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Non-numerical strategies used by bees to solve numerical cognition tasks
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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934903/ https://www.ncbi.nlm.nih.gov/pubmed/33593192 http://dx.doi.org/10.1098/rspb.2020.2711 |
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author | MaBouDi, HaDi Barron, Andrew B. Li, Sun Honkanen, Maria Loukola, Olli J. Peng, Fei Li, Wenfeng Marshall, James A. R. Cope, Alex Vasilaki, Eleni Solvi, Cwyn |
author_facet | MaBouDi, HaDi Barron, Andrew B. Li, Sun Honkanen, Maria Loukola, Olli J. Peng, Fei Li, Wenfeng Marshall, James A. R. Cope, Alex Vasilaki, Eleni Solvi, Cwyn |
author_sort | MaBouDi, HaDi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7934903 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-79349032021-09-13 Non-numerical strategies used by bees to solve numerical cognition tasks MaBouDi, HaDi Barron, Andrew B. Li, Sun Honkanen, Maria Loukola, Olli J. Peng, Fei Li, Wenfeng Marshall, James A. R. Cope, Alex Vasilaki, Eleni Solvi, Cwyn Proc Biol Sci Neuroscience and Cognition 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. The Royal Society 2021-02-24 2021-02-17 /pmc/articles/PMC7934903/ /pubmed/33593192 http://dx.doi.org/10.1098/rspb.2020.2711 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Neuroscience and Cognition MaBouDi, HaDi Barron, Andrew B. Li, Sun Honkanen, Maria Loukola, Olli J. Peng, Fei Li, Wenfeng Marshall, James A. R. Cope, Alex Vasilaki, Eleni Solvi, Cwyn Non-numerical strategies used by bees to solve numerical cognition tasks |
title | Non-numerical strategies used by bees to solve numerical cognition tasks |
title_full | Non-numerical strategies used by bees to solve numerical cognition tasks |
title_fullStr | Non-numerical strategies used by bees to solve numerical cognition tasks |
title_full_unstemmed | Non-numerical strategies used by bees to solve numerical cognition tasks |
title_short | Non-numerical strategies used by bees to solve numerical cognition tasks |
title_sort | non-numerical strategies used by bees to solve numerical cognition tasks |
topic | Neuroscience and Cognition |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934903/ https://www.ncbi.nlm.nih.gov/pubmed/33593192 http://dx.doi.org/10.1098/rspb.2020.2711 |
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