The nematode worm C. elegans chooses between bacterial foods as if maximizing economic utility

  1. Abraham Katzen
  2. Hui-Kuan Chung
  3. William T Harbaugh
  4. Christina Della Iacono
  5. Nicholas Jackson
  6. Elizabeth E Glater
  7. Charles J Taylor
  8. Stephanie K Yu
  9. Steven W Flavell
  10. Paul Glimcher
  11. James Andreoni
  12. Shawn R Lockery  Is a corresponding author
  1. University of Oregon, United States
  2. New York University, United States
  3. Pomona College, United States
  4. Massachusetts Institute of Technology, United States
  5. University of California, San Diego, United States

Abstract

In value-based decision making, options are selected according to subjective values assigned by the individual to available goods and actions. Despite the importance of this faculty of the mind, the neural mechanisms of value assignments, and how choices are directed by them, remain obscure. To investigate this problem, we used a classic measure of utility maximization, the Generalized Axiom of Revealed Preference, to quantify internal consistency of food preferences in Caenorhabditis elegans, a nematode worm with a nervous system of only 302 neurons. Using a novel combination of microfluidics and electrophysiology, we found that C. elegans food choices fulfill the necessary and sufficient conditions for utility maximization, indicating that nematodes behave as if they maintain, and attempt to maximize, an underlying representation of subjective value. Food choices are well-fit by a utility function widely used to model human consumers. Moreover, as in many other animals, subjective values in C. elegans are learned, a process we find requires intact dopamine signaling. Differential responses of identified chemosensory neurons to foods with distinct growth potentials are amplified by prior consumption of these foods, suggesting that these neurons may be part of a value-assignment system. The demonstration of utility maximization in an organism with a very small nervous system sets a new lower bound on the computational requirements for utility maximization and offers the prospect of an essentially complete explanation of value-based decision making at single neuron resolution in this organism.

Data availability

Data of Figures 2, 4, 5-9 are available as Source Data files associated with this publication.

Article and author information

Author details

  1. Abraham Katzen

    Institute of Neuroscience, University of Oregon, Eugene, United States
    Competing interests
    No competing interests declared.
  2. Hui-Kuan Chung

    Center for Neural Science, New York University, New York, United States
    Competing interests
    No competing interests declared.
  3. William T Harbaugh

    Department of Economics, University of Oregon, Eugene, United States
    Competing interests
    No competing interests declared.
  4. Christina Della Iacono

    Institute of Neuroscience, University of Oregon, Eugene, United States
    Competing interests
    No competing interests declared.
  5. Nicholas Jackson

    Institute of Neuroscience, University of Oregon, Eugene, United States
    Competing interests
    No competing interests declared.
  6. Elizabeth E Glater

    Department of Neuroscience, Pomona College, Claremont, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0205-8209
  7. Charles J Taylor

    Department of Chemistry, Pomona College, Claremont, United States
    Competing interests
    No competing interests declared.
  8. Stephanie K Yu

    Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  9. Steven W Flavell

    Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9464-1877
  10. Paul Glimcher

    Center for Neural Science, New York University, New York, United States
    Competing interests
    No competing interests declared.
  11. James Andreoni

    Department of Economics, University of California, San Diego, La Jolla, United States
    Competing interests
    No competing interests declared.
  12. Shawn R Lockery

    Institute of Neuroscience, University of Oregon, Eugene, United States
    For correspondence
    shawn.lockery@nemametrix.com
    Competing interests
    Shawn R Lockery, is co-founder and Chief Technology Officer of InVivo Biosystems, Inc., which manufactures instrumentation for recording electropharyngeograms..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8535-7989

Funding

National Institute of Mental Health (MH051383)

  • Shawn R Lockery

National Institute of General Medical Sciences (GM129576)

  • Shawn R Lockery

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

Reviewing Editor

  1. Manuel Zimmer, University of Vienna, Austria

Version history

  1. Preprint posted: April 26, 2021 (view preprint)
  2. Received: April 26, 2021
  3. Accepted: April 19, 2023
  4. Accepted Manuscript published: April 25, 2023 (version 1)
  5. Version of Record published: May 31, 2023 (version 2)

Copyright

© 2023, Katzen 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.

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  1. Abraham Katzen
  2. Hui-Kuan Chung
  3. William T Harbaugh
  4. Christina Della Iacono
  5. Nicholas Jackson
  6. Elizabeth E Glater
  7. Charles J Taylor
  8. Stephanie K Yu
  9. Steven W Flavell
  10. Paul Glimcher
  11. James Andreoni
  12. Shawn R Lockery
(2023)
The nematode worm C. elegans chooses between bacterial foods as if maximizing economic utility
eLife 12:e69779.
https://doi.org/10.7554/eLife.69779

Share this article

https://doi.org/10.7554/eLife.69779

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