A behavioral architecture for realistic simulations of <i>Drosophila</i> larva locomotion and foraging.

Overview

1. Computational Systems Neuroscience, University of Cologne Cologne Germany

Abstract

The Drosophila larva is extensively used as a model organism in neuroethological studies where precise behavioral tracking enables the statistical analysis of individual and population-level behavioral metrics that can inform mathematical models of larval behavior. Here, we propose a hierarchical model architecture comprising three layers to facilitate modular model construction, closed-loop simulations, and direct comparisons between empirical and simulated data. At the motor layer, the autonomous locomotory model is capable of performing exploration. Based on novel kinematic analyses, our model features intermittent forward crawling that is phasically coupled to lateral bending. At the second layer, navigation is achieved via active sensing in a simulated environment, and top-down modulation of locomotion. At the top layer, behavioral adaptation entails associative learning. We evaluate virtual larval behavior across agent-based simulations of autonomous free exploration, chemotaxis, and odor preference testing. Our behavioral architecture is ideally suited for the modular combination of neuromechanical, neural, or mere statistical model components, facilitating their evaluation, comparison, extension, and integration into multifunctional control architectures.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

Software package and code availability

All data processing, analysis, and model simulations were performed using our open-source Python package Larvaworld (https://pypi.org/project/larvaworld/), a unified platform for behavioral analysis and simulation of Drosophila larvae. In Larvaworld, empirical and simulated data are handled identically: the same analysis pipeline and behavioral metrics are applied to both, ensuring methodological consistency throughout.

The behavioral architecture introduced in this manuscript provides the backbone for constructing, extending, configuring, and fitting behavioral models within Larvaworld. The intermittent coupled-oscillator model developed here is included, alongside other preconfigured models.

A separate publication describes the software architecture and usage in detail and provides practical tutorials for science and teaching (Sakagiannis et al., 2025). Comprehensive documentation is available at https://larvaworld.readthedocs.io.

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability

The current manuscript is a computational study, so no data have been generated for this manuscript. Data analysis, behavioral modeling, and simulations have been carried out using the larvaworld Python package: https://pypi.org/project/larvaworld/.

The following previously published dataset was used:

ThoenerJ SchleyerM 2021Locomotion of naive Drosophila larvaeGIN10.12751/g-node.5e1ifd

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 3 authors, 6 keywords, 10 MeSH terms, 2 funders, 94 references.

Cite

This paper

Sakagiannis, P. P., Jürgensen, A.-M., & Nawrot, M. P. (2026). A behavioral architecture for realistic simulations of <i>Drosophila</i> larva locomotion and foraging. eLife, 14, RP104262. https://doi.org/10.7554/elife.104262

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