NeuroMechFly, the first accurate “digital twin” of the fly Drosophila melanogaster, offers an extremely valuable test bench for research advancing in biomechanics and biorobotics. This could help pave the way for fly-like robots like the one illustrated here. Credit: EPFL

Drosophila digital twin

“We used two types of data to build NeuroMechFly,” said Professor Pavan Ramdja of the Ecole Polytechnique Fédérale de Lausanne (EPFL). “First we took a real fly and did a CT scan to build a morphologically realistic biomechanical model. The second source of data was the actual movements of the fly’s limbs, obtained with the help of posture assessment software, which we have developed over the last few years, which allows us to accurately track the movements of the animal.

Ramdya’s group, working with Professor Auke Ijspeert’s group in the EPFL Biorobotics Laboratory, published an article today (May 11, 2022) in the journal Natural methods showing the first accurate “digital twin” of the fly Drosophila melanogastercalled NeuroMechFly.

Time flies

Drosophila is the most commonly used insect in the life sciences and a long-term focus of Ramdya’s own research, which has been working for years on digital tracking and modeling of this animal. in 2019, his group publishes DeepFly3Din-depth training based motion capture software that uses multiple camera views to quantify motion Drosophila in three-dimensional space.

Continuing with in – depth training in 2021 The Ramdya team published LiftPose3D, a method for reconstructing 3D animal poses from 2D images taken by a single camera. These types of breakthroughs have provided exploding fields of neuroscience and animal-inspired robotics with tools whose usefulness cannot be overstated.

NeuroMechFly

Digital model of Drosophila melanogaster called NeuroMechFly. Credit: Pavan Ramdja (EPFL)

In many ways, NeuroMechFly is the culmination of all these efforts. Limited by morphological and kinematic data from these previous studies, the model includes independent computational parts that simulate different parts of the insect’s body. This includes a biomechanical exoskeleton with articulating body parts such as head, legs, wings, abdominal segments, proboscis, antennae, halteres (organs that help the fly measure its own orientation in flight) and neural network “controllers” with motor exit.

Why build a digital twin Drosophila?

“How do we know when we understand a system?” Says Ramdya. “One way is to be able to recreate it. We can try to build a robotic fly, but it is much faster and easier to build a simulated animal. So one of the main motivations behind this work is to start building a model that integrates what we know about the fly’s nervous system and biomechanics to see if it’s enough to explain its behavior.

“When we do experiments, we are often motivated by hypotheses,” he added. “So far we have relied on intuition and logic to formulate hypotheses and predictions. But as neuroscience becomes more complex, we rely more on models that can bring together many intertwined components, play them out, and predict what might happen if you make a change here or there.

The test bench

NeuroMechFly offers an extremely valuable test platform for research that advances in biomechanics and biorobotics, but only insofar as it accurately represents the real animal in the digital environment. Checking this was one of the main concerns of the researchers. “We have conducted validation experiments that show that we can closely reproduce the behavior of a real animal,” says Ramdya.

The researchers first made 3D measurements of real walking and clipping flies. They then replayed this behavior using NeuroMechFly’s biomechanical exoskeleton in a physics-based simulation environment.

NeuroMechFly research team

Jonathan Aregit, Victor Lobato Rios, Auke Izgspeart, Pavan Ramdia, Shravan Tata Ramalingasetti and Gizem Ozdil. Credit: Alain Herzog (EPFL)

As shown in the article, the model can actually predict various motion parameters that are not otherwise measured, such as leg torques and ground contact response forces. Finally, they were able to use NeuroMechFly’s full neuromechanical capabilities to detect neural networks and muscle parameters that allow the fly to “run” in ways optimized for both speed and stability.

“These cases have built our trust in the model,” Ramdya said. “But we’re most interested in when the simulation fails to reproduce animal behavior, pointing out ways to improve the model.” In this way, NeuroMechFly is a powerful test for building an understanding of how behavior arises from the interactions between complex neuromechanical systems and their physical environment.

Community effort

Ramdya emphasizes that NeuroMechFly has been and will continue to be a public project. As such, the software is open source and is freely available for use and modification by scientists. “We have created a tool not only for us but also for others. So we did it open source and modular and provided guidelines on how to use and modify it.

“More and more progress in science depends on the efforts of the community,” he added. It is important for the community to use the model and improve it. But one of the things NeuroMechFly is already doing is raising the bar. Previously, because the models were not very realistic, we did not ask how they could be directly informed by data. Here’s how to do it; you can take this pattern, reproduce the behavior, and extract meaningful information. So I think that’s a big step forward. “

Reference: “NeuroMechFly, a neuromechanical model of an adult Drosophila melanogaster”By Victor Lobato Rios, Shravan Tata Ramalingasetti, Pembe Gizem Ozdil, Jonathan Areguit, Auke Jan Izgspeurt and Pavan Ramdia, 11 May 2022, Natural methods.
DOI: 10.1038 / s41592-022-01466-7


NeuroMechFly: A Morphologically Realistic Biomechanical Model of a Fly

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