Tyramine and its AmTYR1 receptor modulate attention in honey bees (Apis mellifera)

Latshaw, J. S.; Mazade, R. E.; Petersen, M.; Mustard, J. A.; Sinakevitch, I.; Wissler, L.; Guo, X.; Cook, C. N.; Lei, H.; Gadau, J.; Smith, B. H.

doi:10.1101/2022.09.02.506392

bioRxiv · 10.1101/2022.09.02.506392

Tyramine and its AmTYR1 receptor modulate attention in honey bees (Apis mellifera)

Latshaw, J. S.·Mazade, R. E.·Petersen, M.·Mustard, J. A.·Sinakevitch, I.·Wissler, L.·Guo, X.·Cook, C. N.·Lei, H.·Gadau, J.·Smith, B. H.

View original source ↗Export metadata ↓

Abstract

Animals must learn to ignore stimuli that are irrelevant to survival and attend to ones that enhance survival. When a stimulus regularly fails to be associated with an important consequence, subsequent excitatory learning about that stimulus can be delayed, which is a form of non-associative conditioning called latent inhibition. Honey bees show latent inhibition toward an odor they have experienced without association with food reinforcement. Moreover, individual honey bees from the same colony differ in the degree to which they show latent inhibition, and these individual differences have a genetic basis. To investigate the mechanisms that underly individual differences in latent inhibition, we selected two honey bee lines for high and low latent inhibition, respectively. We crossed those lines and mapped a Quantitative Trait Locus (QTL) for latent inhibition to a region of the genome that contains the tyramine receptor gene Amtyr11. We then show that disruption of Amtyr1 signaling either pharmacologically or through RNAi qualitatively changes the expression of latent inhibition but has little effect on appetitive conditioning, and these results suggest that AmTYR1 modulates inhibitory processing in the CNS. Electrophysiological recordings from the brain during pharmacological blockade are consistent with a model that AmTYR1 indirectly regulates Hebbian plasticity at inhibitory synapses in the CNS. Finally, sequencing Amtyr1 and its up and downstream genomic region for high and low line workers suggested that individual differences might arise from variation in transcriptional control rather than structural changes in the coding region. Our results therefore identify a distinct modulatory pathway for this type of non-associative learning, and we propose a model for how it modulates Hebbian plasticity at defined synapses in the CNS. We have shown elsewhere how this modulation also underlies potentially adaptive intracolonial learning differences among individuals that benefit colony survival.

Source connections

Published article ↗

Explore related subjects

animal behavior and cognition Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Latshaw, J. S., Mazade, R. E., Petersen, M., Mustard, J. A., Sinakevitch, I., Wissler, L., Guo, X., Cook, C. N., Lei, H., Gadau, J., Smith, B. H.. 2022-09-05. Tyramine and its AmTYR1 receptor modulate attention in honey bees (Apis mellifera). https://doi.org/10.1101/2022.09.02.506392

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Deconstructing Boldness: Latent behavioural structure across novelty, predation, and exploration in an endangered species translocation program

Risk-related behaviours including neophobia, exploration, and predator avoidance are often assumed to covary along a general boldness axis. Although some translocation studies have linked one or more of these behaviours with fitness, it is possible that the underlying behavioural structure varies under different selective environments. Conservation breeding programs provide a unique opportunity to evaluate the structure of behavioural correlations in a non-domestic species under artificial conditions. We tested whether risk-related behaviours represent a unified boldness syndrome in a captive population of the endangered Attwaters prairie chicken (APC; Tympanuchus cupido attwateri). We quantified the repeatable behaviours of 257 juveniles and compared 11 models of behavioural covariation structure using multivariate mixed models and confirmatory factor analysis. There was no support for a single risk-taking axis; instead, we found three dimensions representing responses to novelty and environmental stimuli (Engagement), predator avoidance (Threat Response), and maze exploration (Maze Progression). Our results indicate that these risk-related behaviours are not organized along a single axis in captive APCs, challenging assumptions that risk-taking represents a universal behavioural syndrome. To anticipate post-release success accurately, conservation managers should understand the exact behavioural architecture of the captive population rather than assume that the classical bold-shy structure occurs in all contexts.

animal behavior and cognition↗

bioRxiv2026

Shared brain transcriptome signatures of social evolution and plasticity in shell-dwelling cichlid fishes

Inter-individual variability in phenotypic traits is widespread in nature both across and within species, with similar patterns of variation often occurring between and within species. Given that these two types of variation are generated by evolutionary and plasticity processes respectively, it raises the question to what extent the causal mechanisms underlying such variability at these two different levels are shared or not. To address this question, we studied the variation in brain transcriptomes in Tanganyikan cichlids that exhibit both intra- and interspecific variation in social behavior. We compared two facultatively social cichlid species, each containing naturally occurring solitary and social-living individuals, with a closely related obligatory solitary resembling the ancestral state. Differential gene expression and Gene Set Enrichment Analyses were performed in the telencephalon and diencephalon transcriptomes to investigate the molecular basis of both behavioral plasticity and the evolution of sociality. Behavioral plasticity involved few differentially expressed genes but extensive changes in biological pathways, supporting a highly polygenic architecture of social behavior. Across both species, social-living individuals consistently upregulated pathways involved in translation, protein homeostasis, and energy metabolism, whereas solitary individuals showed enrichment of neuronal morphogenesis, cell adhesion, and structural plasticity. Remarkably, these same functional programs were associated with the independent evolution of sociality, revealing a strong overlap between evolutionary and plastic transcriptional responses. This convergence was largely restricted to the telencephalon, while the diencephalon showed limited and inconsistent functional signatures. Together, our results support the repeated recruitment of gene regulatory programs during the evolution of sociality and demonstrate that behavioral plasticity and evolutionary transitions share common neurogenomic responses, consistent with a conserved genetic toolkit for social behavior.

animal behavior and cognition↗

bioRxiv2026

Inductive bias anchors a scaling law for biological learning

The speed of animal learning varies substantially across individuals and task domains, and does not always track intuitive notions of task complexity. A nominally simple binary decision task can take thousands of rewards to reach proficiency, whereas seemingly complex naturalistic tasks can be learned within dozens. A long-standing explanation is that learning speed reflects the alignment between an animal's inductive biases and the task at hand. However, without a precise notion of alignment, it is difficult to translate this idea into quantitative predictions. Here, modeling an animal as a Bayesian learner that improves through iterative reward feedback, we use statistical learning theory to derive a scaling law for biological learning. The law makes two predictions. First, inductive bias multiplicatively sets the speed of learning through a single quantity, the effective complexity. This quantity measures how well the task aligns with the animal's prior, and corresponds to the number of bits required to represent the task solution under that prior. We demonstrate this multiplicative scaling in a human motor learning dataset, where behavioral measurements before learning can precisely predict subsequent learning speed. Second, task performance improves as a power law in experience. We validate this power law in a large-scale mouse learning dataset and show that a two-parameter rescaling collapses individual learning curves onto a universal function predicted by the theory. These results suggest that behavioral measurements before learning can be used to predict task-dependent learning speeds, and they explain why learning speed reflects alignment with prior knowledge rather than nominal task complexity.

animal behavior and cognition↗