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Integration of Descending Command Systems for the Generation of Context-Specific Locomotor Behaviors

Overview of attention for article published in Frontiers in Neuroscience, October 2017
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Title
Integration of Descending Command Systems for the Generation of Context-Specific Locomotor Behaviors
Published in
Frontiers in Neuroscience, October 2017
DOI 10.3389/fnins.2017.00581
Pubmed ID
Authors

Linda H. Kim, Sandeep Sharma, Simon A. Sharples, Kyle A. Mayr, Charlie H. T. Kwok, Patrick J. Whelan

Abstract

Over the past decade there has been a renaissance in our understanding of spinal cord circuits; new technologies are beginning to provide key insights into descending circuits which project onto spinal cord central pattern generators. By integrating work from both the locomotor and animal behavioral fields, we can now examine context-specific control of locomotion, with an emphasis on descending modulation arising from various regions of the brainstem. Here we examine approach and avoidance behaviors and the circuits that lead to the production and arrest of locomotion.

X Demographics

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The data shown below were collected from the profiles of 6 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 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 20%
Researcher 16 15%
Student > Bachelor 15 14%
Student > Master 9 9%
Student > Doctoral Student 6 6%
Other 18 17%
Unknown 19 18%
Readers by discipline Count As %
Neuroscience 45 43%
Agricultural and Biological Sciences 16 15%
Medicine and Dentistry 6 6%
Engineering 5 5%
Nursing and Health Professions 4 4%
Other 9 9%
Unknown 19 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 30 October 2017.
All research outputs
#14,605,790
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#5,875
of 11,542 outputs
Outputs of similar age
#164,740
of 336,554 outputs
Outputs of similar age from Frontiers in Neuroscience
#110
of 184 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% 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 11.0. This one is in the 47th percentile – i.e., 47% 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 336,554 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 184 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.