MaBouDi, H. orcid.org/0000-0002-7612-6465, Barron, A.B., Li, S. et al. (8 more authors) (2021) Non-numerical strategies used by bees to solve numerical cognition tasks. Proceedings of the Royal Society B: Biological Sciences, 288 (1945). 20202711. ISSN 0962-8452
Abstract
We examined how bees solve a visual discrimination task with stimuli commonly used in numerical cognition studies. Bees performed well on the task, but additional tests showed that they had learned continuous (non-numerical) cues. A network model using biologically plausible visual feature filtering and a simple associative rule was capable of learning the task using only continuous cues inherent in the training stimuli, with no numerical processing. This model was also able to reproduce behaviours that have been considered in other studies indicative of numerical cognition. Our results support the idea that a sense of magnitude may be more primitive and basic than a sense of number. Our findings highlight how problematic inadvertent continuous cues can be for studies of numerical cognition. This remains a deep issue within the field that requires increased vigilance and cleverness from the experimenter. We suggest ways of better assessing numerical cognition in non-speaking animals, including assessing the use of all alternative cues in one test, using cross-modal cues, analysing behavioural responses to detect underlying strategies, and finding the neural substrate.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Author(s). Published by the Royal Society. This is an author-produced version of a paper subsequently published in Proceedings of the Royal Society B: Biological Sciences. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | animal cognition; accumulator model; spatial frequency; magnitude; inhibition of return |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/P006094/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Feb 2021 16:19 |
Last Modified: | 24 Feb 2021 16:19 |
Status: | Published |
Publisher: | The Royal Society |
Refereed: | Yes |
Identification Number: | 10.1098/rspb.2020.2711 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:171533 |