The tiny fruit fly, one of the most popular model organisms in science, lives fast and dies at about 50 days old. But this brief life is anything but unremarkable. The fly fills its days with intricate routines and schemes—and, on occasion, romance. To better understand how such a minuscule brain can power these complex behaviors, scientists have already created a connectome, a virtual “map” showing the links between each of the fruit fly’s 200,000 neurons.
And now they’ve built a body.
Researchers at the Howard Hughes Medical Institute’s (HHMI’s) Janelia Research Campus in Virginia and Google DeepMind recently designed a virtual fruit fly that looks and moves like the real thing, making it easier for scientists to observe this favorite research animal’s surprisingly nuanced habits and movements. They posted their paper on the project, which has not yet been peer-reviewed, to the preprint server bioRxiv in mid-March.
“Few organisms have been studied in as much detail along the complete scale of biology, from molecule to the behavior, as the fruit fly Drosophila melanogaster,” says developmental biologist Ruth Lehmann. Lehmann, who directs the Whitehead Institute for Biomedical Research and was not involved in the new project, has studied fruit fly genetics and body development. The virtual insect “portrays realistic behavior of a fly walking, flying and even grooming,” she says. “This type of research tests the limits of our fundamental understanding of biology.”
Compared with a human brain or an artificial neural network, both of which have trillions of connections, the fly brain is teeny and simple. But that doesn’t mean it’s easy to understand what goes on inside it. The connectome’s network of neurons tells you “who’s talking to whom, not what messages are being sent” within the brain, says the preprint paper’s senior author Srinivas Turaga, a neuroscientist at the Howard Hughes Medical Institute. The virtual fly project (which has not yet incorporated the digital connectome) instead focuses on behavior—the result, Turaga notes, of how a body translates nervous system connections.
To build this virtual insect, researchers first used high-resolution microscopes to scan a real female fruit fly’s anatomy—its limbs, wings and joints. From these fine-scale measurements, the team assembled a three-dimensional model within a physics simulation program called MuJoCo, short for Multi-Joint Dynamics with Contact, developed by Google’s DeepMind lab subsidiary. To get the virtual fly to move like a real one, the simulated body needed to learn from the source. That’s where artificial intelligence came in—more specifically, a subset of AI called reinforcement learning.
Reinforcement learning allows a machine to improve its performance by understanding an environment, watching a behavior, doing that behavior and receiving feedback. Then the process repeats until the machine gets the task right. (This same mechanism lies behind training self-driving cars, for example.)