A Washington State University – WSU research team for the first time has developed a computer algorithm that is nearly as accurate as people are at mapping brain neural networks — a breakthrough that could speed up the image analysis that researchers use to understand brain circuitry.
A report on the WSU team’s work currently in the journal, Bioinformatics.
Like mapping 100 billion homes
For more than a generation, people have been trying to improve understanding of human brain circuitry, but are challenged by its vast complexity. It is similar to having a satellite image of the earth and trying to map out 100 billion homes, all of the connecting streets and everyone’s destinations, said Shuiwang Ji, associate professor in the School of Electrical Engineering and Computer Science and lead researcher on the project.
Researchers, in fact, took more than a decade to fully map the circuitry of just one animal’s brain — a worm that has only 302 neurons. The human brain, meanwhile, has about 100 billion neurons, and the amount of data needed to fully understand its circuitry would require 1000 exabytes of data, or the equivalent of all the data that is currently available in the world.
Neuron by neuron
To map neurons, researchers currently use an electron microscope to take pictures — with one image usually containing a small number of neurons. The researchers then study each neuron’s shape and size as well as its thousands of connections with other nearby neurons to learn about its role in behavior or biology.
Accurate as humans