Researchers Build Virtual Brain Network Based on Fruit Fly’s Brain

Researchers have developed a brain network that can forecast how individual neurons behave in the brain of a living organism. The model is based on the visual system of a fruit fly, affording researchers a way to test ideas prior to investing in experiments that involve other lab animals.

This feat was realized after more than 10 years of intense study on the structure and composition of the brain of a fruit fly. Most of this research was funded and conducted by the Howard Hughes Medical Institute, which generated maps that demonstrate every connection and neuron in the brain of this insect. The researchers theorized that they could utilize these maps to develop a model that would behave like the visual system of the fruit fly, which makes up a huge part of the insect’s brain.

The study’s author, Professor Jakob Macke, explained that the brain of a fruit fly was small and energy efficient, which allowed it to perform a lot of computations. He noted that the insect was able to walk, fly, mate, detect predators and basically survive, using only 100,000 neurons.

SrinivasTuraga, group leader at the Janelia Research Campus, stated that with this information, they could predict how the brain of a fly could work before anyone could make an experimental measurement.

For their study, the researchers generated a connectome, which shows all the connections between neurons. Once this was completed, they developed a brain circuit model that allowed the insect to detect motion. This led to a model that could forecast how every neuron in the artificial network would respond to a certain video.  Surprisingly, the artificial intelligence (AI)-generated model could also forecast neuron response in actual fruit flies that had seen these videos in prior studies.

The researchers’ approach suggests that AI systems such as ChatGPT may consume less energy if they utilized computational strategies similar to those in a living brain. In comparison, artificial intelligence systems usually require computers with billions upon billions of transistors. Globally, these systems consume so much power that it could meet the energy needs of a small nation.

The researchers published their findings in the “Nature” journal.

Other researchers who were part of the study included PhD candidate Janne Lappalainen, Eyal Gruntman, Fabian D. Tschopp, Shin-ya Takemura, Sridhama Prakhya, Kazunori Shinomiya, Aljoscha Nern and Mason McGill.

Ben Crowley, a computational neuroscientist who wasn’t part of this study, notes that borrowing strategies from the brain of a fruit fly could help make AI systems more power efficient.

As companies such as Microsoft Corp. (NASDAQ: MSFT) continue to develop AI-based solutions for different fields, these technologies are bound to revolutionize many industries beyond just the medical field.

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