Nematodes Maximize Expected Utility on the heels of the new paper showing that the trading behavior of mycorrhizal fungi is consistent with the predictions of general equilibrium theory we have that nematodes obey the generalized axiom of revealed preference. It would be amusing if economics turns out to work well everywhere except for humans.

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 electro-physiology, we found that C. elegans food choices fulfill the necessary and sufficient conditions for utility maximization, indicating that nematodes behave exactly 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 now find requires intact dopamine signaling. Differential responses of identified chemosensory neurons to foods with distinct growth potential 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 no more than several hundred neurons sets a new lower bound on the computational requirements for maximization, and offers the prospect of an essentially complete explanation of value-based decision making at single neuron resolution.

Photo Credit: By Agricultural Research Service – source (15016 KB); Description page, Public Domain,

Hat tip: Derek Lowe.


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