Elements of a stochastic 3D prediction engine in larval zebrafish prey capture release_qxj5rd7kkvhzzmksofrydo5xsm

by Andrew D Bolton, Martin Haesemeyer, Josua Jordi, Ulrich Schaechtle, Feras A Saad, Vikash K Mansinghka, Joshua B Tenenbaum, Florian Engert

Published in eLife by eLife Sciences Publications, Ltd.

2019   Volume 8

Abstract

The computational principles underlying predictive capabilities in animals are poorly understood. Here, we wondered whether predictive models mediating prey capture could be reduced to a simple set of sensorimotor rules performed by a primitive organism. For this task, we chose the larval zebrafish, a tractable vertebrate that pursues and captures swimming microbes. Using a novel naturalistic 3D setup, we show that the zebrafish combines position and velocity perception to construct a future positional estimate of its prey, indicating an ability to project trajectories forward in time. Importantly, the stochasticity in the fish's sensorimotor transformations provides a considerable advantage over equivalent noise-free strategies. This surprising result coalesces with recent findings that illustrate the benefits of biological stochasticity to adaptive behavior. In sum, our study reveals that zebrafish are equipped with a recursive prey capture algorithm, built up from simple stochastic rules, that embodies an implicit predictive model of the world.
In application/xml+jats format

Archived Files and Locations

application/pdf  1.9 MB
file_eh5mpbwmmbhurjbfzl2mp6lp54
elifesciences.org (publisher)
web.archive.org (webarchive)

Web Captures

https://elifesciences.org/articles/51975
2022-04-02 12:15:47 | 27 resources
webcapture_j6ezczwrrrbqhcxryzvw2utv54
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2019-11-26
Language   en ?
DOI  10.7554/elife.51975
PubMed  31769753
PMC  PMC6930116
Container Metadata
Open Access Publication
In DOAJ
In ISSN ROAD
In Keepers Registry
ISSN-L:  2050-084X
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 6e9b107b-59aa-406b-ac2a-a54a613fe282
API URL: JSON