Literature DB >> 35493317

Mathematical modeling of zebrafish social behavior in response to acute caffeine administration.

Mohammad Tuqan1, Maurizio Porfiri1,2,3.   

Abstract

Zebrafish is a model organism that is receiving considerable attention in preclinical research. Particularly important is the use of zebrafish in behavioral pharmacology, where a number of high-throughput experimental paradigms have been proposed to quantify the effect of psychoactive substances consequences on individual and social behavior. In an effort to assist experimental research and improve animal welfare, we propose a mathematical model for the social behavior of groups of zebrafish swimming in a shallow water tank in response to the administration of psychoactive compounds to select individuals. We specialize the mathematical model to caffeine, a popular anxiogenic compound. Each fish is assigned to a Markov chain that describes transitions between freezing and swimming. When swimming, zebrafish locomotion is modeled as a pair of coupled stochastic differential equations, describing the time evolution of the turn-rate and speed in response to caffeine administration. Comparison with experimental results demonstrates the accuracy of the model and its potential use in the design of in-silico experiments.

Entities:  

Keywords:  Anxiety; Danio rerio; collective behavior; in-silico; pharmacology; social interaction; stochastic differential equations

Year:  2021        PMID: 35493317      PMCID: PMC9053518          DOI: 10.3389/fams.2021.751351

Source DB:  PubMed          Journal:  Front Appl Math Stat        ISSN: 2297-4687


  44 in total

1.  Dopaminergic control of anxiety in young and aged zebrafish.

Authors:  Victoria Kacprzak; Neil A Patel; Elizabeth Riley; Lili Yu; Jing-Ruey J Yeh; Irina V Zhdanova
Journal:  Pharmacol Biochem Behav       Date:  2017-04-10       Impact factor: 3.533

2.  Collective response to perturbations in a data-driven fish school model.

Authors:  Daniel S Calovi; Ugo Lopez; Paul Schuhmacher; Hugues Chaté; Clément Sire; Guy Theraulaz
Journal:  J R Soc Interface       Date:  2015-03-06       Impact factor: 4.118

3.  Emergent sensing of complex environments by mobile animal groups.

Authors:  Andrew Berdahl; Colin J Torney; Christos C Ioannou; Jolyon J Faria; Iain D Couzin
Journal:  Science       Date:  2013-02-01       Impact factor: 47.728

4.  Model-free information-theoretic approach to infer leadership in pairs of zebrafish.

Authors:  Sachit Butail; Violet Mwaffo; Maurizio Porfiri
Journal:  Phys Rev E       Date:  2016-04-18       Impact factor: 2.529

5.  Data-driven modelling of social forces and collective behaviour in zebrafish.

Authors:  Adam K Zienkiewicz; Fabrizio Ladu; David A W Barton; Maurizio Porfiri; Mario Di Bernardo
Journal:  J Theor Biol       Date:  2018-01-31       Impact factor: 2.691

6.  Pharmacological analysis of zebrafish (Danio rerio) scototaxis.

Authors:  Caio Maximino; Annanda Waneza Batista da Silva; Amauri Gouveia; Anderson Manoel Herculano
Journal:  Prog Neuropsychopharmacol Biol Psychiatry       Date:  2011-01-13       Impact factor: 5.067

Review 7.  Zebrafish as a pharmacological tool: the how, why and when.

Authors:  Paul Goldsmith
Journal:  Curr Opin Pharmacol       Date:  2004-10       Impact factor: 5.547

8.  Analyzing fish movement as a persistent turning walker.

Authors:  Jacques Gautrais; Christian Jost; Marc Soria; Alexandre Campo; Sébastien Motsch; Richard Fournier; Stéphane Blanco; Guy Theraulaz
Journal:  J Math Biol       Date:  2008-06-28       Impact factor: 2.259

Review 9.  Zebrafish models for translational neuroscience research: from tank to bedside.

Authors:  Adam Michael Stewart; Oliver Braubach; Jan Spitsbergen; Robert Gerlai; Allan V Kalueff
Journal:  Trends Neurosci       Date:  2014-04-09       Impact factor: 13.837

10.  A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments.

Authors:  Bertrand Collignon; Axel Séguret; José Halloy
Journal:  R Soc Open Sci       Date:  2016-01-13       Impact factor: 2.963

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