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Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2013
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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Title
Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling
Published in
Frontiers in Computational Neuroscience, January 2013
DOI 10.3389/fncom.2013.00024
Pubmed ID
Authors

Julijana Gjorgjieva, Jimena Berni, Jan Felix Evers, Stephen J. Eglen

Abstract

Drosophila larvae crawl by peristaltic waves of muscle contractions, which propagate along the animal body and involve the simultaneous contraction of the left and right side of each segment. Coordinated propagation of contraction does not require sensory input, suggesting that movement is generated by a central pattern generator (CPG). We characterized crawling behavior of newly hatched Drosophila larvae by quantifying timing and duration of segmental boundary contractions. We developed a CPG network model that recapitulates these patterns based on segmentally repeated units of excitatory and inhibitory (EI) neuronal populations coupled with immediate neighboring segments. A single network with symmetric coupling between neighboring segments succeeded in generating both forward and backward propagation of activity. The CPG network was robust to changes in amplitude and variability of connectivity strength. Introducing sensory feedback via "stretch-sensitive" neurons improved wave propagation properties such as speed of propagation and segmental contraction duration as observed experimentally. Sensory feedback also restored propagating activity patterns when an inappropriately tuned CPG network failed to generate waves. Finally, in a two-sided CPG model we demonstrated that two types of connectivity could synchronize the activity of two independent networks: connections from excitatory neurons on one side to excitatory contralateral neurons (E to E), and connections from inhibitory neurons on one side to excitatory contralateral neurons (I to E). To our knowledge, such I to E connectivity has not yet been found in any experimental system; however, it provides the most robust mechanism to synchronize activity between contralateral CPGs in our model. Our model provides a general framework for studying the conditions under which a single locally coupled network generates bilaterally synchronized and longitudinally propagating waves in either direction.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Germany 1 <1%
Australia 1 <1%
Unknown 116 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 30%
Student > Bachelor 17 14%
Researcher 12 10%
Student > Doctoral Student 12 10%
Student > Master 9 8%
Other 18 15%
Unknown 15 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 33%
Neuroscience 29 24%
Biochemistry, Genetics and Molecular Biology 11 9%
Engineering 10 8%
Physics and Astronomy 7 6%
Other 7 6%
Unknown 16 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 06 June 2013.
All research outputs
#8,891,434
of 26,401,177 outputs
Outputs from Frontiers in Computational Neuroscience
#467
of 1,495 outputs
Outputs of similar age
#90,228
of 294,572 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#39
of 139 outputs
Altmetric has tracked 26,401,177 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1,495 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has gotten more attention than average, scoring higher than 68% 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 294,572 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 69% of its contemporaries.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.