MIT neuroscientist Sebastian Seung wants to map the networks connecting the 100 billion neurons in the human brain,those networks, creating a wiring diagram of the brain that could help scientists learn how we each become our unique selves.
Using a combination of human and artificial intelligence, they have mapped all the wiring among 950 neurons within a tiny patch of the mouse retina.
Composed of neurons that process visual information, the retina is technically part of the brain and is a more approachable starting point, Seung says. By mapping all of the neurons in this 117-micron-by-80-micron patch of tissue, the researchers were able to classify most of the neurons they found, based on their patterns of wiring. They also identified a new type of retinal cell that had not been seen before.
“It’s the complete reconstruction of all the neurons inside this patch. No one’s ever done that before in the mammalian nervous system,” says Seung, a professor of computational neuroscience at MIT.
Neurons in the retina are classified into five classes: photoreceptors, horizontal cells, bipolar cells, amacrine cells and ganglion cells. Within each class are many types, classified by shape and by the connections they make with other neurons.
“Neurons come in many types, and the retina is estimated to contain 50 to 100 types, but they’ve never been exhaustively characterized. And their connections are even less well known,” Seung says.
In this study, the research team focused on a section of the retina known as the inner plexiform layer, which is one of several layers sandwiched between the photoreceptors, which receive visual input, and the ganglion cells, which relay visual information to the brain via the optic nerve. The neurons of the inner plexiform layer help to process visual information as it passes from the surface of the eye to the optic nerve.
To map all of the connections in this small patch of retina, the researchers first took electron micrographs of the targeted section. The Max Planck researchers obtained these images using a technique called serial block face scanning electron microscopy, which they invented to generate high-resolution three-dimensional images of biological samples.