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

HaDi MaBouDi, Andrew B. Barron, Sun Li, Maria Honkanen, Olli J. Loukola, Fei Peng, Wenfeng Li, James A. R. Marshall, Alex Cope, Eleni Vasilaki, Cwyn Solvi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Article number20202711
Pages (from-to)1-10
Number of pages10
JournalProceedings of the Royal Society B: Biological Sciences
Volume288
Issue number1945
DOIs
Publication statusPublished - 24 Feb 2021

Keywords

  • accumulator model
  • animal cognition
  • inhibition of return
  • magnitude
  • spatial frequency

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