Skip to main content Accessibility help
  • Cited by 2
  • Print publication year: 1990
  • Online publication date: May 2010

Representation and high-speed computation in neural networks



What I want to sell you is some neuroscience. I want to sell you the idea that current neuroscience has become directly relevant to the cognitive/computational issues that have always concerned AI. In what follows I shall outline a highly general scheme for representation and computation, a scheme inspired in part by the microarchitecture of both the cerebral and the cerebellar cortex. We shall also explore some of the interesting properties displayed by computing systems of this general kind.

The basic claim, to be explained as we proceed, is that the brain represents specific states of affairs by implementing specific positions in an appropriate state space, and it performs computations on such representations by means of general coordinate transformations from one state space to another. (There is no suggestion that this is the only mode of information-processing in the brain. But its role does seem to be nontrivial.)

That one can perform computations by this abstract means will be old news to some readers. For them, I hope to occasion surprise with evidence about the implementation of these procedures in the microanatomy of the empirical brain. Also intriguing is the natural way in which problems of sensorimotor coordination can be solved by this approach, since from an evolutionary point of view, sensorimotor coordination is where cognitive activity had its raw beginnings. Of further interest is the very great representational power of such systems, and the truly extraordinary speed with which even biological implementations of such procedures can perform computations of great complexity.