2 Robot With a Biological Brain: New Research Provides Insights Into How The Brain Works

A multidisciplinary team at the University of Reading has developed a robot which is controlled by a biological brain formed from cultured neurons. This cutting-edge research is the first step to examine how memories manifest themselves in the brain, and how a brain stores specific pieces of data.

The key aim is that eventually this will lead to a better understanding of development and of diseases and disorders which affect the brain such as Alzheimer's Disease, Parkinson's Disease, stoke and brain injury.

The robot's biological brain is made up of cultured neurons which are placed onto a multi-electrode array (MEA). The MEA is a dish with approximately 60 electrodes which pick up the electrical signals generated by the cells. This is then used to drive the movement of the robot. Every time the robot nears an object, signals are directed to stimulate the brain by means of the electrodes. In response, the brain's output is used to drive the wheels of the robot, left and right, so that it moves around in an attempt to avoid hitting objects. The robot has no additional control from a human or a computer, its sole means of control is from its own brain.

The researchers are now working towards getting the robot to learn by applying different signals as it moves into predefined positions. It is hoped that as the learning progresses, it will be possible to witness how memories manifest themselves in the brain when the robot revisits familiar territory.

Professor Kevin Warwick from the School of Systems Engineering, said: "This new research is tremendously exciting as firstly the biological brain controls its own moving robot body, and secondly it will enable us to investigate how the brain learns and memorises its experiences. This research will move our understanding forward of how brains work, and could have a profound effect on many areas of science and medicine."

Dr Ben Whalley from the School of Pharmacy, said: "One of the fundamental questions that scientists are facing today is how we link the activity of individual neurons with the complex behaviours that we see in whole organisms. This project gives us a really unique opportunity to look at something which may exhibit complex behaviours, but still remain closely tied to the activity of individual neurons. Hopefully we can use that to go some of the way to answer some of these very fundamental questions. "

http://www.sciencedaily.com/releases/2008/08/080813175509.htm

3 Quantum Computers Could Excel In Modeling Chemical Reactions

Quantum computers would likely outperform conventional computers in simulating chemical reactions involving more than four atoms, according to scientists at Harvard University, the Massachusetts Institute of Technology, and Haverford College. Such improved ability to model and predict complex chemical reactions could revolutionize drug design and materials science, among other fields.

Writing in the Proceedings of the National Academy of Sciences, the researchers describe "software" that could simulate chemical reactions on quantum computers, an ultra-modern technology that relies on quantum mechanical phenomena, such as entanglement, interference, and superposition. Quantum computing has been heralded for its potential to solve certain types of problems that are impossible for conventional computers to crack.

"There is a fundamental problem with simulating quantum systems -- such as chemical reactions -- on conventional computers," says Alán Aspuru-Guzik, assistant professor of chemistry and chemical biology in Harvard's Faculty of Arts and Sciences. "As the size of a system grows, the computational resources required to simulate it grow exponentially. For example, it might take one day to simulate a reaction involving 10 atoms, two days for 11 atoms, four days for 12 atoms, eight days for 13 atoms, and so on. Before long, this would exhaust the world's computational power."

Unlike a conventional computer, Aspuru-Guzik and his colleagues say, a quantum computer could complete the steps necessary to simulate a chemical reaction in a time that doesn't increase exponentially with the reaction's complexity.

"Being able to predict the outcomes of chemical reactions would have tremendous practical applications," says Ivan Kassal, a graduate student in chemical physics at Harvard. "A lot of research in drug design, materials science, catalysis, and molecular biology is still done by trial and error. Having accurate predictions would change the way these types of science are done."

The researchers demonstrate in PNAS that quantum computers would need to attain a size of about 100 qubits -- which are to quantum computers as bits are to conventional computers -- to outperform current classical supercomputers at a chemical simulation.

"This is still far beyond current prototype quantum computers," Kassal says. "And although it might take millions of quantum elementary operations on a few hundred quantum bits, our work suggests that with quantum computers that are as fast as modern conventional computers, one could simulate in seconds a chemical reaction that would take a conventional computer years."

Rather than using binary bits labeled as "zero" and "one" to encode data, as in a conventional computer, quantum computing stores information in qubits, which can represent both "zero" and "one" simultaneously. When a quantum computer is put to work on a problem, it considers all possible answers by simultaneously arranging its qubits into every combination of "zeroes" and "ones."

Since one sequence of qubits can represent many different numbers, a quantum computer would make far fewer computations than a conventional one in solving some problems. After the computer's work is done, a measurement of its qubits provides the answer.

Aspuru-Guzik and Kassal's co-authors on the PNAS paper are Stephen P. Jordan of MIT, Peter J. Love of Haverford College, and Masoud Mohseni of Harvard. The work was sponsored by the Army Research Office and the Joyce and Zlatko Balokovic Scholarship.

http://www.sciencedaily.com/releases/2008/11/081120130601.htm

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