PNAS：美国科学家发现蜜蜂会选择性避免困难抉择

美国亚利桑那州立大学的研究人员Clint Perry 和Andrew Barron最新研究发现，当蜜蜂没有足够的信息去解决一个问题的时候，它们和人类一样，会避免困难的决定。相关文章发表于2013年11月4日的《PNAS》杂志上。

PNAS：美国科学家发现蜜蜂会选择性避免困难抉择

长久以来，科研人员知道人类依赖于元认知的力量在做出一个决定之前去衡量他们对于一个决定的确定程度，但是不清楚动物是否有类似的能力。

Clint Perry 和Andrew Barron通过评估蜜蜂(Apis melLifera)在一个视觉分辨任务中如何对基于有限信息的决定做出响应，从而探索了这个问题。

研究小组训练了自由飞行的蜜蜂进入一个两室结构，在每一个室内提供了各种形状、尺寸、颜色和位置的两种类型的目标——一个甜的“奖赏”和一个苦的“惩罚”。在

难度有变化的一系列的实验中，这些蜜蜂选择从这些目标中定位那个甜的奖赏。这些蜜蜂因为正确的选择而得到奖赏，因为错误的选择而得到惩罚，或者通过退出试验而避免选择。这些发现揭示出了当缺乏足够的信息的时候，蜜蜂优先选择退出困难的试验，因此就改善了它们的成功率。

研究人员称，这项研究提示甚至是无脊椎动物也可能有能力做出复杂而具有适应性的决定。

原文摘要：

Honey bees selectively avoid difficult choICEs

Clint J. Perry and Andrew B. Barron

human decision-making strategies are strongly influenced by an awareness of certainty or uncertainty (a form of metacognition) to increase the chances of making a right choice. Humans seek more information and defer choosing when they realize they have insufficient information to make an accurate decision， but whether animals are aware of uncertainty is currently highly contentious. To explore this issue， we examined how honey bees (Apis mellifera) responded to a visual discrimination task that varied in difficulty between trials. Free-flying bees were rewarded for a correct choice， punished for an incorrect choice， or could avoid choosing by exiting the trial (opting out). Bees opted out more often on difficult trials， and opting out improved their proportion of successful trials. Bees could also transfer the concept of opting out to a novel task. Our data show that bees selectively avoid difficult tasks they lack the information to solve. This finding has been considered as evidence that nonhuman animals can assess the certainty of a predicted outcome， and bees’ performance was comparable to that of primates in a similar paradigm. We discuss whether these behavioral results prove bees react to uncertainty or whether associative mechanisms can explain such findings. To better frame metacognition as an issue for neuroBioLogical investigation， we propose a neurobiological hypothesis of uncertainty monitoring based on the known circuitry of the honey bee brain.

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