Two-dimensional reward evaluation in mice

Anim Cogn. 2021 Sep;24(5):981-998. doi: 10.1007/s10071-021-01482-8. Epub 2021 Mar 15.

Abstract

When choosing among multi-attribute options, integrating the full information may be computationally costly and time-consuming. So-called non-compensatory decision rules only rely on partial information, for example when a difference on a single attribute overrides all others. Such rules may be ecologically more advantageous, despite being economically suboptimal. Here, we present a study that investigates to what extent animals rely on integrative rules (using the full information) versus non-compensatory rules when choosing where to forage. Groups of mice were trained to obtain water from dispensers varying along two reward dimensions: volume and probability. The mice's choices over the course of the experiment suggested an initial reliance on integrative rules, later displaced by a sequential rule, in which volume was evaluated before probability. Our results also demonstrate that while the evaluation of probability differences may depend on the reward volumes, the evaluation of volume differences is seemingly unaffected by the reward probabilities.

Keywords: Economic decision-making; Home cage testing; Mice; Multi-attribute choice; Non-compensatory decision rules.

MeSH terms

  • Animals
  • Choice Behavior
  • Decision Making*
  • Mice
  • Probability
  • Reward*