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“It’s very exciting,” says Terrence Sejnowski, head of the Computational Neurobiology Laboratory at the Salk Institute, in La Jolla, CA. “The technology has matured to the point where it’s possible to think about large-scale simulations.” For example, Sejnowski studies how the thalamus, a brain area thought to relay and integrate information from different parts of the brain, interacts with the cortex. “We can currently do small simulations of hundreds to thousands of neurons, but it would be great to be able to scale that up,” he says.

The million-neuron grid will have a processing speed equivalent to 300 teraflops, meaning that unlike computer-software simulations of the cortex, the hardwired silicon model will be able to run in real time. “Instead of running a thousand software instructions, it’s just current running through transistors, just like real neurons,” says Boahen.

Of course, the project will be a challenging one. “They will have to get a large number of chips to work together,” says Douglas. “To put together a structure on the scale Kwabena has in mind–no one has done that yet.” But it could become a turning point in the field. Douglas likens the current state of neuromorphic engineering to the early stages of computer-chip design. “People had been working on different types of logic gates, but it took a whole different worldview to build computer chips,” he says.

Engineers ultimately hope to use the information generated by the silicon cortex in a variety of ways–to build better neural prostheses, for example. “The real-time aspect of this technology allows us in principle to interface the silicon cortex with the real cortex or brain,” says Gert Cauwenberghs, a neuroengineer at the University of California, San Diego. “There is the promise, at least in the future, to build a prosthesis to replace some lost motor function or sensory function.”

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Credit: Joseph Lin

Tagged: Computing, Biomedicine, brain, neuroscience, silicon, chip, neuron

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