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The brain in silico

At the linkurl:Society for Neuroscience's;https://www.sfn.org/ annual meeting today (Nov 5), linkurl:Kathie Olsen;https://www.nsf.gov/news/speeches/olsen/olsen_bio.jsp laughingly introduced linkurl:Kwabena Boahen's;https://www.stanford.edu/group/brainsinsilicon/goals.html talk with, "Good luck." Boahen, a Stanford bioengineering professor, went on to describe his ambitious goals of creating affordable linkurl:supercomputers;https://www.the-scientist.com/2007/8/1/44/1/ neuroscientists can use in simu

Written byKerry Grens
| 2 min read

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At the linkurl:Society for Neuroscience's;https://www.sfn.org/ annual meeting today (Nov 5), linkurl:Kathie Olsen;https://www.nsf.gov/news/speeches/olsen/olsen_bio.jsp laughingly introduced linkurl:Kwabena Boahen's;https://www.stanford.edu/group/brainsinsilicon/goals.html talk with, "Good luck." Boahen, a Stanford bioengineering professor, went on to describe his ambitious goals of creating affordable linkurl:supercomputers;https://www.the-scientist.com/2007/8/1/44/1/ neuroscientists can use in simulating brain systems in real time. Efforts to simulate just a small fraction of the billions of neurons and networks in the brain on IBM's linkurl:Blue Gene;https://bluebrain.epfl.ch/ supercomputers are 5,000 times slower than real time, according to Boahen. During his talk at the San Diego conference, Boahen demonstrated on his Neurogrid chip (a computer chip about the size of a notecard, plugged into a laptop) the real-time activity of 256 interconnected "neurons." His aim for 2008 is to make 16 chips, totaling one million neurons, that will communicate with each other. The question, as one audience member asked, is whether Boahen's neurons resemble real ones. His answer is that they resemble real neuronal activity -- action potentials. His approach capitalizes on the physical similarities between ion channels and transistors on chips, which is that each must overcome some energy barrier to switch from one state to another. In the case of ion channels, the states go from closed to open, and in transistors, from source to drain. The current flowing through the transistor mimics that of the current flowing through an ion channel. The activity of each transistor "neuron" on Boahen's Neurogrid chip acts like a cell during an action potential, which he said is different from how Blue Gene works. Boahen didn't say how much his Neurogrid chip might cost, although the successful GRAPE6 supercomputer used by astrophysicists (which is much smaller than Blue Gene and can operate in real time speed) is only about $40,000 -- a big improvement on the multi-million dollar Blue Gene. In about four years, Boahen projected, he hopes to make affordable supercomputers like GRAPE6 available to neuroscientists.
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Meet the Author

  • kerry grens

    Kerry served as The Scientist’s news director until 2021. Before joining The Scientist in 2013, she was a stringer for Reuters Health, the senior health and science reporter at WHYY in Philadelphia, and the health and science reporter at New Hampshire Public Radio. Kerry got her start in journalism as a AAAS Mass Media fellow at KUNC in Colorado. She has a master’s in biological sciences from Stanford University and a biology degree from Loyola University Chicago.

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