Statistical olfactory learning in honey bees
Year: 2025
Type: article
Abstract: Statistical learning is a cognitive process for detecting regularities in sensory inputs typically presented as strings of sounds, shapes, or objects, enabling species to predict future events, thereby guiding decision-making and behavior. Such an adaptive trait has been demonstrated in vertebrates, including human and non-human primates, birds, and dogs. It remains unclear whether invertebrates, which possess smaller and simpler neural systems than vertebrates, can extract statistical information from sensory inputs. Here, we show for the first time that honey bees are able to learn and recall the temporal (statistical) structure of an olfactory stimulus. These results suggest that statistical learning is a fundamental component of a conserved cognitive toolkit present, even in invertebrates.
Source: iScience
Institutions: Université de Tours, Centre National de la Recherche Scientifique, Inserm, Sorbonne Université, Institut de Biologie Paris-Seine, Institut de Recherche sur la Biologie de l'Insecte UMR 7261, Neuro-SU, Institut de Recerca Sant Joan de Déu, Université de Bourgogne, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Institut Agro Dijon, Centre des Sciences du Goût et de l'Alimentation
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,240
Awards: Gates to Language, G8460384808
OpenAlex ID: W4414568907
