Why Google Just Made The Most Detailed Map Of The Human Brain

What do artificial intelligence and the human brain have in common? It appears Google wants to find out, and is willing to go to great lengths to unlock the secrets.

It's only a tiny sliver of the brain, but the map led to several surprising discoveries, Google Editor in Chief Ari Marini wrote in a post in which Google Research Scientist Viren Jain described neurons.

“For example, we found some of the wires will wrap themselves into these giant knots,” Jain said. “We have no idea why — nobody's ever seen it before.”

Mapping the entire human brain would require gathering and analyzing as much as a zettabyte of data — equal to one billion terabytes — which is beyond the current capabilities of existing technologies.

“If we were to map the whole human brain right now, it might take billions of dollars and hundreds of years,” Jain said.



Jain and his team are now working with mice to help solve mysteries about the human mind. Think about the innovations in AI, advertising, and search when Google researchers explore the mysteries around how memories are stored and retrieved, how the brain recognizes objects and faces, and why humans need so much sleep.

“One reason we don't have answers to these questions is that we don’t yet have the data we need in order to study the brain,” Jain said.

The human brain has about 86 billion neurons connected to each other by more than 100 trillion synapses that enable people to think, feel, move and interact with the world, Marini wrote. So by creating a map of neural connections, known as “connectome,” Google can unlock new understandings of how our brains work, and why they sometimes don't.

Knowing how the brain works can become the Holy Grail for a search and advertising company, and discovering what types of factors AI and the human brain have in common can further innovations.

It seems that Google is willing to go to great lengths to unlock the secrets of the universe — not only in areas such as supporting ways to identify early on, slow or eliminate Alzheimer's, but in the field of technology as well.

Company researchers will undoubtedly find the connection between AI and real-life forms to help make decisions on how far to take synthetic thinking for search, performance, content and advertising — and how to strengthen the connection.

The post does not provide a lot of detail about this, but that's where my brain went after reading the interview.

Building detailed maps at the synaptic level, researchers had to image the brain at nanometer resolution and work with massive amounts of data. This process requires innovation in imaging techniques, AI algorithms and data-management tools. In preparation for this endeavor, 10 years ago Google Research formed its Connectomics team.

During the past decade, the team has developed technologies in order to more efficiently process, analyze and share data. It has introduced flood-filling networks that replaced the manual effort of coloring in cells across brain images by using machine learning to automatically trace the paths of neurons through layers of tissue.

Yes, this is all Google, the organic and paid-search advertising company. Its SegCLR algorithm automatically identifies distinct parts of cells and cell types within these networks. When developers created software such as TensorStore and Neuroglancer, it helped to store, process and visualize large multidimensional images.

Researchers have quietly focused for years on either mapping large portions of the brains of small animals, or small pieces of brain tissue from large animals. The team has mapped half of a fruit fly's brain, created connectomes for portions of the brains of the zebra finch and zebrafish larvae, and in May the aforementioned map of 1 cubic millimeter of human brain tissue was published in Science.

Now it's time to share the connectomes.

2 comments about "Why Google Just Made The Most Detailed Map Of The Human Brain".
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  1. John Grono from GAP Research, July 9, 2024 at 9:14 p.m.

    I can't wait for when AI finds out everything exactlby about how the human brain works.   Then we can give up reading endless articles like this.

  2. Laurie Sullivan from lauriesullivan, July 9, 2024 at 9:42 p.m.

    Thank you so much, John, for taking the time to comment.

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