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Eyes Matched to the Prize: The State of Matched Filters in Insect Visual Circuits

Overview of attention for article published in Frontiers in Neural Circuits, April 2018
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Title
Eyes Matched to the Prize: The State of Matched Filters in Insect Visual Circuits
Published in
Frontiers in Neural Circuits, April 2018
DOI 10.3389/fncir.2018.00026
Pubmed ID
Authors

Jessica R. Kohn, Sarah L. Heath, Rudy Behnia

Abstract

Confronted with an ever-changing visual landscape, animals must be able to detect relevant stimuli and translate this information into behavioral output. A visual scene contains an abundance of information: to interpret the entirety of it would be uneconomical. To optimally perform this task, neural mechanisms exist to enhance the detection of important features of the sensory environment while simultaneously filtering out irrelevant information. This can be accomplished by using a circuit design that implements specific "matched filters" that are tuned to relevant stimuli. Following this rule, the well-characterized visual systems of insects have evolved to streamline feature extraction on both a structural and functional level. Here, we review examples of specialized visual microcircuits for vital behaviors across insect species, including feature detection, escape, and estimation of self-motion. Additionally, we discuss how these microcircuits are modulated to weigh relevant input with respect to different internal and behavioral states.

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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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 23%
Student > Ph. D. Student 10 21%
Student > Master 4 8%
Student > Doctoral Student 3 6%
Student > Bachelor 3 6%
Other 4 8%
Unknown 13 27%
Readers by discipline Count As %
Neuroscience 17 35%
Agricultural and Biological Sciences 8 17%
Physics and Astronomy 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Engineering 2 4%
Other 5 10%
Unknown 12 25%
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 20 April 2018.
All research outputs
#15,330,390
of 23,577,654 outputs
Outputs from Frontiers in Neural Circuits
#710
of 1,243 outputs
Outputs of similar age
#200,560
of 330,379 outputs
Outputs of similar age from Frontiers in Neural Circuits
#17
of 24 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,243 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 36th percentile – i.e., 36% 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 330,379 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.