Development of neural circuits for social motion perception in schooling fish

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Abstract

Many animals move in groups, where collective behavior emerges from the interactions amongst individuals. These social interactions produce the coordinated movements of bird flocks and fish schools, but little is known about their developmental emergence and neurobiological foundations. By characterizing the visually-based schooling behavior of the micro glassfish Danionella cerebrum, here we found that social development progresses sequentially, with animals first acquiring the ability to aggregate, followed by postural alignment with social partners. This social maturation was accompanied by the development of neural populations in the midbrain and forebrain that were preferentially driven by visual stimuli that resemble the shape and movements of schooling fish. The development of these neural circuits enables the social coordination required for collective movement.

One-Sentence Summary:

The collective behavior of schooling fish emerges with the development of neural populations selective to social motion.

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Most cited references 45

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The vertebrate mesolimbic reward system and social behavior network: a comparative synthesis.

Lauren A. O'Connell, Hans A. Hofmann (2011)

All animals evaluate the salience of external stimuli and integrate them with internal physiological information into adaptive behavior. Natural and sexual selection impinge on these processes, yet our understanding of behavioral decision-making mechanisms and their evolution is still very limited. Insights from mammals indicate that two neural circuits are of crucial importance in this context: the social behavior network and the mesolimbic reward system. Here we review evidence from neurochemical, tract-tracing, developmental, and functional lesion/stimulation studies that delineates homology relationships for most of the nodes of these two circuits across the five major vertebrate lineages: mammals, birds, reptiles, amphibians, and teleost fish. We provide for the first time a comprehensive comparative analysis of the two neural circuits and conclude that they were already present in early vertebrates. We also propose that these circuits form a larger social decision-making (SDM) network that regulates adaptive behavior. Our synthesis thus provides an important foundation for understanding the evolution of the neural mechanisms underlying reward processing and behavioral regulation. Copyright © 2011 Wiley-Liss, Inc.

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Inferring the structure and dynamics of interactions in schooling fish.

Y Katz, K. Tunstrom, C Ioannou … (2011)

Determining individual-level interactions that govern highly coordinated motion in animal groups or cellular aggregates has been a long-standing challenge, central to understanding the mechanisms and evolution of collective behavior. Numerous models have been proposed, many of which display realistic-looking dynamics, but nonetheless rely on untested assumptions about how individuals integrate information to guide movement. Here we infer behavioral rules directly from experimental data. We begin by analyzing trajectories of golden shiners (Notemigonus crysoleucas) swimming in two-fish and three-fish shoals to map the mean effective forces as a function of fish positions and velocities. Speeding and turning responses are dynamically modulated and clearly delineated. Speed regulation is a dominant component of how fish interact, and changes in speed are transmitted to those both behind and ahead. Alignment emerges from attraction and repulsion, and fish tend to copy directional changes made by those ahead. We find no evidence for explicit matching of body orientation. By comparing data from two-fish and three-fish shoals, we challenge the standard assumption, ubiquitous in physics-inspired models of collective behavior, that individual motion results from averaging responses to each neighbor considered separately; three-body interactions make a substantial contribution to fish dynamics. However, pairwise interactions qualitatively capture the correct spatial interaction structure in small groups, and this structure persists in larger groups of 10 and 30 fish. The interactions revealed here may help account for the rapid changes in speed and direction that enable real animal groups to stay cohesive and amplify important social information.

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Collective cognition in animal groups.

Iain Couzin (2009)

The remarkable collective action of organisms such as swarming ants, schooling fish and flocking birds has long captivated the attention of artists, naturalists, philosophers and scientists. Despite a long history of scientific investigation, only now are we beginning to decipher the relationship between individuals and group-level properties. This interdisciplinary effort is beginning to reveal the underlying principles of collective decision-making in animal groups, demonstrating how social interactions, individual state, environmental modification and processes of informational amplification and decay can all play a part in tuning adaptive response. It is proposed that important commonalities exist with the understanding of neuronal processes and that much could be learned by considering collective animal behavior in the framework of cognitive science.

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Author and article information

Journal

Journal ID (nlm-ta): bioRxiv

Journal ID (publisher-id): BIORXIV

Title: bioRxiv

Publisher: Cold Spring Harbor Laboratory

Publication date (Electronic): 27 October 2023

Electronic Location Identifier: 2023.10.25.563839

Affiliations

[1 ]Department of Neurobiology, School of Biological Sciences. University of California, San Diego. La Jolla, CA, USA 92093

Author notes

[†]

These authors contributed equally to this work

Author contributions:

DZ, LS, JY, and MLB designed experiments. DZ, JY, JN, and PT performed freely-swimming behavioral experiments. DZ, LS, JY, PT, JN, and MLB wrote code and analyzed data. DZ, LS, JY, JN, and MLB developed the head-tethering approach. DZ, LS, and MLB performed imaging experiments. DZ, LS, and MLB wrote the paper, with feedback from all authors.

[* ]Corresponding author: mlb@ 123456ucsd.edu

Author information

David Zada http://orcid.org/0000-0002-5064-247X

Lisanne Schulze http://orcid.org/0000-0001-7875-3107

Jo-Hsien Yu http://orcid.org/0000-0003-2880-8215

Princess Tarabishi http://orcid.org/0000-0002-0827-188X

Julia L Napoli http://orcid.org/0000-0003-3306-2710

Matthew Lovett-Barron http://orcid.org/0000-0003-1425-5277

Article

DOI: 10.1101/2023.10.25.563839

PMC ID: 10634817

PubMed ID: 37961196

SO-VID: 053fa140-34e5-4c77-8d29-b8f7002a7c7e

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

History

Funding

Funded by: Human Frontier Science Program Postdoctoral Fellowship

Funded by: Zuckerman STEM Program Israeli Postdoctoral Fellowship

Funded by: Kavli Institute for Brain and Mind Postdoctoral Fellowship

Award ID: 2022140

Funded by: UC San Diego J. Yang Scholarship

Funded by: Taiwanese Government Scholarship to Study Abroad Award

Funded by: NIH

Award ID: T32GM133351

Award ID: R00MH112840

Funded by: Searle Scholars Award

Funded by: Packard Foundation Fellowship

Funded by: Pew Biomedical Scholar Award

Funded by: Klingenstein-Simons Fellowship in Neuroscience

Funded by: Sloan Research Fellowship

Funded by: NIH New Innovator Award

Award ID: DP2EY036251

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