| Literature DB >> 33593192 |
HaDi MaBouDi1, Andrew B Barron1,2, Sun Li3, Maria Honkanen4, Olli J Loukola4, Fei Peng3, Wenfeng Li5, James A R Marshall1, Alex Cope1, Eleni Vasilaki1, Cwyn Solvi2,6.
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.Entities:
Keywords: accumulator model; animal cognition; inhibition of return; magnitude; spatial frequency
Mesh:
Year: 2021 PMID: 33593192 PMCID: PMC7934903 DOI: 10.1098/rspb.2020.2711
Source DB: PubMed Journal: Proc Biol Sci ISSN: 0962-8452 Impact factor: 5.349