Taste quality and hunger interactions in a feeding sensorimotor circuit

  1. Philip K Shiu
  2. Gabriella R Sterne  Is a corresponding author
  3. Stefanie Engert
  4. Barry J Dickson
  5. Kristin Scott  Is a corresponding author
  1. University of California, Berkeley, United States
  2. University of Queensland, Australia

Abstract

Taste detection and hunger state dynamically regulate the decision to initiate feeding. To study how context-appropriate feeding decisions are generated, we combined synaptic resolution circuit reconstruction with targeted genetic access to specific neurons to elucidate a gustatory sensorimotor circuit for feeding initiation in adult Drosophila melanogaster. This circuit connects gustatory sensory neurons to proboscis motor neurons through three intermediate layers. Most neurons in this pathway are necessary and sufficient for proboscis extension, a feeding initiation behavior, and respond selectively to sugar taste detection. Pathway activity is amplified by hunger signals that act at select second-order neurons to promote feeding initiation in food-deprived animals. In contrast, the feeding initiation circuit is inhibited by a bitter taste pathway that impinges on premotor neurons, illuminating a local motif that weighs sugar and bitter taste detection to adjust behavioral outcome. Together, these studies reveal central mechanisms for the integration of external taste detection and internal nutritive state to flexibly execute a critical feeding decision.

Data availability

All data is included in the manuscript or available at https://catmaid-fafb.virtualflybrain.org.

Article and author information

Author details

  1. Philip K Shiu

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Gabriella R Sterne

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    For correspondence
    sternegr@berkeley.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7221-648X
  3. Stefanie Engert

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0644-8116
  4. Barry J Dickson

    Queensland Brain Institute, University of Queensland, Queensland, Australia
    Competing interests
    The authors declare that no competing interests exist.
  5. Kristin Scott

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    For correspondence
    kscott@berkeley.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3150-7210

Funding

National Institutes of Health (R01DC013280)

  • Kristin Scott

National Institutes of Health (F32DK117671)

  • Gabriella R Sterne

National Institutes of Health (F32DC018225)

  • Philip K Shiu

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Shiu et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 4,316
    views
  • 754
    downloads
  • 31
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Philip K Shiu
  2. Gabriella R Sterne
  3. Stefanie Engert
  4. Barry J Dickson
  5. Kristin Scott
(2022)
Taste quality and hunger interactions in a feeding sensorimotor circuit
eLife 11:e79887.
https://doi.org/10.7554/eLife.79887

Share this article

https://doi.org/10.7554/eLife.79887

Further reading

    1. Biochemistry and Chemical Biology
    2. Neuroscience
    Silvia Galli, Marco Di Antonio
    Insight

    The buildup of knot-like RNA structures in brain cells may be the key to understanding how uncontrolled protein aggregation drives Alzheimer’s disease.

    1. Neuroscience
    Paul I Jaffe, Gustavo X Santiago-Reyes ... Russell A Poldrack
    Research Article

    Evidence accumulation models (EAMs) are the dominant framework for modeling response time (RT) data from speeded decision-making tasks. While providing a good quantitative description of RT data in terms of abstract perceptual representations, EAMs do not explain how the visual system extracts these representations in the first place. To address this limitation, we introduce the visual accumulator model (VAM), in which convolutional neural network models of visual processing and traditional EAMs are jointly fitted to trial-level RTs and raw (pixel-space) visual stimuli from individual subjects in a unified Bayesian framework. Models fitted to large-scale cognitive training data from a stylized flanker task captured individual differences in congruency effects, RTs, and accuracy. We find evidence that the selection of task-relevant information occurs through the orthogonalization of relevant and irrelevant representations, demonstrating how our framework can be used to relate visual representations to behavioral outputs. Together, our work provides a probabilistic framework for both constraining neural network models of vision with behavioral data and studying how the visual system extracts representations that guide decisions.