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The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish

Despite considerable advances, studying electrocommunication of weakly electric fish, particularly in pulse-type species, is challenging as very short signal epochs at variable intervals from a few hertz up to more than 100 Hz need to be assigned to individuals. In this study, we show that supervise...

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Autores principales: Pedraja, Federico, Herzog, Hendrik, Engelmann, Jacob, Jung, Sarah Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542711/
https://www.ncbi.nlm.nih.gov/pubmed/34707485
http://dx.doi.org/10.3389/fnbeh.2021.718491
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author Pedraja, Federico
Herzog, Hendrik
Engelmann, Jacob
Jung, Sarah Nicola
author_facet Pedraja, Federico
Herzog, Hendrik
Engelmann, Jacob
Jung, Sarah Nicola
author_sort Pedraja, Federico
collection PubMed
description Despite considerable advances, studying electrocommunication of weakly electric fish, particularly in pulse-type species, is challenging as very short signal epochs at variable intervals from a few hertz up to more than 100 Hz need to be assigned to individuals. In this study, we show that supervised learning approaches offer a promising tool to automate or semiautomate the workflow, and thereby allowing the analysis of much longer episodes of behavior in a reasonable amount of time. We provide a detailed workflow mainly based on open resource software. We demonstrate the usefulness by applying the approach to the analysis of dyadic interactions of Gnathonemus petersii. Coupling of the proposed methods with a boundary element modeling approach, we are thereby able to model the information gained and provided during agonistic encounters. The data indicate that the passive electrosensory input, in particular, provides sufficient information to localize a contender during the pre-contest phase, fish did not use or rely on the theoretically also available sensory information of the contest outcome-determining size difference between contenders before engaging in agonistic behavior.
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spelling pubmed-85427112021-10-26 The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish Pedraja, Federico Herzog, Hendrik Engelmann, Jacob Jung, Sarah Nicola Front Behav Neurosci Behavioral Neuroscience Despite considerable advances, studying electrocommunication of weakly electric fish, particularly in pulse-type species, is challenging as very short signal epochs at variable intervals from a few hertz up to more than 100 Hz need to be assigned to individuals. In this study, we show that supervised learning approaches offer a promising tool to automate or semiautomate the workflow, and thereby allowing the analysis of much longer episodes of behavior in a reasonable amount of time. We provide a detailed workflow mainly based on open resource software. We demonstrate the usefulness by applying the approach to the analysis of dyadic interactions of Gnathonemus petersii. Coupling of the proposed methods with a boundary element modeling approach, we are thereby able to model the information gained and provided during agonistic encounters. The data indicate that the passive electrosensory input, in particular, provides sufficient information to localize a contender during the pre-contest phase, fish did not use or rely on the theoretically also available sensory information of the contest outcome-determining size difference between contenders before engaging in agonistic behavior. Frontiers Media S.A. 2021-10-11 /pmc/articles/PMC8542711/ /pubmed/34707485 http://dx.doi.org/10.3389/fnbeh.2021.718491 Text en Copyright © 2021 Pedraja, Herzog, Engelmann and Jung. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Behavioral Neuroscience
Pedraja, Federico
Herzog, Hendrik
Engelmann, Jacob
Jung, Sarah Nicola
The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish
title The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish
title_full The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish
title_fullStr The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish
title_full_unstemmed The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish
title_short The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish
title_sort use of supervised learning models in studying agonistic behavior and communication in weakly electric fish
topic Behavioral Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542711/
https://www.ncbi.nlm.nih.gov/pubmed/34707485
http://dx.doi.org/10.3389/fnbeh.2021.718491
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