the rat

Overview of attention for article published in Frontiers in Neuroscience, May 2014
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users
facebook
1 Facebook page

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
34 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Encoding of forelimb forces by corticospinal tract activity in the rat
Published in
Frontiers in Neuroscience, May 2014
DOI 10.3389/fnins.2014.00062
Pubmed ID
Authors

Yi Guo, Richard A. Foulds, Sergei V. Adamovich, Mesut Sahin

Abstract

In search of a solution to the long standing problems encountered in traditional brain computer interfaces (BCI), the lateral descending tracts of the spinal cord present an alternative site for taping into the volitional motor signals. Due to the convergence of the cortical outputs into a final common pathway in the descending tracts of the spinal cord, neural interfaces with the spinal cord can potentially acquire signals richer with volitional information in a smaller anatomical region. The main objective of this study was to evaluate the feasibility of extracting motor control signals from the corticospinal tract (CST) of the rat spinal cord. Flexible substrate, multi-electrode arrays (MEA) were implanted in the CST of rats trained for a lever pressing task. This novel use of flexible substrate MEAs allowed recording of CST activity in behaving animals for up to three weeks with the current implantation technique. Time-frequency and principal component analyses (PCA) were applied to the neural signals to reconstruct isometric forelimb forces. Computed regression coefficients were then used to predict isometric forces in additional trials. The correlation between measured and predicted forces in the vertical direction averaged across six animals was 0.67 and R (2) value was 0.44. Force regression in the horizontal directions was less successful, possibly due to the small amplitude of forces. Neural signals above and near the high gamma band made the largest contributions to prediction of forces. The results of this study support the feasibility of a spinal cord computer interface (SCCI) for generation of command signals in paralyzed individuals.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 33 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 21%
Researcher 6 18%
Student > Master 6 18%
Student > Doctoral Student 3 9%
Student > Bachelor 2 6%
Other 5 15%
Unknown 5 15%
Readers by discipline Count As %
Engineering 8 24%
Agricultural and Biological Sciences 7 21%
Medicine and Dentistry 7 21%
Neuroscience 4 12%
Sports and Recreations 1 3%
Other 1 3%
Unknown 6 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 December 2016.
All research outputs
#15,169,543
of 25,374,647 outputs
Outputs from Frontiers in Neuroscience
#6,402
of 11,538 outputs
Outputs of similar age
#123,515
of 242,177 outputs
Outputs of similar age from Frontiers in Neuroscience
#51
of 102 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,538 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 42nd percentile – i.e., 42% 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 242,177 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.