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The interaction of positive and negative sensory feedback loops in dynamic regulation of a motor pattern

Overview of attention for article published in Journal of Computational Neuroscience, March 2009
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Article details
Title
The interaction of positive and negative sensory feedback loops in dynamic regulation of a motor pattern
Published in
Journal of Computational Neuroscience, March 2009
DOI 10.1007/s10827-009-0140-z
Pubmed ID
Authors
Abstract

In many rhythmic behaviors, phasic sensory feedback modifies the motor pattern. This modification is assumed to depend on feedback sign (positive vs. negative). While on a phenomenological level feedback sign is well defined, many sensory pathways also process antagonistic, and possibly contradictory, sensory information. We here model the locust flight pattern generator and proprioceptive feedback provided by the tegula wing receptor to test the functional significance of sensory pathways processing antagonistic information. We demonstrate that the tegula provides delayed positive feedback via interneuron 301, while all other pathways provide negative feedback. Contradictory to previous assumptions, the increase of wing beat frequency when the tegula is activated during flight is due to the positive feedback. By use of an abstract model we reveal that the regulation of motor pattern frequency by sensory feedback critically depends on the interaction of positive and negative feedback, and thus on the weighting of antagonistic pathways.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 4%
Germany 1 4%
Australia 1 4%
Unknown 25 89%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 7 25%
Student > Master 5 18%
Student > Ph. D. Student 3 11%
Professor > Associate Professor 3 11%
Student > Doctoral Student 2 7%
Other 6 21%
Unknown 2 7%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 12 43%
Engineering 6 21%
Neuroscience 5 18%
Linguistics 1 4%
Nursing and Health Professions 1 4%
Other 1 4%
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 17 July 2009.
All research outputs
#15,240,835
of 22,660,862 outputs
Outputs from Journal of Computational Neuroscience
#168
of 306 outputs
Outputs of similar age
#90,250
of 106,774 outputs
Outputs of similar age from Journal of Computational Neuroscience
#3
of 3 outputs
Altmetric has tracked 22,660,862 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 306 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 30th percentile – i.e., 30% 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 106,774 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.