↓ Skip to main content

The banana code—natural blend processing in the olfactory circuitry of Drosophila melanogaster

Overview of attention for article published in Frontiers in Physiology, January 2014
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
4 X users
facebook
1 Facebook page

Readers on

mendeley
95 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The banana code—natural blend processing in the olfactory circuitry of Drosophila melanogaster
Published in
Frontiers in Physiology, January 2014
DOI 10.3389/fphys.2014.00059
Pubmed ID
Authors

Marco Schubert, Bill S. Hansson, Silke Sachse

Abstract

Odor information is predominantly perceived as complex odor blends. For Drosophila melanogaster one of the most attractive blends is emitted by an over-ripe banana. To analyze how the fly's olfactory system processes natural blends we combined the experimental advantages of gas chromatography and functional imaging (GC-I). In this way, natural banana compounds were presented successively to the fly antenna in close to natural occurring concentrations. This technique allowed us to identify the active odor components, use these compounds as stimuli and measure odor-induced Ca(2+) signals in input and output neurons of the Drosophila antennal lobe (AL), the first olfactory neuropil. We demonstrate that mixture interactions of a natural blend are very rare and occur only at the AL output level resulting in a surprisingly linear blend representation. However, the information regarding single components is strongly modulated by the olfactory circuitry within the AL leading to a higher similarity between the representation of individual components and the banana blend. This observed modulation might tune the olfactory system in a way to distinctively categorize odor components and improve the detection of suitable food sources. Functional GC-I thus enables analysis of virtually any unknown natural odorant blend and its components in their relative occurring concentrations and allows characterization of neuronal responses of complete neural assemblies. This technique can be seen as a valuable complementary method to classical GC/electrophysiology techniques, and will be a highly useful tool in future investigations of insect-insect and insect-plant chemical interactions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
France 1 1%
United Kingdom 1 1%
Canada 1 1%
United States 1 1%
Unknown 88 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 34%
Researcher 23 24%
Student > Bachelor 8 8%
Student > Master 8 8%
Other 4 4%
Other 7 7%
Unknown 13 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 54%
Neuroscience 15 16%
Biochemistry, Genetics and Molecular Biology 5 5%
Computer Science 3 3%
Business, Management and Accounting 1 1%
Other 7 7%
Unknown 13 14%
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 09 March 2014.
All research outputs
#13,173,409
of 23,577,654 outputs
Outputs from Frontiers in Physiology
#4,101
of 14,284 outputs
Outputs of similar age
#158,785
of 309,121 outputs
Outputs of similar age from Frontiers in Physiology
#44
of 106 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,284 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 70% 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 309,121 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 106 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.