Transitive inference in
            <i>Polistes</i>
            paper wasps

Tibbetts, Elizabeth A.; Agudelo, Jorge A.; Pandit, Sohini; Riojas, Jessica

doi:10.1098/rsbl.2019.0015

Cited by 53 publications

(45 citation statements)

References 27 publications

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“…In such cases, when selection is stronger on social competence, we additionally predict that the general cognitive system can become specialized to the social domain through the emergence of cognitive abilities especially adapted for social decision‐making. This could be the case, for example, of transitive inference, a cognitive ability that allows animals to recognize dominance hierarchies but that can be useful outside the social domain (MacLean, Merritt, & Brannon, ; Tibbetts, Agudelo, Pandit, & Riojas, ). Animals in this circumstance develop an enhanced cognitive system that although general is also predominantly social (Figure a).…”

Section: The Social Specialization Of the Cognitive Systemmentioning

confidence: 99%

The correlated evolution of social competence and social cognition

2019

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Knowing which of correlated traits are more strongly targeted by selection is crucial to understand the evolutionary process. For example, it could help in understanding how behavioural and cognitive adaptations to social living have evolved. Social competence is the ability of animals to optimize their social behaviours according to the demands of their social environment. It is a behavioural performance trait that expresses how well a whole organism performs complex social tasks, such as choosing mates, raising offspring, participating in dominance hierarchies, solving conflicts or forming social bonds. Non‐social competence, on the other hand, is the ability of animals to optimize their non‐social behaviours according to the demands of their non‐social environment, such as finding food or avoiding predators. Social and non‐social cognition are correlated lower‐level traits of social and non‐social competence, respectively, encompassing the underlying psychological and neural mechanisms of behaviour that allow animals to acquire, encode, store and recall information about their social and non‐social environments. Here, we employ the theoretical framework that selection acts on performance traits first and on lower‐level traits only secondarily, to propose a new approach to the study of the evolution of social cognition. We hypothesize that when selection favours social competence, the cognitive system becomes more adapted to the social domain, making species biased for social information, and increasing their degree of sociality. The opposite can happen when selection favours non‐social competence. The level of specialization that the cognitive system can attain depends on whether social and non‐social competence are correlated with the same cognitive lower‐level traits. This in turn will determine whether species will evolve a type of social cognition that is general—that contributes with cognitive abilities that can be used in both social and non‐social environments—or modular—that contributes with cognitive abilities that are specific to the social environment. A free Plain Language Summary can be found within the Supporting Information of this article.

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Section: The Social Specialization Of the Cognitive Systemmentioning

confidence: 99%

The correlated evolution of social competence and social cognition

2019

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“…This is, of course, not evidence bees or other insects cannot rank. As we noted above, Polistes wasps have solved a transitive inference task that controlled for reinforcement history [13] suggesting a capacity to compare and rank. Honey bees, however, failed at a similar task [63].…”

Section: Discussionmentioning

confidence: 94%

Honeybees solve a multi-comparison ranking task by probability matching

2020

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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.

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“…This is, of course, not evidence bees or other insects cannot rank. As we noted above, Polistes wasps have solved a transitive inference task that controlled for reinforcement history [12] suggesting a capacity to compare and rank. Honey bees, however, failed at a similar task [55].…”

Section: Discussionmentioning

confidence: 94%

“…Probability maximising requires a capacity to compare the value of different options and to rank them accordingly. Until recently this kind of cognition was presumed to be too complex for insects, but bees do have the capacity to learn abstract relationships between stimuli [9][10][11], and a recent study with Polistes wasps showed the wasps could pass a behavioural test considered indicative of the capacity for transitive inference [12]. This requires arranging stimuli in a ranked order [12] suggesting that Polistes dominula and Polistes metricus at least have a capacity for ranking of stimuli.…”

Section: Introductionmentioning

confidence: 99%

Honey bees solve a multi-comparison ranking task by probability matching

MaBouDi

Marshall

Barron

2020

Preprint

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Honey bees forage on a range of flowers, all of which can vary unpredictably in the amount and type of rewards they offer. In this environment bees are challenged with maximising 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 challenged bees with a fivecomparison 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 matching their preferences to their history of reinforcement for each colour. We used a computational model to explore the feasibility of this probability matching strategy for the honey bee brain. The model suggested a structure like the honey bee mushroom body with reinforcement-related plasticity at both input and output was 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 utility and limitations of this simple cognitive strategy for foraging animals.

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Transitive inference in Polistes paper wasps

Cited by 53 publications

References 27 publications

The correlated evolution of social competence and social cognition

The correlated evolution of social competence and social cognition

Honeybees solve a multi-comparison ranking task by probability matching

Honey bees solve a multi-comparison ranking task by probability matching

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