Data for 'Honeybees solve a multi-comparison ranking task by probability matching'

Honeybees forage on diverse flowers which vary in the amount and type of rewards they offer, and bees are challenged with maximizing the resources they gather for their colony. That bees are effective foragers is clear, but how bees solve this type of complex multi-choice task is unknown. Here, we set bees a five-comparison choice task in which five colours differed in their probability of offering reward and punishment. The colours were ranked such that high ranked colours were more likely to offer reward, and the ranking was unambiguous. Bees’ choices in unrewarded tests matched their individual experiences of reward and punishment of each colour, indicating bees solved this test not by comparing or ranking colours but by basing their colour choices on their history of reinforcement for each colour. Computational modelling suggests a structure like the honeybee mushroom body with reinforcement-related plasticity at both input and output can be sufficient for this cognitive strategy.We discuss how probability matching enables effective choices to be made without a need to compare any stimuli directly, and the use and limitations of this simple cognitive strategy for foraging animals.

蜜蜂会在种类繁多的花朵间觅食，不同花朵提供的奖赏数量与类型存在差异，而蜜蜂面临的核心挑战是为其蜂群最大化采集到的资源。蜜蜂是高效的觅食者已是不争的事实，但蜜蜂如何完成这类复杂的多选择觅食任务，其背后的认知机制仍未明确。本研究中，我们为蜜蜂设计了一项五色彩对比选择任务：五种颜色分别对应不同的奖励与惩罚概率，且排名规则清晰明确——排名越高的颜色，获得奖励的概率也越高。在无奖励测试环节中，蜜蜂的选择与其自身对每种颜色的奖惩经历高度吻合，这表明蜜蜂并非通过比较或排序颜色来完成任务，而是基于每种颜色对应的强化历史来做出颜色选择。计算建模结果显示，一种类似蜜蜂蕈形体（mushroom body）、且在输入与输出通路均具备与强化相关的突触可塑性的神经结构，足以支撑该认知策略的实现。我们还探讨了概率匹配如何使动物无需直接比较任何刺激即可做出高效选择，以及这种简单认知策略在觅食动物中的应用场景与局限性。