Evidence map›Paper›PMID 33593192›Full record

ArticleProceedings. Biological sciences2021

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 and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Proceedings. Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.4field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
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  9. Article
  10. An insect brain organizes numbers on a left-to-right mental number line.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  11. Illusional Perspective across Humans and Bees.Vision (Basel, Switzerland) · 2022
    Review
  12. Article
  13. Review
  14. Article
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 4 countries.

HaDi MaBouDiDepartment of Computer Science, University of Sheffield, Sheffield S1 4DP, UK.
Andrew B BarronDepartment of Computer Science, University of Sheffield, Sheffield S1 4DP, UK.
Sun LiDepartment of Psychology, School of Public Health, Southern Medical University, Guangzhou, People's Republic of China.
Maria HonkanenEcology and Genetics Research Unit, University of Oulu, Oulu, Finland.
Olli J LoukolaEcology and Genetics Research Unit, University of Oulu, Oulu, Finland.
Fei PengDepartment of Psychology, School of Public Health, Southern Medical University, Guangzhou, People's Republic of China.
Wenfeng LiGuangdong 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.
James A R MarshallDepartment of Computer Science, University of Sheffield, Sheffield S1 4DP, UK.
Alex CopeDepartment of Computer Science, University of Sheffield, Sheffield S1 4DP, UK.
Eleni VasilakiDepartment of Computer Science, University of Sheffield, Sheffield S1 4DP, UK.
Cwyn SolviDepartment of Biological Sciences, Macquarie University, North Ryde, New South Wales 2109, Australia.
University of Sheffield · GBSouthern Medical University · CNUniversity of Oulu · FIInstitute of Zoology · CNQueen Mary University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

CognitionLearningAnimalsBeesCuesDiscrimination, PsychologicalVisual Perceptionaccumulator modelanimal cognitioninhibition of returnmagnitudespatial frequency

Identifiers

PMID33593192
PMCPMC7934903
OpenAlexW3129424131

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.