A smart chip: Scientists in Europe are using conventional chip production techniques to create circuits that mimic the structure and function of the human brain. This early prototype has just 384 neurons and 100,000 synapses, but the latest version contains 200,000 neurons and 50 million synapses.
Karlheinz Meier

Computing

Building a Brain on a Silicon Chip

A chip developed by European scientists simulates the learning capabilities of the human brain.

  • Wednesday, March 25, 2009
  • By Duncan Graham-Rowe

An international team of scientists in Europe has created a silicon chip designed to function like a human brain. With 200,000 neurons linked up by 50 million synaptic connections, the chip is able to mimic the brain's ability to learn more closely than any other machine.

Although the chip has a fraction of the number of neurons or connections found in a brain, its design allows it to be scaled up, says Karlheinz Meier, a physicist at Heidelberg University, in Germany, who has coordinated the Fast Analog Computing with Emergent Transient States project, or FACETS.

The hope is that recreating the structure of the brain in computer form may help to further our understanding of how to develop massively parallel, powerful new computers, says Meier.

This is not the first time someone has tried to recreate the workings of the brain. One effort called the Blue Brain project, run by Henry Markram at the Ecole Polytechnique Fédérale de Lausanne, in Switzerland, has been using vast databases of biological data recorded by neurologists to create a hugely complex and realistic simulation of the brain on an IBM supercomputer.

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FACETS has been tapping into the same databases. "But rather than simulating neurons," says Karlheinz, "we are building them." Using a standard eight-inch silicon wafer, the researchers recreate the neurons and synapses as circuits of transistors and capacitors, designed to produce the same sort of electrical activity as their biological counterparts.

A neuron circuit typically consists of about 100 components, while a synapse requires only about 20. However, because there are so much more of them, the synapses take up most of the space on the wafer, says Karlheinz.

The advantage of this hardwired approach, as opposed to a simulation, Karlheinz continues, is that it allows researchers to recreate the brain-like structure in a way that is truly parallel. Getting simulations to run in real time requires huge amounts of computing power. Plus, physical models are able to run much faster and are more scalable. In fact, the current prototype can operate about 100,000 times faster than a real human brain. "We can simulate a day in a second," says Karlheinz.

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nekote

139 Comments

  • 1051 Days Ago
  • 03/25/2009

memristors, anyone?

Memristors, first proposed by Prof. Chua in 1971 and recently fabricated by HP seem like they would be a natural for brain / self-organizing / learning / neural net circuitry.

Presumably simplifying and densifying the circuitry.

Any thoughts of incorporating them into this silicon circuitry?
Or even more or less substituting memristors, en masse?

Reply

rafaelcp

1 Comment

  • 1051 Days Ago
  • 03/25/2009

Mr. Markram is very prudent and clear about his research, unlike other researchers claiming to have built artificial brains. I like it.

Reply

gsegura

5 Comments

  • 1049 Days Ago
  • 03/27/2009

No Darwin allowed here

Even though it must take bast amounts of processing and information for a conscience to arise. Having this technology at reach hand makes me pray for the engineers to unplug the thing every night.
Why give Darwin a chance to mess with it? so next thing you know is you're getting a socket installed in the back of your neck. ;)

Reply

mergatroidal

8 Comments

  • 1045 Days Ago
  • 03/31/2009

Stanford?

Encouraging, indeed.

Reply

szeldich

2 Comments

  • 494 Days Ago
  • 10/03/2010

Building of a human brain

Sorry, but all of that effort will bring the same result as Stuart Hameroff attempt to build the quantum brain.

We could left aside the technical difficulties of the process of modelling. Brain is a dynamic net of interconnections which are reflecting something. Could researchers explain what is reflected in it?

It is impossible to have a working model of a brain without answering on that question.

Good luck, Michael

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