Lessons from the Brain: Toward an Intelligent Molecular Computer

April 25, 2010 By Marcia Goodrich, Michigan Technological University
Magnetic resonance images of human brain during different functions appear on top. Similar evolving patterns have been generated on the molecular monolayer one after another (bottom). A snapshot of the evolving pattern for a particular brain function is captured using Scanning Tunneling Microscope at 0.68 V tip bias (scale bar is 6 nm). The input pattern to mimic particular brain function is distinct, and the dynamics of pattern evolution is also typical for a particular brain operation. Credit: Anirban Bandyopadhyay

(PhysOrg.com) -- Information processing circuits in digital computers are static. In our brains, information processing circuits—neurons—evolve continuously to solve complex problems. Now, an international research team from Japan and Michigan Technological University has created a similar process of circuit evolution in an organic molecular layer that can solve complex problems. This is the first time a brain-like "evolutionary circuit" has been realized.

A team of researchers from Japan and Michigan Technological University has built a molecular computer using lessons learned from the human brain.

Physicist Ranjit Pati of Michigan Tech provided the theoretical underpinnings for this tiny computer composed not of silicon but of organic molecules on a gold substrate. “This molecular computer is the brainchild of my colleague Anirban Bandyopadhyay from the National Institute for Materials Science,” says Pati. Their work is detailed in “Massively Parallel Computing on an Organic Molecule Layer,” published April 25 online in Nature Physics.

“Modern computers are quite fast, capable of executing trillions of instructions a second, but they can’t match the intelligent performance of our brain,” says Pati. “Our neurons only fire about a thousand times per second. But I can see you, recognize you, talk with you, and hear someone walking by in the hallway almost instantaneously, a Herculean task for even the fastest computer.”

That’s because information processing is done sequentially in digital computers. Once a current path is established along a circuit, it does not change. By contrast, the electrical impulses that travel through our brains follow vast, dynamic, evolving networks of neurons that operate collectively.

The researchers made their different kind of computer with DDQ, a hexagonal molecule made of nitrogen, oxygen, chlorine and carbon that self-assembles in two layers on a gold substrate.

The DDQ molecule can switch among four conducting states—0, 1, 2 and 3—unlike the binary switches—0 and 1—used by digital computers.

“The neat part is, approximately 300 molecules talk with each other at a time during information processing,” Pati says. “We have mimicked how neurons behave in the brain.”

“The evolving neuron-like circuit network allows us to address many problems on the same grid, which gives the device intelligence," Pati says. As a result, their tiny processor can solve problems for which algorithms on computers are unknown, especially interacting many-body problems, such as predictions of natural calamities and outbreaks of disease. To illustrate this feature, they mimicked two natural phenomena in the molecular layer: heat diffusion and the evolution of cancer cells.

In addition, their molecular processor heals itself if there is a defect. This property comes from the self-organizing ability of the molecular monolayer. “No existing man-made computer has this property, but our brain does,” Bandyopadhyay says. “If a neuron dies, another neuron takes over its function.”

“This is very exciting, a conceptual breakthrough,” Pati says. “This could change the way people think about molecular computing.”

An abstract of “Massively Parallel Computing on an Organic Molecule Layer” is available at Nature Physics.

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not rated yet Apr 25, 2010
But it should be possible to program a virtual hardware that dynamically changes its structure. If that is the case, then that means, that given enough time, we can, with certain accuracy - model any process on our static hardware.
3 / 5 (2) Apr 25, 2010
I'm sorry but this article is really a terrible read. It's just plainly confusing and poorly written.Please let someone revise it next time before posting!
not rated yet Apr 25, 2010
check out techdimwit.com more on technology and Brain Machine interfaces.

Ray Kurzweil and so fourth.

Nitish Kannan
not rated yet Apr 26, 2010
looks like B.O.B. to me, Brain on Biscuit.
No enslave Bob, Free Bob, Free Bob now.
not rated yet Apr 26, 2010
But it should be possible to program a virtual hardware that dynamically changes its structure. If that is the case, then that means, that given enough time, we can, with certain accuracy - model any process on our static hardware.

True, but simulation is not the same as the real thing. While your normal digital computer will be busy running extra processes to simulate a structure that dynamically changes, this thing actually does that. To simulate one second of the dynamic "brain-like" processor a normal digital computer might require a thousand seconds. I'd rather have the real thing than a simulation, as it will be faster and more energy efficient than a clunky simulation.
not rated yet Apr 26, 2010
The graphic provided is misleading. The lower (nano) images have been selected because of a resemblance to the brain MRI images above. These are utterly different entities in structure, scale and complexity and the resemblance is as scientifically significant as seeing a face on the moon or the Virgin Mary on a piece of toast. Similar patterns have been observed in complex inorganic salt solutions.
Apr 30, 2010
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