Video: First map of an insect brain – Scientists map complete brain of a fruit fly larva for the first time

The connectome of the complete fruit fly larvae brain. The different colors represent different types of neurons.© Johns Hopkins University and University of Cambridge

Neurobiological milestone: For the first time, scientists have succeeded in completely mapping the brain of the fruit fly larva. The map includes all 3,016 neurons and 548,000 synapses of the insect Drosophila melanogaster, making it the largest brain map ever. With their help, the researchers want to learn more about various brain processes such as thinking, learning and decision-making. The results can also be transferred to humans.

Every brain consists of neurons that are connected to each other via synapses. Although we now know which brain regions are responsible for what, some unanswered questions remain. Above all, these concern how different brain processes work in detail, i.e. how neuronal signals migrate through the brain and then lead to certain behaviors or to us learning something new.

A twelve year old brain portrait

“If we want to understand who we are and how we think, we must also understand the mechanism of thinking. And the key to that is knowing how the neurons are connected,” says Joshua Vogelstein of Johns Hopkins University. He is part of a research team that has now mapped the circuitry of the neurons in the larvae of the fruit fly Drosophila melanogaster in more detail than ever before. The resulting connectome shows all 3,016 neurons and 548,000 synapses of the insect in a three-dimensional model.

Twelve years of work have gone into this largest and most complete brain mapping to date. In order to get a complete picture of the brain at the cellular level, the research team led by Michael Winding from the University of Cambridge first had to dissect the brain into hundreds of individual tissue samples and image each of them with the electron microscope. This imaging alone cost the research team about a day per neuron. The scientists then had to reconstruct all these individual parts – neuron by neuron – and put them together to form a complete portrait of the brain.

milestone in neuroscience

So far, this has only been achieved with the brains of three worms, although these consisted of significantly fewer neurons. Complex brains with several thousand, millions or even billions of neurons have only been partially mapped, if at all, but never completely. The brain map of the fruit fly is therefore considered a milestone in neuroscience. However, we are still a long way from a connectome of the human brain. This would have to represent an impressive 100 billion nerve cells – too many for current technology.

Nonetheless, our brains and those of other complex mammals are not significantly different from that of the fruit fly. In principle, they too are nothing more than networks of interconnected neurons that have to carry out a series of complex behaviors, such as learning, selecting food and finding their way. Therefore, according to Winding’s team, the knowledge gained from the fruit fly connectome can also be transferred to the human brain.

Application in machine learning

Winding and his colleagues have already started investigating the circuit architecture in the brain of the fruit fly larvae. Among other things, they were able to identify different connection and 93 neuron types as well as network nodes. Winding’s team noticed that the brain’s busiest circuits were those that lead to and from the neurons in the learning center.

These and some other structures in the fruit fly brain remind the researchers of machine learning structures. They therefore suggest: “Future analysis of the similarities and differences between brains and artificial neural networks could help to understand the computational principles of the brain and perhaps inspire new architectures for machine learning.”

So not only will the fruit fly map bring us closer to understanding our own brains, but it will also enable advances in the development of artificial intelligence. (Science, 2023; doi:10.1126/science.add9330)

Quelle: University of Cambridge, Johns Hopkins University, Science