Institute of Neuroscience, University of Oregon, Eugene, United States.
Center for Neural Science, New York University, New York, United States.
Elife. 2023 Apr 25;12:e69779. doi: 10.7554/eLife.69779.
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 , a nematode worm with a nervous system of only 302 neurons. Using a novel combination of microfluidics and electrophysiology, we found that 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 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.
在基于价值的决策中,根据个人对可用商品和行为赋予的主观价值来选择选项。尽管这种思维能力很重要,但价值分配的神经机制以及选择如何受到它们的影响仍然不清楚。为了解决这个问题,我们使用了经典的效用最大化度量标准,即揭示偏好的广义公理,来量化线虫(一种神经系统仅有 302 个神经元的线虫)中食物偏好的内部一致性。通过微流控和电生理学的新颖组合,我们发现线虫的食物选择满足了效用最大化的必要和充分条件,这表明线虫表现出它们维持并试图最大化潜在的主观价值的表示。食物选择符合广泛用于模拟人类消费者的效用函数。此外,与许多其他动物一样,线虫的主观价值是通过学习获得的,我们发现这个过程需要完整的多巴胺信号。对具有不同生长潜力的食物的不同识别化学感觉神经元的反应被这些食物的先前消耗放大,这表明这些神经元可能是价值分配系统的一部分。在神经系统非常小的生物体中证明了效用最大化,为效用最大化的计算要求设定了一个新的下限,并为在该生物体中单神经元分辨率下基于价值的决策提供了一个完整解释的前景。