Scientists at EPFL have created a digital model of the fruit fly that is realistic. The twin is a big step towards reverse engineering the neurological control of animals.
Professor Pavan Ramdya at EPFL's School of Life Sciences says that they used two kinds of data to build NeuroMechFly. The real limb movements of the fly were obtained using pose estimation software that we have developed in the last couple of years that allow us to precisely track the movements of the animal.
Ramdya's group, working with the group of Professor Auke Ijspeert at EPFL's Biorobotics Laboratory, has published a paper in Nature Methods showcasing the first ever accurate digital twin of the fly Drosophila melan.
It's not long before time flies.
Ramdya has been working on digitally tracking and modeling the animal for years, and he has a long-term focus on this insect. His group published DeepFly3D, a motion capture software that uses multiple camera views to quantify the movements of flies in three-dimensional space.
LiftPose3D is a method for reconstructing 3D animal poses from 2D images taken from a single camera. Neuroscience and animal-inspired robotics have been provided with tools that can't be overstated.
The culmination of all those efforts is what NeuroMechFly represents. The model is based on data from previous studies and features independent computational parts that mimic different parts of the insect's body. This also includes a neural network and controllers with a motor output, as well as a body part that helps the fly measure its own orientation while flying, such as head, legs, wings, abdominal segments, proboscis, and halteres.
Why build a twin of a fruit?
Ramdya asked how we know when we have understood a system. It is easier to build a simulation animal than a robotic fly. One of the main reasons for this work is to build a model that integrates what we know about the fly's nervous system and biomechanics to see if it explains its behavior.
When we do experiments, we are often motivated by hypotheses. As neuroscience becomes more complicated, we rely on models that can bring together many intertwined components, play them out, and predict what might happen if you make a change.
The bed was tested.
The testbed for studies that advance biomechanics and biorobotics, but only in so far as it accurately represents the real animal in a digital environment, is called NeuroMechFly. Ramdya says that one of the main concerns was to verify this.
The researchers made 3D measurements of flies. They used a physics-based simulation environment to replay those behaviors.
In the paper, they show that the model can predict movement parameters that are otherwise unmeasured, such as the legs and contact reaction forces with the ground. They were able to find neural network and muscle parameters that allow the fly to run in ways that are both fast and stable.
Ramdya says that the case studies built their confidence in the model.
There is a community effort.
The project is called NeuroMechFly. The software is open source and can be used by scientists. We made it open source and modular and provided guidelines on how to modify it.
Progress in science depends on a community effort. One of the things that NeuroMechFly does is raise the bar. Because models were not very realistic, we did not ask how they could be informed by data. This model, replay behaviors, and infer meaningful information have been shown to you. This is a big step forward.
More information: NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster, Nature Methods (2022). DOI: 10.1038/s41592-022-01466-7 Journal information: Nature Methods Citation: NeuroMechFly: A digital twin of Drosophila (2022, May 11) retrieved 11 May 2022 from https://phys.org/news/2022-05-neuromechfly-digital-twin-drosophila.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.
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