Evidence map›Paper›PMID 37063993›Full record

ArticleRoyal Society open science2023

Observing a trained demonstrator influences associative appetitive learning in rats.

Laura A Agee, Miriam E Ortega, Hongjoo J Lee, Marie-H Monfils

Abstract read
In one paragraph

Article in Royal Society open science, 2023. 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. Review
  2. 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

4 authors.

Laura A AgeeDepartment of Psychology, The University of Texas at Austin, 108 E. Dean Keeton Stop A8000, Austin, TX 78712-1043, USA.
Miriam E OrtegaDepartment of Psychology, The University of Texas at Austin, 108 E. Dean Keeton Stop A8000, Austin, TX 78712-1043, USA.
Hongjoo J LeeDepartment of Psychology, The University of Texas at Austin, 108 E. Dean Keeton Stop A8000, Austin, TX 78712-1043, USA.
Marie-H MonfilsDepartment of Psychology, The University of Texas at Austin, 108 E. Dean Keeton Stop A8000, Austin, TX 78712-1043, USA.ORCID 0000-0001-8971-6651

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to acquire information about the environment through social observation or instruction is an essential form of learning in humans and other animals. Here, we assessed the ability of rats to acquire an association between a light stimulus and the presentation of a reward that is either hidden (sucrose solution) or visible (food pellet) via observation of a trained demonstrator. Subsequent training of observers on the light-reward association indicated that while observation alone was not sufficient for observers to acquire the association, contact with the reward location was higher in observers that were paired with a demonstrator. However, this was only true when the light cue predicted a sucrose reward. Additionally, we found that in the visible reward condition, levels of demonstrator orienting and food cup contact during the observation period tended to be positively correlated with the corresponding behaviour of their observer. This relationship was only seen during later sessions of observer training. Together, these results suggest that while our models were not sufficient to induce associative learning through observation alone, demonstrator behaviour during observation did influence how their paired observer's behavioural response to the cue evolved over the course of direct individual training.

Indexed as

appetitive social learningassociative learningobservational learningsocial learning

Identifiers

PMID37063993
PMCPMC10090881

What OpenQuestion holds

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Registered trials

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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.