How honey bees make fast and accurate decisions

Abstract

Honey bee ecology demands they make both rapid and accurate assessments of which flowers are most likely to offer them nectar or pollen. To understand the mechanisms of honey bee decision-making, we examined their speed and accuracy of both flower acceptance and rejection decisions. We used a controlled flight arena that varied both the likelihood of a stimulus offering reward and punishment and the quality of evidence for stimuli. We found that the sophistication of honey bee decision-making rivalled that reported for primates. Their decisions were sensitive to both the quality and reliability of evidence. Acceptance responses had higher accuracy than rejection responses and were more sensitive to changes in available evidence and reward likelihood. Fast acceptances were more likely to be correct than slower acceptances; a phenomenon also seen in primates and indicative that the evidence threshold for a decision changes dynamically with sampling time. To investigate the minimally sufficient circuitry required for these decision-making capacities, we developed a novel model of decision-making. Our model can be mapped to known pathways in the insect brain and is neurobiologically plausible. Our model proposes a system for robust autonomous decision-making with potential application in robotics.

Motivational modulation of flight speed in foraging bumblebees

“…This contrasts with other studies investigating the temporal aspects of decision-making in which latency before choice was influenced by the detectability and properties of the stimuli, or what bees had learned about them (e.g. (24,(39)(40)(41)(42)). Reducing the complexity of this classical foraging task was aimed to ensure that potential changes in flying behaviour could be interpreted as reflecting the effects of reward value and predictability on decision-making.…”

“…Two often overlooked factors are the time dimension of decision-making (97) and, as shown here, behavioural vigour. The present results suggest that studying the flight parameters of foraging bees, which involves both of these factors, may help study the different valuation subsystems involved in decision-making (see also (40)). By dissociating the effects of the liking and wanting components of motivation, this type of analysis offers a potential way forward to a long lasting problem in insect cognitive studies (66).…”

How bumblebees manage conflicting information seen on arrival and departure from flowers

“…The mushroom body alone is not a decision maker (Galizia 2014, Bhazenov et al 2013, Huerta et al 2004. It can perhaps best be thought of a as a classi er -learning to associate presented stimuli with different outcomes which are conveyed by mushroom body output neurons to premotor regions (Galizia 2014, Maboudi et al 2023). The punished stimuli were consistent in all groups therefore the rate of learning to avoid the CS-would be the same in all groups.…”

Future avenues inDrosophilamushroom body research

“…Developing better tools to record neural activity while animals learn via instrumental or classical conditioning could provide unique insights into how individual neurons function distinctly in these contexts. These tool advancements could also promote our understanding of Drosophila larval ( Saumweber et al 2018 ; Wong et al 2021 ; Thoener et al 2022 ) and bee learning ( Pahlke et al 2021 ; Lafon et al 2022 ; MaBouDi et al 2023 ). Delineating how individual identifiable neurons function in different learning contexts could allow us to develop targeted treatments when animals exhibit maladaptive behavioral motivation (e.g., consuming drugs to the point of intoxication).…”