MaBouDi, H. orcid.org/0000-0002-7612-6465, Galpayage Dona, H.S., Gatto, E. et al. (5 more authors) (2020) Bumblebees use sequential scanning of countable items in visual patterns to solve numerosity tasks. Integrative and Comparative Biology, 60 (4). pp. 929-942. ISSN 1540-7063
Abstract
Most research in comparative cognition focuses on measuring if animals manage certain tasks; fewer studies explore how animals might solve them. We investigated bumblebees’ scanning strategies in a numerosity task, distinguishing patterns with two items from four and one from three, and subsequently transferring numerical information to novel numbers, shapes, and colors. Video analyses of flight paths indicate that bees do not determine the number of items by using a rapid assessment of number (as mammals do in “subitizing”); instead, they rely on sequential enumeration even when items are presented simultaneously and in small quantities. This process, equivalent to the motor tagging (“pointing”) found for large number tasks in some primates, results in longer scanning times for patterns containing larger numbers of items. Bees used a highly accurate working memory, remembering which items have already been scanned, resulting in fewer than 1% of re-inspections of items before making a decision. Our results indicate that the small brain of bees, with less parallel processing capacity than mammals, might constrain them to use sequential pattern evaluation even for low quantities.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
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: | 23 Mar 2022 17:08 |
Last Modified: | 23 Mar 2022 17:16 |
Status: | Published |
Publisher: | Oxford University Press (OUP) |
Refereed: | Yes |
Identification Number: | 10.1093/icb/icaa025 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185033 |