↓ Skip to main content

The coding of valence and identity in the mammalian taste system

Overview of attention for article published in Nature, May 2018
Altmetric Badge

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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Citations

dimensions_citation
171 Dimensions

Readers on

mendeley
388 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 coding of valence and identity in the mammalian taste system
Published in
Nature, May 2018
DOI 10.1038/s41586-018-0165-4
Pubmed ID
Authors

Li Wang, Sarah Gillis-Smith, Yueqing Peng, Juen Zhang, Xiaoke Chen, C. Daniel Salzman, Nicholas J. P. Ryba, Charles S. Zuker

Abstract

The ability of the taste system to identify a tastant (what it tastes like) enables animals to recognize and discriminate between the different basic taste qualities1,2. The valence of a tastant (whether it is appetitive or aversive) specifies its hedonic value and elicits the execution of selective behaviours. Here we examine how sweet and bitter are afforded valence versus identity in mice. We show that neurons in the sweet-responsive and bitter-responsive cortex project to topographically distinct areas of the amygdala, with strong segregation of neural projections conveying appetitive versus aversive taste signals. By manipulating selective taste inputs to the amygdala, we show that it is possible to impose positive or negative valence on a neutral water stimulus, and even to reverse the hedonic value of a sweet or bitter tastant. Remarkably, mice with silenced neurons in the amygdala no longer exhibit behaviour that reflects the valence associated with direct stimulation of the taste cortex, or with delivery of sweet and bitter chemicals. Nonetheless, these mice can still identify and discriminate between tastants, just as wild-type controls do. These results help to explain how the taste system generates stereotypic and predetermined attractive and aversive taste behaviours, and support the existence of distinct neural substrates for the discrimination of taste identity and the assignment of valence.

X Demographics

X Demographics

The data shown below were collected from the profiles of 78 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 388 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 388 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 85 22%
Researcher 70 18%
Student > Bachelor 43 11%
Student > Master 32 8%
Student > Doctoral Student 23 6%
Other 62 16%
Unknown 73 19%
Readers by discipline Count As %
Neuroscience 151 39%
Agricultural and Biological Sciences 64 16%
Biochemistry, Genetics and Molecular Biology 23 6%
Psychology 18 5%
Medicine and Dentistry 15 4%
Other 31 8%
Unknown 86 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 705. 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 02 November 2023.
All research outputs
#29,724
of 25,734,859 outputs
Outputs from Nature
#2,742
of 98,631 outputs
Outputs of similar age
#615
of 345,303 outputs
Outputs of similar age from Nature
#61
of 934 outputs
Altmetric has tracked 25,734,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 98,631 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.6. This one has done particularly well, scoring higher than 97% 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 345,303 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 99% of its contemporaries.
We're also able to compare this research output to 934 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.