Honey bees selectively avoid difficult choices

C. J. Perry, A. B. Barron
2013 Proceedings of the National Academy of Sciences of the United States of America  
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
more » ... 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. O ften a correct choice can only be estimated rather than absolutely known. To aid in this estimation, humans are able to monitor their degree of uncertainty and use that knowledge to improve their decisions (1, 2). The ability to monitor one's own cognitive processes is considered a form of metacognition (1, 2). When uncertain, humans will often defer choosing and seek more information rather than risk the consequences of a wrong choice. Whether the ability to monitor uncertainty exists in nonhuman animals is currently highly contentious. Smith et al. (3, 4) developed the opt-out paradigm to test uncertainty monitoring in animals in which an animal must solve a discrimination task that varies in difficulty. The animal is rewarded when correct and punished for an incorrect choice. A third option is then introduced where the animal can "opt out" by responding in some different way to avoid the discrimination task, thereby usually beginning a new trial. If animals opt out more on difficult than easy tasks, if opting out improves performance on difficult tasks, and if they can apply the opt-out strategy to a novel task, then this has been taken as evidence that animals can modify their decision-making strategy based on their degree of uncertainty. This result has been reported for nonhuman primates, dolphins, dogs, and rats (3-12). However, some strongly argue that all comparative studies using opt-out paradigms can be explained through associative mechanisms that do not require judgments of uncertainty (3, 13-15). Because two alternative mechanisms have been proposed to explain the same behavioral data, Morgan's Canon (16) cautions that when presented with two alternative explanations, we are obliged to choose the simpler of the two. However, directly comparing these hypotheses is difficult because there is no agreed neural model for uncertainty processing. Therefore, it is challenging to judge which explanation is truly the simpler. Here we contribute to the debate by examining how an invertebrate, the honey bee, performed in the opt-out paradigm. We found that bees met all of the necessary criteria considered indicative of uncertainty monitoring. Bees have a far smaller brain than any mammal, and we hypothesize how uncertainty monitoring might be achieved by this animal. Results To assess how honey bees responded to choices based on limited information, we examined their performance in a visual discrimination task in which task difficulty was varied. We combined a configural-learning task, where bees had to learn stimuli placed above or below a referent (17) , with the option to opt out of trials (5) to determine if bees adaptively changed behavior in response to task difficulty. We trained free-flying bees to enter a two-chamber test apparatus (Fig. 1) . During training, stimuli were placed either in the first decision chamber or the second. During testing, both chambers contained stimuli. The stimuli were two variable targets that were positioned either above or below a reference bar (cf. ref. 17) (Fig. 1B) . One group of bees was trained that the above target contained 2 M sucrose (reward) and the below target contained 50 mM quinine (punishment) (18). For the second group, the contingency was reversed. During this stage, bees were trained with five different targets that differed in shape, size, and color. We changed targets and vertical position of targets and reference bars pseudorandomly to eliminate the possible use of associative cues. In other words, the shape, color, and size of targets changed from trial to trial and the distance of the targets from the bottom of the chamber and with respect to the reference bars varied from trial to trial. This format ensured that low-level cues, such as cumulated area (the area covered by both reference bar and target) or configural identity (the shape and orientation of both target and reference bar together), were not informative for solving the task (Fig. 1B) (17) . Bees' performance increased over six blocks of five trials ( Fig. 2A) (ANOVA for repeated measures; n = 33 bees; block effect: F 5, 155 = 18.127, P < 0.001). There was no difference in performance between below-and above-trained groups (F 1, 31 = 0.422, Significance Here we show that honey bees (Apis mellifera) can adaptively alter their behavior in a choice test in response to trial difficulty. Bees preferentially opt out of difficult trials and by doing so, improve their success rate. We discuss whether this choice involves assessing degree of uncertainty (considered a definition of basic metacognition) or whether this task might be solved by associative mechanisms. We propose a hypothesis for how uncertainty might be processed within the known circuitry of the insect brain to frame the concept of uncertainty as a topic for neurobiological analysis.
doi:10.1073/pnas.1314571110 pmid:24191024 pmcid:PMC3839751 fatcat:x7ii4rkbdzawtios27yii2yula