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Two-dimensional reward evaluation in mice.

Vladislav Nachev1, Marion Rivalan2,3, York Winter2,3

  • 1Institute of Biology, Humboldt University, Philippstr. 13, 10099, Berlin, Germany. vladislav.nachev@gmail.com.

Animal Cognition
|March 15, 2021
PubMed
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Mice initially integrated all reward information but later used a sequential decision rule, prioritizing volume over probability. This suggests animals may use simpler foraging strategies when faced with complex choices.

Area of Science:

  • Behavioral Ecology
  • Animal Cognition
  • Decision Science

Background:

  • Integrating multi-attribute information for decisions can be computationally intensive.
  • Non-compensatory decision rules, using partial information, may offer ecological advantages over economically optimal strategies.

Purpose of the Study:

  • To investigate whether animals utilize integrative or non-compensatory decision rules when foraging.
  • To determine how mice evaluate reward dimensions like volume and probability.

Main Methods:

  • Mice were trained to choose between water dispensers with varying reward volumes and probabilities.
  • Choice behavior was analyzed to infer the decision rules employed.

Main Results:

Keywords:
Economic decision-makingHome cage testingMiceMulti-attribute choiceNon-compensatory decision rules

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  • Mice initially used integrative decision rules, considering both volume and probability.
  • Decision-making shifted to a sequential rule, evaluating volume before probability.
  • Volume evaluation was independent of probability, while probability evaluation was influenced by volume.

    • Conclusions:

    • Animal foraging decisions can shift from integrative to simpler, sequential rules.
    • Non-compensatory strategies, like sequential evaluation, may be ecologically relevant for animals.
    • Reward attribute evaluation is context-dependent, with volume influencing probability assessment.