Data-driven modelling of social forces and collective behaviour in zebrafish
Copyright © 2018 Elsevier Ltd. All rights reserved..
Zebrafish are rapidly emerging as a powerful model organism in hypothesis-driven studies targeting a number of functional and dysfunctional processes. Mathematical models of zebrafish behaviour can inform the design of experiments, through the unprecedented ability to perform pilot trials on a computer. At the same time, in-silico experiments could help refining the analysis of real data, by enabling the systematic investigation of key neurobehavioural factors. Here, we establish a data-driven model of zebrafish social interaction. Specifically, we derive a set of interaction rules to capture the primary response mechanisms which have been observed experimentally. Contrary to previous studies, we include dynamic speed regulation in addition to turning responses, which together provide attractive, repulsive and alignment interactions between individuals. The resulting multi-agent model provides a novel, bottom-up framework to describe both the spontaneous motion and individual-level interaction dynamics of zebrafish, inferred directly from experimental observations.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2018 |
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| Erschienen: |
2018 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:443 |
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| Enthalten in: |
Journal of theoretical biology - 443(2018) vom: 14. Apr., Seite 39-51 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zienkiewicz, Adam K [VerfasserIn] |
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| Links: |
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| Themen: |
Agent-based modelling |
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| Anmerkungen: |
Date Completed 31.07.2019 Date Revised 31.07.2019 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jtbi.2018.01.011 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM280273878 |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2018 Elsevier Ltd. All rights reserved. | ||
| 520 | |a Zebrafish are rapidly emerging as a powerful model organism in hypothesis-driven studies targeting a number of functional and dysfunctional processes. Mathematical models of zebrafish behaviour can inform the design of experiments, through the unprecedented ability to perform pilot trials on a computer. At the same time, in-silico experiments could help refining the analysis of real data, by enabling the systematic investigation of key neurobehavioural factors. Here, we establish a data-driven model of zebrafish social interaction. Specifically, we derive a set of interaction rules to capture the primary response mechanisms which have been observed experimentally. Contrary to previous studies, we include dynamic speed regulation in addition to turning responses, which together provide attractive, repulsive and alignment interactions between individuals. The resulting multi-agent model provides a novel, bottom-up framework to describe both the spontaneous motion and individual-level interaction dynamics of zebrafish, inferred directly from experimental observations | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Agent-based modelling | |
| 650 | 4 | |a Data-driven | |
| 650 | 4 | |a Stochastic differential equations | |
| 650 | 4 | |a Zebrafish | |
| 700 | 1 | |a Ladu, Fabrizio |e verfasserin |4 aut | |
| 700 | 1 | |a Barton, David A W |e verfasserin |4 aut | |
| 700 | 1 | |a Porfiri, Maurizio |e verfasserin |4 aut | |
| 700 | 1 | |a Bernardo, Mario Di |e verfasserin |4 aut | |
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