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Plasticity-driven individualization of olfactory coding in mushroom body output neurons

Overview of attention for article published in Nature, September 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

news
4 news outlets
blogs
6 blogs
twitter
35 tweeters
facebook
6 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
302 Mendeley
Title
Plasticity-driven individualization of olfactory coding in mushroom body output neurons
Published in
Nature, September 2015
DOI 10.1038/nature15396
Pubmed ID
Authors

Toshihide Hige, Yoshinori Aso, Gerald M. Rubin, Glenn C. Turner

Abstract

Although all sensory circuits ascend to higher brain areas where stimuli are represented in sparse, stimulus-specific activity patterns, relatively little is known about sensory coding on the descending side of neural circuits, as a network converges. In insects, mushroom bodies have been an important model system for studying sparse coding in the olfactory system, where this format is important for accurate memory formation. In Drosophila, it has recently been shown that the 2,000 Kenyon cells of the mushroom body converge onto a population of only 34 mushroom body output neurons (MBONs), which fall into 21 anatomically distinct cell types. Here we provide the first, to our knowledge, comprehensive view of olfactory representations at the fourth layer of the circuit, where we find a clear transition in the principles of sensory coding. We show that MBON tuning curves are highly correlated with one another. This is in sharp contrast to the process of progressive decorrelation of tuning in the earlier layers of the circuit. Instead, at the population level, odour representations are reformatted so that positive and negative correlations arise between representations of different odours. At the single-cell level, we show that uniquely identifiable MBONs display profoundly different tuning across different animals, but that tuning of the same neuron across the two hemispheres of an individual fly was nearly identical. Thus, individualized coordination of tuning arises at this level of the olfactory circuit. Furthermore, we find that this individualization is an active process that requires a learning-related gene, rutabaga. Ultimately, neural circuits have to flexibly map highly stimulus-specific information in sparse layers onto a limited number of different motor outputs. The reformatting of sensory representations we observe here may mark the beginning of this sensory-motor transition in the olfactory system.

Twitter Demographics

The data shown below were collected from the profiles of 35 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 302 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 2%
Germany 6 2%
United Kingdom 2 <1%
India 1 <1%
Brazil 1 <1%
Japan 1 <1%
Portugal 1 <1%
Argentina 1 <1%
Unknown 283 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 106 35%
Researcher 76 25%
Unspecified 27 9%
Student > Master 22 7%
Student > Bachelor 17 6%
Other 54 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 133 44%
Neuroscience 95 31%
Unspecified 28 9%
Biochemistry, Genetics and Molecular Biology 14 5%
Computer Science 8 3%
Other 24 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 96. 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 04 April 2016.
All research outputs
#152,227
of 12,809,119 outputs
Outputs from Nature
#11,763
of 66,911 outputs
Outputs of similar age
#4,519
of 246,559 outputs
Outputs of similar age from Nature
#421
of 1,024 outputs
Altmetric has tracked 12,809,119 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 66,911 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 73.5. This one has done well, scoring higher than 82% 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 246,559 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 1,024 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 58% of its contemporaries.