A rat’s brain has millions of neurons, each with up to 10,000 connections to other neurons. This “simple” animal’s neural network is mind-bogglingly complex. Yet a Swiss laboratory has achieved remarkable success duplicating a vast region of a rat’s brain using a supercomputer. They still have a ways to go, however. The computer currently has 10,000 microprocessors, each representing a single neuron in the rat’s brain. To duplicate the entire brain they’ll need a computer 2,000 times bigger. Their ultimate goal is even more ambitious: to create a model of the human brain, with its hundred billion neurons.
Creating a computational model of a portion of a brain has been done before; what’s different about this project is its insistence on absolute biological accuracy:
Researchers opened thousands of rat skulls over the years, removed their brains, and cut them into thin slices, which they kept alive. Then they directed tiny sensors at the individual neurons. They listened to the cells firing neurons, and intercepted the responses coming from the adjacent cells.
In the end, the researchers at Markram’s lab collected the entire repertoire of behavior of hundreds of types of cells in every conceivable situation in a rat’s life — stored in endless tables.
So instead of starting from an observed behavior and attempting to come up with a computer model to replicate it, Markram’s team observed the activity in the brain itself, and created its model based on that. Only afterwards do the look at their model and see if its activity matches real-world behavior.
The so-called neural networks that other researchers have developed for years are very different. A neural network is also meant to behave like a brain, somehow, but how the likeness is achieved — the circuitry underneath — is more or less irrelevant. Someone building a cow using this principle would be content with any milk machine that moos and produces the occasional cowpat.
“That doesn’t help us to understand the biology,” says Markram. The researchers in Lausanne are interested in the real cow: “Our first priority is that we never use tricks to achieve the correct result,” says project manager Schürmann. “If something goes wrong in the simulation, our only option to improve it is by incorporating new biological knowledge.”
Those are certainly high ideals. In future years, we’ll see if the project can continue to live up to them.
(via Mind Hacks)