Google is helping Harvard scientists map the human brain

The result is the most detailed digital map, or “connectivity,” of the human brain.

On Thursday, Lichtman and his colleagues published Results Their efforts were also published in the prestigious journal Science Web rendering The never-before-seen human brain. They come complete with a program that allows visitors to walk through a microscopic alien landscape, so detailed Lichtman can’t resist waxing poetic as he talks about it.

“It’s an alien world inside your own head,” he said. “Neurons are truly stunningly beautiful. There’s no two ways about it.”

True, insights gained from small samples have yet to unravel the mysteries of autism, schizophrenia, or depression. They are still unable to explain the dynamics of human learning, memory and personality at the cellular level. But they represent an important first step in that direction, and provide a preview of the kind of insights we might see in decades to come.

This complex landscape contains strange structures never seen before, and not in any textbook, and in Lichtman’s words, “wonderfully weird.” Nerve cells point in only one of two directions, opposite to each other. Axons, the brain’s long-distance fiber optic cables, are eccentric from straight lines “swirl” Look like turbans – then unravel and resolve again in straight lines. Whatever the purpose Many of these strange contradictions are the subject of future study.

Lichtham’s team was able to map images of some mysterious brain structures with the help of Google researchers. Harvard/Google

Some are already developing paradigm-shifting theories and may reveal fundamental new insights into how the brain works. The discovery of what appears to be a new, extremely rare “superconnection” that connects individuals is particularly significant, Lichtman said. Neurons have axon fibers that carry information that cross the brain. Each superjunction has 50 or more protrusions where there is normally only one. These structures, Lichtman hypothesizes, may help explain how learned habits, such as mindlessly stopping at a red light, become encoded in the physical structure of the brain.

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“Maybe 99 percent of the connections between axons and individual brain cells are these super weak connections,” Lichtman says. But, “the stronger the connections, the more efficient the information flows. That may be one way to explain the fact that after you learn something, you have this automatic ability to do it.”

The new paper is part of a larger series of projects funded by the BRAIN Initiative, a major science initiative launched by the Obama administration in 2013 to uncover fundamental insights into the human brain.

“It’s a big deal,” said Ed Lean, a neuroscientist at the Allen Institute for Brain Sciences in Seattle who was not involved in the study. The mapping is “really the first of its kind in a human.”

Leanne helps lead Another component of the BRAIN initiative, He said Lichtman’s work could revolutionize our understanding of the human brain and greatly improve our ability to treat disease.

“We have a very poor understanding of that circuit,” he said. “Imagine your cell phone is broken, you have no idea about the components of the cell phone or how they are connected to each other, and you are trying to fix it. If we don’t understand how the thing is put together, we have very little chance of fixing it.

Dr. Jeffrey Lichtman is working on a neural wiring diagram.David L. Ryan/Globe staff

Originally funded as part of a $7 million five-year grant from the National Institutes of Health, Lichtman’s project recently received $30 million. More than five years from the relevant NIH program. The federal agency’s goal is to advance our understanding of diseases that affect cognition and emotion.

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Money, which finances others Related projectsSupplemented by Google’s free joint ventures, it provided the computational muscle and engineering labor needed for the project.

After staining, the human brain sample was sectioned and imaged In Lichtman LaboratoryGoogle’s engineers use machine learning to put those pieces back together and use colors to make the wiring visible to the naked eye.

The challenge aims to recreate that 1-cubic-millimeter model of the human brain Much better in digital form, imaging the entire human brain would have to wait. An accurate picture The whole human brain That would roughly equal the amount of data produced worldwide in one year, Lichtman says.

That’s why the next attempt will be more modest: Over the next five years, Lichtman and his collaborators aim to image the first 10-cubic-millimeter region. A Mouse brain. The project is a proof of concept for the ultimate goal: a full mouse brain, 50 times larger.

“The human brain is a factor of a thousand larger than a mouse brain,” says Lichtman. “We don’t have the ability to store that information.”

The payoff of all these efforts can ultimately prove enormous. Google and others hope to use the findings to improve their ability to invent artificial intelligence algorithms that model the human brain.

Lichtman, for his part, hopes to answer fundamental questions about the human mind: How are representations of the world embedded in our heads? What is the physical basis of knowledge?

The project had already taken him into intellectual territory he hadn’t expected to enter. The experience of sitting in his office with the new “NeuroGlancer” tool allowed him to manipulate the visual landscape of neural connectivity as “awesome,” “magical” and “fantasy.” He wanted to click on every cell.

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Citing the names of Magellan, Americo Vespucci and other famous explorers, Lichtman extolled the thrill of discovery.

“It’s like using the Hubble telescope or the James Webb telescope,” says Lichtman. “But it’s not a telescope, it’s a microscope, which allows us to look inside. Of course, there are all kinds of things we’ve never seen before. We’re exploring a Terra occulta.

Dr. Jeffrey Lichtman is leading efforts to develop a neural wiring diagram.David L. Ryan/Globe staff

Adam Piore can be reached at [email protected].

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