Ten years ago, Dr. Jeff Lichtman, a molecular and cellular biology professor at Harvard University, received a little brain sample in his laboratory. Despite its small size, one cubic millimetre of tissue might hold 57,000 cells, 230 millimetres of blood arteries, and 150 million synapses. Lichtman and his team eventually obtained 1,400 terabytes of data from the sample, which is roughly equivalent to the content of more than 1 billion books.
Following a decade of close work with Google scientists, the lab team’s data has resulted in the most precise map of a human brain sample ever made.
Where did the brain sample come from?
The brain sample was obtained from a patient with severe epilepsy. Lichtman explained that it is the usual procedure to remove a little bit of the brain to halt the seizures and then examine the tissue to ensure it is okay.
Also read: Australian Doctor Reports Being Cancer-Free A Year After Self-Treating His ‘Incurable’ Brain Tumor
“But it was anonymized, so I knew next to nothing about the patient, other than their age and gender,” he stated.
To analyze the sample, Lichtman and his team first sliced it into thin slices with a diamond-bladed knife. The parts were then implanted in a hard resin and chopped very thinly.
“About 30 nanometers, or nearly one thousandth the thickness of a human hair. They were almost invisible if we hadn’t dyed them with heavy metals, which made them visible when undertaking electron imaging,” he explained.
The crew ended up with several thousand slices, which were picked up with custom-made tape to create a type of film strip: “If you take a picture of each of those sections and align those pictures, you get a three-dimensional piece of the brain at the microscopic level.”
To make sense of the photos, Google scientists utilized AI-based processing and analysis to determine what kind of cells were present in each image and how they were connected.
The end result is an interactive 3D model of brain tissue, as well as the largest dataset of human brain structure ever created at this resolution.
Google made it available online under the name “Neuroglancer,” and research was published in the journal Science at the same time, with Lichtman and Jain as co-authors.
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