Evidence map›Paper›PMID 39092671›Full record

ArticleThe Journal of experimental biology2024

Brain energy metabolism as an underlying basis of slow and fast cognitive phenotypes in honeybees.

Catherine Tait, Adam J Chicco, Dhruba Naug

Abstract read
In one paragraph

Article in The Journal of experimental biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Cognitive individual differences are key in the network of trait covariance.Behavioral ecology : official journal of the International Society for Behavioral Ecology
    Article
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

3 authors.

Catherine TaitDepartment of Biology, Colorado State University, Fort Collins, CO 80523, USA.
Adam J ChiccoDepartment of Biomedical Sciences, Colorado State University, Fort Collins, CO 80523, USA.
Dhruba NaugDepartment of Biology, Colorado State University, Fort Collins, CO 80523, USA.ORCID 0000-0001-9252-8037

Funding

Foundation for Food and Agricultural ResearchNational Science FoundationNational Science Foundation, U.S.A.
6 · The paper itself

Abstract

In the context of slow-fast behavioral variation, fast individuals are hypothesized to be those who prioritize speed over accuracy while slow individuals are those which do the opposite. Since energy metabolism is a critical component of neural and cognitive functioning, this predicts such differences in cognitive style to be reflected at the level of the brain. We tested this idea in honeybees by first classifying individuals into slow and fast cognitive phenotypes based on a learning assay and then measuring their brain respiration with high-resolution respirometry. Our results broadly show that inter-individual differences in cognition are reflected in differences in brain mass and accompanying energy use at the level of the brain and the whole animal. Larger brains had lower mass-specific energy usage and bees with larger brains had a higher metabolic rate. These differences in brain respiration and brain mass were, in turn, associated with cognitive differences, such that bees with larger brains were fast cognitive phenotypes whereas those with smaller brains were slow cognitive phenotypes. We discuss these results in the context of the role of energy in brain functioning and slow-fast decision making and speed accuracy trade-off.

Indexed as

BrainCognitionEnergy MetabolismPhenotypeAnimalsBeesBehavior, AnimalOrgan SizeBrain respirationCognitive phenotypesHoneybeeMetabolic rateSlow–fast variationSpeed accuracy trade-off

Identifiers

PMID39092671
PMCPMC11418170

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.