4.7 Article

Aversive view memories and risk perception in navigating ants

期刊

SCIENTIFIC REPORTS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-022-06859-4

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资金

  1. Mitacs Globalink Research Award
  2. Natural Sciences and Engineering Research Council of Canada [04133, 2020-03933]
  3. European Research Council [ERCstg: EMERG-ANT 759817]

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Ants establish foraging routes through learning views of the visual panorama. They rapidly learn and perceive aversive views, which trigger changes in behavior. A logarithmic relationship between captivity duration and hesitations suggests how aversive view learning could be executed within the mushroom bodies circuitry.
Many ants establish foraging routes through learning views of the visual panorama. Route models have focused primarily on attractive view use, which experienced foragers orient towards to return to known sites. However, aversive views have recently been uncovered as a key component of route learning. Here, Cataglyphis velox rapidly learned aversive views, when associated with a negative outcome, a period of captivity in vegetation, triggering increases in hesitation behavior. These memories were based on the accumulation of experiences over multiple trips with each new experience regulating forager hesitancy. Foragers were also sensitive to captivity time differences, suggesting they possess some mechanism to quantify duration. Finally, we analyzed foragers' perception of risky (i.e. variable) versus stable aversive outcomes by associating two sites along the route with distinct captivity schedules, a fixed or variable duration, with the same mean across training. Foragers exhibited fewer hesitations in response to risky outcomes compared to fixed ones, indicating they perceived risky outcomes as less severe. Results align with a logarithmic relationship between captivity duration and hesitations, suggesting that aversive stimulus perception is a logarithm of its actual value. We discuss how aversive view learning could be executed within the mushroom bodies circuitry following a prediction error rule.

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