What do navigating animals see? Reconstructing the visual histories of desert ants

To understand how brains translate sensory input into behavioural outputs requires a fuller account of the sensory experience of individual animals in their natural settings. Previously we developed a visual rendering software capable of reconstructing the information that insect's compound eyes perceive (Millward et al, 2022). In this work, we extend this software pipeline to integrate data from animal tracking, habitat mapping, and compound eye modelling methods. The result is a new type of dataset that documents the natural foraging behaviour of desert ants (a model species for the study of animal navigation) within their natural habitat, combined with simulation tools to accurately reconstruct the visual experience of each forager as they learned to navigate their surroundings. This addresses a long-held need to create realistic training input for brain models complimented with verification tests in the same real ecologically relevant scenarios.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-10-27
DOI
https://doi.org/10.64898/2026.10.22.760929
Primary Topic
Insect and Arachnid Ecology and Behavior
Type
preprint
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preprint

What do navigating animals see? Reconstructing the visual histories of desert ants

Blayze Millward, Emily Baird, Michael Mangan, Sebastian James
1 links
bioRxiv (Cold Spring Harbor Laboratory)
Insect and Arachnid Ecology and Behavior
preprint

What do navigating animals see? Reconstructing the visual histories of desert ants

Blayze Millward, Emily Baird, Michael Mangan, Sebastian James
preprint en

Abstract

To understand how brains translate sensory input into behavioural outputs requires a fuller account of the sensory experience of individual animals in their natural settings. Previously we developed a visual rendering software capable of reconstructing the information that insect's compound eyes perceive (Millward et al, 2022). In this work, we extend this software pipeline to integrate data from animal tracking, habitat mapping, and compound eye modelling methods. The result is a new type of dataset that documents the natural foraging behaviour of desert ants (a model species for the study of animal navigation) within their natural habitat, combined with simulation tools to accurately reconstruct the visual experience of each forager as they learned to navigate their surroundings. This addresses a long-held need to create realistic training input for brain models complimented with verification tests in the same real ecologically relevant scenarios.

bioRxiv (Cold Spring Harbor Laboratory)
Stockholm University (SE)
Insect and Arachnid Ecology and Behavior
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What do navigating animals see? Reconstructing the visual histories of desert ants — Blayze Millward, Emily Baird, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS