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== History ==
In the early 1980s, having laid out the foundations of VLSI,<ref>C. Mead and L. Conway, ''Introduction to VLSI systems''. Addison-Wesley Reading Mass. (1980)</ref> [[Carver Mead]] became interested in exploring the similarities between computation done in the brain and the type of computations that could be carried out in analog silicon electronic circuits. Mead joined with [[Nobelist]] [[John Hopfield]], who was studying the theoretical foundations of neural computation,<ref name=HopfieldNets>Hopfield, J.J. ''[http://www.pnas.org/content/pnas/79/8/2554.full.pdf Neural networks and physical systems with emergent collective computational abilities].'' Proc. NatL Acad. Sci. USA Vol. 79, pp. 2554-2558, April 1982</ref> to expand his study. Mead and Hopfield's first joint course in this area was entitled “Physics of Computation”; Hopfield teaching about his work in neural networks and Mead about his work in the area of replicating neuronal structures in highly integrated electronic circuits.<ref name=MeadInterview>Shirley K. Cohen, ''Interview with Carver Mead''. Archives of the California Institute of Technology. ([https://docs.google.com/viewer?url=http%3A%2F%2Foralhistories.library.caltech.edu%2F133%2F02%2FOH_Mead.pdf PDF])</ref> Given the interest among both students and faculty, they decided to expand upon these themes in the following year. [[Nobelist]] [[Richard Feynman]] joined them and three separate courses resulted: Hopfield's on neural networks, Mead's on neuromorphic analog circuits,<ref>C. Mead, ''Analog VLSI and neural systems''. Addison-Wesley (1989)</ref> and Feynman's course on the physics of computation.<ref name=MeadInterview/><ref>R.P. Feynman, ''Feynman Lectures on Computation''. Tony Hey and Robin W. Allen ed. Perseus Books Group (2000) {{ISBN|0738202967}}</ref> At this point, Mead and Hopfield realized that a new field was emerging with neural scientists and the people doing the computer models and circuits all talking to each other.
In the fall of 1986, [[John Hopfield]] championed forming an interdisciplinary Ph.D. program to give birth to a scholarly community studying questions arising at the interface between neurobiology and electrical engineering, computer science and physics. It was called ''Computation and Neural Systems'' (CNS). The unifying theme of the program was the relationship between the physical structure of a computational system (physical or biological hardware), the dynamics of its operation and the computational problems that it can efficiently solve. The creation of this multidisciplinary program stems largely from progress on several previously unrelated fronts: the analysis of complex neural systems at both the single-cell and the network levels
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