University of Oulu

MaBouDi, H., Barron, A. B., Li, S., Honkanen, M., Loukola, O. J., Peng, F., Li, W., Marshall, J. A. R., Cope, A., Vasilaki, E., & Solvi, C. (2021). Non-numerical strategies used by bees to solve numerical cognition tasks. Proceedings of the Royal Society B: Biological Sciences, 288(1945), 20202711.

Non-numerical strategies used by bees to solve numerical cognition tasks

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Author: MaBouDi, HaDi1; Barron, Andrew B.1,2; Li, Sun3;
Organizations: 1Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK
2Department of Biological Sciences, Macquarie University, North Ryde, New South Wales 2109, Australia
3Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, People's Republic of China
4Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
5Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Institute of Zoology, Guangdong Academy of Science, Guangzhou, People's Republic of China
6School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
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Language: English
Published: The Royal Society, 2021
Publish Date: 2021-02-22


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.

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Series: Proceedings of the Royal Society. B, Biological sciences
ISSN: 0962-8452
ISSN-E: 1471-2954
ISSN-L: 0962-8452
Volume: 288
Issue: 1945
Article number: 20202711
DOI: 10.1098/rspb.2020.2711
Type of Publication: A1 Journal article – refereed
Field of Science: 1181 Ecology, evolutionary biology
Funding: This study was supported by the EPSRC programme grant Brains-on-Board (EP/P006094/1) awarded to J.A.R.M. and E.V. A.B.B. and J.A.R.M. were supported by a Leverhulme visiting professorship. A.B.B. and C.S. were supported by the Templeton World Charity Foundation project number TWCF0266. F.P. was supported by the National Natural Science Foundation of China (Project no. 31700988). O.J.L. was supported by The Academy of Finland, grant no. 309995.
Academy of Finland Grant Number: 309995
Detailed Information: 309995 (Academy of Finland Funding decision)
Dataset Reference: The data supporting the findings of this study (figure 1f–j, figure 2b and figure 3b–e), the code necessary for the model, and the code for measuring the continuous visual features of the stimuli are available in the public repository figshare at
Copyright information: © 2021 The Author(s). Published by the Royal Society. All rights reserved.