12 February 2007

The Silicon Cortex

Over the years a lot of AI researchers and electrical engineers have tried to model the neurological function of parts of the brain on silicon. Tech Review features a current effort by Stanford neuroengineer Kwabena Boahen.
"Brains do things in technically and conceptually novel ways--they can solve rather effortlessly issues which we cannot yet resolve with the largest and most modern digital machines," says Rodney Douglas, a professor at the Institute of Neuroinformatics, in Zurich. "One of the ways to explore this is to develop hardware that goes in the same direction."

Neurons communicate with a series of electrical pulses; chemical signals transiently change the electrical properties of individual cells, which in turn trigger an electrical change in the next neuron in the circuit. In the 1980s, Carver Mead, a pioneer in microelectronics at the California Institute of Technology, realized that the same transistors used to build computer chips could be used to build circuits that mimicked the electrical properties of neurons. Since then, scientists and engineers have been using these transistor-based neurons to build more-complicated neural circuits, modeling the retina, the cochlea (the part of the inner ear that translates sound waves into neural signals), and the hippocampus (a part of the brain crucial for memory). They call the process neuromorphing.

Now Kwabena Boahen, a neuroengineer at Stanford University, is planning the most ambitious neuromorphic project to date: creating a silicon model of the cortex. The first-generation design will be composed of a circuit board with 16 chips, each containing a 256-by-256 array of silicon neurons. Groups of neurons can be set to have different electrical properties, mimicking different types of cells in the cortex. Engineers can also program specific connections between the cells to model the architecture in different parts of the cortex.

I am putting my money on Jeff Hawkins and Rodney Brooks. But when attempting something this ambitious, it doesn't hurt to include as many contestants as possible.

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