Evidence map›Paper›PMID 39415602›Full record

ArticleJournal of fish biology2025

A framework for a low-cost system of automated gate control in assays of spatial cognition in fishes.

Valerie Lucks, Jens Theine, Maria Paula Arteaga Avendaño, Jacob Engelmann

Abstract read
In one paragraph

Article in Journal of fish biology, 2025. 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. 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.

Valerie LucksActive Sensing, Faculty of Biology, Bielefeld University, Bielefeld, Germany.ORCID https://orcid.org/0000-0002-1283-8236
Jens TheineGenetics and Genomics of Plants, Faculty of Biology & Center for Biotechnology, Bielefeld University, Bielefeld, Germany.
Maria Paula Arteaga AvendañoActive Sensing, Faculty of Biology, Bielefeld University, Bielefeld, Germany.
Jacob EngelmannActive Sensing, Faculty of Biology, Bielefeld University, Bielefeld, Germany.

Funding

Human Frontier Science Program RGP0016/2019
6 · The paper itself

Abstract

Automation of experimental setups is a promising direction in behavioral research because it can facilitate the acquisition of data while increasing its repeatability and reliability. For example, research in spatial cognition can benefit from automated control by systematic manipulation of sensory cues and more efficient execution of training procedures. However, commercial solutions are often costly, restricted to specific platforms, and mainly focused on the automation of data acquisition, stimulus presentation, and reward delivery. Animal welfare considerations as well as experimental demands may require automating the access of an animal or animals to the experimental arena. Here, we provide and test a low-cost, versatile Raspberry Pi-based solution for such use cases. We provide four application scenarios of varying complexities, based on our research of spatial orientation and navigation in weakly electric fish, with step-by-step protocols for the control of gates in the experimental setups. This easy-to-implement, platform-independent approach can be adapted to various experimental needs, including closed-loop as well as field experiments. As such, it can contribute to the optimization and standardization of experiments in a variety of species, thereby enhancing the comparability of data.

Indexed as

CognitionElectric FishSpatial NavigationAnimalsAutomationOrientation, Spatialautomationmotor systemnavigationraspberry pisetup gatesspatial learningweakly electric fish

Identifiers

PMID39415602
PMCPMC12536059

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.