ABSTRACT
We begin with a brief consideration of the topology of knowledge. It has traditionally been assumed that true knowledge must be represented by discrete symbol structures, but recent research in psychology, philosophy and computer science has shown the fundamental importance of subsymbolic information processing, in which knowledge is represented in terms of very large numbers — or even continua — of microfeatures. We believe that this sets the stage for a fundamentally new theory of knowledge, and we sketch a theory of continuous information representation and processing. Next we consider field computation, a kind of continuous information processing that emphasizes spatially continuous fields of information. This is a reasonable approximation for macroscopic areas of cortex and provides a convenient mathematical framework for studying information processing at this level. We apply it also to a linear-systems model of dendritic information processing. We consider examples from the visual cortex, including Gabor and wavelet representations, and outline field-based theories of sensorimotor intentions and of model-based deduction.
