A team of American neuroscientists and AI researchers has built the most sophisticated digital model of the fruit fly to date. The work is detailed in a study published by the Howard Hughes Medical Institute (HHMI) and highlights a new level of realism in simulating insect biology.
In this latest research, the authors expanded the model to cover anatomy, biomechanics, physics, and behavior, aiming for a simulation that can perform multiple actions with convincing accuracy. The result is a virtual insect that mirrors flight and terrestrial movement with a high degree of fidelity and reliability.
The process involves taking extensive data on how real flies fly and walk, training a neural network to reproduce those movements, and then letting the trained network drive the virtual fly to perform specific motions. This approach enables researchers to test and refine control strategies in a closed, repeatable environment.
Realistic computer models of flies and other organisms help scientists study how the nervous system, body form, and environmental forces shape movement and behavior. While decades of laboratory work with real animals have yielded insights, virtual simulations allow researchers to isolate variables and quantify the impact of factors such as aerodynamic forces during flight and ground contact dynamics during walking.
Looking ahead, the team plans to enrich the fly model further by integrating more anatomical details, including muscle groups and tendon mechanics, and by building a more authentic sensory system. These enhancements will support deeper investigations into how perception guides motor decisions in tiny fliers and crawlers alike.
Previously, the project demonstrated a vision pipeline that approximates how animals perceive their surroundings, providing the foundation for more comprehensive sensory simulations and navigation behaviors inside the digital model. This work supports broader efforts to model animal intelligence and motor control for research and potential applications in robotics and neuroscience research [citation].