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A central control circuit for encoding perceived food value
Author(s) -
Michael Crossley,
Kevin Staras,
György Kemenes
Publication year - 2018
Publication title -
science advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.928
H-Index - 146
ISSN - 2375-2548
DOI - 10.1126/sciadv.aau9180
Subject(s) - encoding (memory) , value (mathematics) , control (management) , computer science , artificial intelligence , machine learning
Hunger state can substantially alter the perceived value of a stimulus, even to the extent that the same sensory cue can trigger antagonistic behaviors. How the nervous system uses these graded perceptual shifts to select between opposed motor patterns remains enigmatic. Here, we challenged food-deprived and satiated to choose between two mutually exclusive behaviors, ingestion or egestion, produced by the same feeding central pattern generator. Decoding the underlying neural circuit reveals that the activity of central dopaminergic interneurons defines hunger state and drives network reconfiguration, biasing satiated animals toward the rejection of stimuli deemed palatable by food-deprived ones. By blocking the action of these neurons, satiated animals can be reconfigured to exhibit a hungry animal phenotype. This centralized mechanism occurs in the complete absence of sensory retuning and generalizes across different sensory modalities, allowing food-deprived animals to increase their perception of food value in a stimulus-independent manner to maximize potential calorific intake.

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