Brains have long been viewed as different kinds of information processors than electronic computers because of differences in componentry (von Neumann, 1958). Von Neumann used the all-or-none law of neural activity to infer that the brain was essentially a digital information processor, but made other observations that differentiated the brain from other digital devices. Many of his observations match nicely with modern connectionist criticisms of classical models. Von Neumann noted that while electronic computers use a small number of fast components, the brain consists of a large number of slower components (i.e. neurons). As a result, the brain must be a parallel processing device that “will tend to pick up as many logical (or informational) items as possible simultaneously, and process them simultaneously” (p. 51). Von Neumann also argued that neural information processing would be far less precise (in terms of decimal point precision) than electronic information processing. However, this low level of neural precision would be complemented by a comparatively high level of reliability, where noise or missing information would have far less effect than is the case for electronic computers. Given that the basic architecture of the brain involves many connections amongst many elementary components, and that these connections serve as a memory, the brain’s memory capacity should far exceed that of digital computers.
- von Neumann, J. (1958). The Computer And The Brain. New Haven, CN: Yale University Press.
(Added November 2010)