A behavioral architecture for realistic simulations of Drosophila larva locomotion and foraging.

Authors

Panagiotis Parthenios Sakagiannis, Anna-Maria Jürgensen, Martin Paul Nawrot

Published in

eLife. Volume 14. Aug 17, 2026. Epub Aug 17, 2026.

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.

PMID:
42605607
Bibliographic data and abstract were imported from PubMed on 17 Aug 2026.

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