Scientists Develop New, Incredibly Fast 3D Brain Imaging Technique

The human brain is often described as a meager mass of tissue that is colossal in its complexity. Seeing as neuroscientists still struggle to fathom the mind of a fruit fly, whose brain is the size of a poppy seed and has only 100,000 neurons, a human’s noggin at 1.4 kilograms (3 pounds) and over 80 billion neurons is a feat on another level.

Still, progress is progress and now scientists have mapped in 3D a fruit fly’s brain in nanoscale detail in less than three days. This is compared to the years it previously took.

“You can spend years and years getting an EM image of one fly brain,” said co-author Eric Betzig, a Nobel laureate and professor at UC Berkeley, in a statement. “I can see us getting to the point of imaging at least 10 fly brains per day.”

Their new technique is called ExLLSM, which combines two state-of-the-art imaging technologies to make the brain swell like a balloon and yet keep the delicate internal biology intact. The first, called expansion microscopy (EM), expands the tissue, while lattice light-sheet microscopy (LLSM) uses focused beams of light to create a 3D image of the brain one slice at a time.

“The idea does sound a bit crude,” admitted Ruixuan Gao, one of the lead authors from MIT. “We’re stretching tissues apart.” 

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In fact, when Gao and fellow team lead Shoh Asano asked to use Betzig’s microscope, he said yes but didn’t hold much hope of success.

“I was going to show them [it wouldn’t work],” said Betzig. Instead, “I couldn’t believe the quality of the data I was seeing. You could have knocked me over with a feather.”

With the two techniques combined, they produced something beautiful in its intricacy and simplicity of use. The new method is high speed, high resolution, and yet still gentle. The EM makes the brain bigger by infusing the tissue with swellable gels, delicately separating molecules from each other and making the structures easier to see under a microscope. 

However, they were soon confronted with another hurdle: the thicker a sample is, the harder it is to image. This is due to the need to shine light on them, but too much and you can photobleach portions of it. This is a predicament, especially considering they expanded the brain tissue by a factor of four, which pumps up the volume 64-fold.

Despite all odds, the lattice light-sheet microscope was up to the task. This is because rather than imaging the brain all at once, it “sweeps an ultrathin sheet of laser light through a specimen,” wrote the authors in Science. They were able to capture highly detailed images at a resolution of about 60 nanometers. 

Over the last two years, they kept improving the technique, rallying biologists, physicists, microscopists, and computer scientists to their discovery. “This is like an Avengers-level collaboration,” said Gao. 

Once imaged, the team of scientists were not done. They next needed to use complicated computational stitching to piece the pictures together.

“Stephen [Saalfeld] and Igor [Pisarev] saved our bacon,” said Betzig. “They dealt with all the horrible little details of image processing and made it work on each multi-terabyte data set.”

They combined this 200 terabytes of data to make a movie of the internal workings of a fruit fly’s brain. Still, much work remains. A human brain contains tens of billions of neurons that connect through around 7,000 synapses each in a network of tremendous complexity. Furthermore, any image of a once-living specimen is an imperfect version, and the more steps that are required, the more imperfect it becomes. 

EM has additional steps of polymer infusion, gelation, label attachment, digestion, expansion, and handling that can perturb such detailed intricacy even more. This, the researchers note, means careful controls are essential.

“We’ve crossed a threshold in imaging performance,” said Ed Boyden. “That’s why we’re so excited. We’re not just scanning incrementally more brain tissue, we’re scanning entire brains.”

Original Article : HERE ; This post was curated & posted using : RealSpecific

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