Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Modeling the variability of the electromotor command system of pulse mormyrids

View ORCID ProfileÁngel Lareo, Pablo Varona, Francisco B. Rodríguez
doi: https://doi.org/10.1101/2020.06.09.142083
Ángel Lareo
1Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Ángel Lareo
  • For correspondence: angel.lareo@gmail.com
Pablo Varona
1Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Francisco B. Rodríguez
1Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

The electromotor neural system in weakly electric fish is a network responsible for active electroreception and electrolocation. This system controls the timing of pulse generation in the electrical signals used by these fish for extracting information from the environment and communicating with other specimens. Ethological studies related to fish mating, exploratory, submissive or aggressive behaviors have described distinct sequences of pulse intervals (SPIs). Accelerations, scallops, rasps, and cessations are four patterns of SPIs reported in pulse mormyrids, each showing characteristic temporal structures and large variability both in timing and duration. This paper presents a biologically plausible computational model of the electromotor command circuit that reproduces these four SPI patterns as a function of the input to the model while keeping the same internal parameter configuration. The topology of the model is based on a simplified representation of the network as described by morphological and electrophysiological studies. An initial ad hoc tuned configuration (S-T) was build to reproduce all four SPI patterns. Then, starting from S-T, a genetic algorithm (GA) was developed to automatically find the parameters of the model connectivity. Two different configurations obtained from the GA are presented here: one optimized to a set of synthetic examples of SPI patterns based on experimental observations in mormyrids (S-GA), and another configuration adjusted to patterns recorded from freely-behaving Gnathonemus Petersii specimens (R-GA). A robustness analysis to input variability of these model configurations was performed to discard overfitting and assess validity. Results showed that the four SPI patterns are consistently reproduced, both with synthetic (S-GA) data and with signals recorded from behaving animals (R-GA). This new model can be used as a tool to analyze the electromotor command chain during electrogeneration and assess the role of temporal structure in electroreception.

Author summary Weakly electric fish are a convenient system to study information processing in the nervous system. These fish have a remarkable sense of active electroreception, which allows them to generate and detect electrical fields for locating objects and communicating with other specimens in their surroundings. The electrical signal generated by these fish can be easily monitored noninvasively in freely-behaving animals. Activity patterns in this signal have been associated to different fish behaviors, like aggression or mating, for some species of the mormyridae family. In this work we use discharge patterns recorded from specimens of the Gnathonemus Petersii species along with synthetic data to develop a model of the electromotor command network. The model network is based on morphological and physiological studies in this type of weakly electric fish. The parameters of this model were tuned using a genetic algorithm to fit both synthetic and recorded activity patterns. This computational model allows to simulate the electromotor network behavior under controlled conditions and to test new hypotheses on the generation and function of temporal structure in the signals produced by weakly electric fish.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵* angel.lareo{at}gmail.com, f.rodriguez{at}uam.es

  • https://github.com/angellareo/electromotor-nmodel

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
Back to top
PreviousNext
Posted June 11, 2020.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Modeling the variability of the electromotor command system of pulse mormyrids
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Modeling the variability of the electromotor command system of pulse mormyrids
Ángel Lareo, Pablo Varona, Francisco B. Rodríguez
bioRxiv 2020.06.09.142083; doi: https://doi.org/10.1101/2020.06.09.142083
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Modeling the variability of the electromotor command system of pulse mormyrids
Ángel Lareo, Pablo Varona, Francisco B. Rodríguez
bioRxiv 2020.06.09.142083; doi: https://doi.org/10.1101/2020.06.09.142083

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (2635)
  • Biochemistry (5224)
  • Bioengineering (3650)
  • Bioinformatics (15730)
  • Biophysics (7218)
  • Cancer Biology (5597)
  • Cell Biology (8051)
  • Clinical Trials (138)
  • Developmental Biology (4739)
  • Ecology (7472)
  • Epidemiology (2059)
  • Evolutionary Biology (10531)
  • Genetics (7704)
  • Genomics (10090)
  • Immunology (5157)
  • Microbiology (13829)
  • Molecular Biology (5354)
  • Neuroscience (30605)
  • Paleontology (212)
  • Pathology (872)
  • Pharmacology and Toxicology (1520)
  • Physiology (2235)
  • Plant Biology (4987)
  • Scientific Communication and Education (1037)
  • Synthetic Biology (1380)
  • Systems Biology (4131)
  • Zoology (804)