The coding of valence and identity in the mammalian taste system View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-06

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. More... »

PAGES

127-131

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41586-018-0165-4

DOI

http://dx.doi.org/10.1038/s41586-018-0165-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104243615

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29849148


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41586-018-0165-4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41586-018-0165-4'

Turtle is a human-readable linked data format.

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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41586-018-0165-4'


 

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298 https://www.grid.ac/institutes/grid.21729.3f schema:alternateName Columbia University
299 schema:name Department of Biochemistry and Molecular Biophysics, Columbia College of Physicians and Surgeons, Columbia University, New York, NY, USA
300 Department of Neuroscience, Columbia College of Physicians and Surgeons, Columbia University, New York, NY, USA
301 Department of Psychiatry and New York State Psychiatric Institute, Columbia University, New York, NY, USA
302 Howard Hughes Medical Institute, Columbia University, New York, NY, USA
303 rdf:type schema:Organization
304 https://www.grid.ac/institutes/grid.419633.a schema:alternateName National Institute of Dental and Craniofacial Research
305 schema:name National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
306 rdf:type schema:Organization
 




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