Human brain mapped in 3-D with high resolution

“BigBrain” model, the most detailed atlas yet, could improve brain scanning tools and neurosurgeons’ navigation

A new 3-D map of the brain is the best thing since sliced cold cuts, at least to some neuroscientists.

A BIG BRAIN PROJECT By slicing a brain into ultrathin sheets and digitally pasting them together, researchers have created the first 3-D high-resolution map of the human brain. Courtesy of Amunts, Zilles, Evans et al

“It’s a remarkable tour-de-force to reconstruct an entire human brain with such accuracy,” says David Van Essen, a neuroscientist at Washington University in St. Louis.

Using a high-tech deli slicer and about 100,000 computer processors, researchers shaved a human brain into thousands of thin slivers and then digitally glued them together. The result is the most detailed brain atlas ever published. Dubbed BigBrain, the digital model has a resolution 50 times greater in each of the three spatial dimensions than currently available maps, researchers report in the June 21 Science.

The difference is like zooming from a satellite view of a city down to the street level, says coauthor Alan Evans, a neuroimaging scientist at McGill University in Montreal.

BigBrain allows researchers to navigate the landscape of the human cortex, the rugged outer layer of the brain. And unlike previous maps, the tool also lets scientists burrow beneath the surface, tunnel through the brain’s hemispheres and step slice-by-slice through high-res structural data.

Around 100 years ago, neuroscientists relied on thick slabs of brain tissue to crudely chart out neural regions. More recently, imaging tools such as MRI have let researchers take a more detailed look. But even the very best MRI maps are still a little fuzzy, says Hanchuan Peng, a computational biologist at the Allen Institute for Brain Science in Seattle.

In 2010, a team of Chinese researchers constructed a digital map of the mouse brain using techniques similar to the ones that produced BigBrain. But until now, no one had done it in humans. Because the human brain is thousands of times bigger than the mouse brain, Evans and colleagues had to massively scale up slicing and computing methods. First, Katrin Amunts and colleagues at the Jülich Research Center in Germany carved the donated brain of a 65-year-old woman into 7,404 ultrathin sheets, each about the thickness of plastic wrap.

Next, researchers stained the sheets to boost contrast, took pictures of each sheet with a flatbed scanner, and then harnessed the processing power from seven supercomputing facilities across Canada to digitally stitch together the images. In all, the researchers analyzed about one terabyte, or 1,000 gigabytes, of image data. That’s about the same amount of data as 250,000 MP3 songs.

“Your laptop would choke if it tried to run a typical image-processing program to look at this dataset,” Evans says.

His team designed a software program that lets researchers dig into BigBrain’s data. Users will be able to pick up the brain, rotate it in any direction and cut through any plane they want. “It’s like a video game,” he says.

 Evans hopes BigBrain will provide a digital scaffold for other researchers to layer on different kinds of brain data. Scientists could stack on information about chemical concentrations or electrophysical signals, just as climate and traffic data can be layered onto a geographical map.

The 3-D map could also help researchers interpret data from lower-resolution brain-scanning techniques such as MRI and PET, study coauthor Karl Zilles of the Jülich Research Center said during a press briefing June 19. Overlaying images from these scans onto BigBrain might give neuroimagers a better idea of where exactly damaged tissue lies in diseased brains.

And neurosurgeons might use BigBrain to guide placement of electrodes during deep-brain stimulation for Alzheimer’s or Parkinson’s diseases, he said.

Though all human brains have largely similar architecture, Evans says, every person has subtle shape variations. As a result, he’d like to make maps of more brains for comparison.

Now that the teams have ironed out BigBrain’s technical kinks, the researchers think they can compile a second brain’s map in about a year. “The computational tools are all largely in place now,” Evans says.

Meghan Rosen is a staff writer who reports on the life sciences for Science News. She earned a Ph.D. in biochemistry and molecular biology with an emphasis in biotechnology from the University of California, Davis, and later graduated from the science communication program at UC Santa Cruz.

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