Biology subjects

Barron, A. B.

Publications and source records attributed to Barron, A. B..

7 recordsLinked to original sources

bioRxiv2026

Hoverfly responses to looming stimuli depend on elevation and speed

An object on immediate collision course generates a rapidly expanding visual stimulus on the retina, which will typically trigger a fast reaction, such as an evasive behavior. In hoverflies, for example, visual looming stimuli may be generated if the insect is about to collide with a stationary object in the surround, by an approaching predator, or by conspecifics during territorial interactions. Supporting these behavioral responses is a diverse range of looming sensitive descending neurons that project information from the optic lobes and central brain to the motor control centers in the thoracic ganglia. We here show that the looming sensitive descending neurons are predominantly sensitive to looming stimuli located in the ventral visual field. To investigate if this is matched by behavior, we recorded how tethered hoverflies responded to looming stimuli presented dorsally or ventrally on a visual monitor, at four different speeds (l/|v| of 10 - 667 ms), covering a naturalistic range. We found that ventral stimuli, especially at intermediate speeds (l/|v| = 50 or 200 ms), triggered much stronger behavioral responses than dorsally displayed stimuli. The behavioral data thus not only match the receptive fields of the neurons likely to support the behavior, but also highlight that behavioral output is not entirely reflexive but is strongly modulated by stimulus speed and elevation. Significance StatementIf someone throws a ball at you, this generates a rapidly expanding object across your visual field, which will make you react before you have even had time to think. You may for example duck, dip or dive to avoid the ball, or bring your hands up to grab it. Similarly, many insects respond to rapidly approaching objects. We here show that hoverfly reactions to such looming stimuli depend on stimulus speed and elevation, with the strongest response to stimuli approaching from below. We further demonstrate that the neurons likely supporting these behaviors show highest sensitivity in the ventral visual field, suggesting a close match between neural tuning and behavioral output.

animal behavior and cognition↗

bioRxiv2023

How honey bees make fast and accurate decisions

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.

neuroscience↗

bioRxiv2022

Bumblebees retrieve only the ordinal ranking of foraging options when comparing memories obtained in distinct settings

Are animals preferences determined by absolute memories for options (e.g., reward sizes) or by their remembered ranking (better/worse)? The only studies examining this question suggest humans and starlings utilize memories for both absolute and relative information. We show that bumblebees make decisions using only memories of ordinal comparisons. After learning to discriminate pairs of different flowers by sucrose concentration, bumblebees preferred flowers (in novel pairings) with 1) higher ranking over equal absolute reward, 2) higher ranking over higher absolute reward, and 3) identical qualitative ranking but different quantitative ranking equally. Despite these suboptimal choices, bumblebees found the optimal option in an ecologically relevant foraging task. Our results illuminate a divergent mechanism of learned preferences that may have arisen from adaptations to bumblebees natural environment.

animal behavior and cognition↗

bioRxiv2021

Extent and complexity of RNA processing in the development of honey bee queen and worker castes revealed by Nanopore direct RNA sequencing

The distinct honey bee (Apis mellifera) worker and queen castes have become a model for the study of genomic mechanisms of phenotypic plasticity. Prior studies have explored differences in gene expression and methylation during development of the two castes, but thus far no study has performed a genome-wide analysis of differences in RNA processing. To address this here we performed a Nanopore-based direct RNA sequencing with exceptionally long reads to compare the mRNA transcripts between honey bee queen and workers at three points during their larval development. We found thousands of significantly differentially expressed isoforms (DEIs) between queen and worker larvae. Most DEIs contained alternative splicing, and many of them contained at least two types of alternative splicing patterns, indicating complex RNA processing in honey bee caste differentiation. We found a negative correlation between poly(A) length and DEI expression, suggesting that poly(A) tails participate in the regulation of isoform expression. Hundreds of isoforms uniquely expressed in either queens or workers during their larval development, and isoforms were expressed at different points in queen and worker larval development demonstrating a dynamic relationship between isoform expression and developmental mechanisms. These findings show the full complexity of RNA processing and transcript expression in honey bee phenotypic plasticity.

developmental biology↗

bioRxiv2020

Heavy metal pollutants have additive negative effects on honey bee cognition

Environmental pollutants can exert sublethal deleterious effects on animals. These include disruption of cognitive functions underlying crucial behaviours. While agrochemicals have been identified as a major threat to pollinators, other compounds, such as heavy metals that are often found in complex mixtures, have largely been overlooked. Here, we assessed the impact of acute exposure to field-realistic concentrations of lead, copper, arsenic, and their combinations, on honey bee learning and memory. All treatments involving single metals slowed down appetitive learning and disrupted memory retrieval at 24 h. Importantly, combinations of these metals induced additive negative effects on both processes, suggesting common pathways of toxicity. Our results highlight the need to further assess the risks of heavy metal pollution on invertebrates and to their associated ecosystem services. Summary statementHoney bees displayed reduced learning and memory performances following acute exposure to arsenic, copper or lead. Exposure to combinations of these metals induced additive effects.

animal behavior and cognition↗

bioRxiv2020

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

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 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 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.

animal behavior and cognition↗

bioRxiv2018

Abstract concept learning in a simple neural network inspired by the insect brain

The capacity to learn abstract concepts such as sameness and difference is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly have this capacity. Here we report a model of the structures of the honey bee brain that can learn same-ness and difference, as well as a range of complex and simple associative learning tasks. Our model is constrained by the known connections and properties of the mushroom body, including the protocerebral tract, and provides a good fit to the learning rates and performances of real bees in all tasks, including learning sameness and difference. The model proposes a novel mechanism for learning the abstract concepts of sameness and difference that is compatible with the insect brain, and is not dependent on top-down or executive control processing.

neuroscience↗