Field Computation in the Brain
Bruce James MacLennan · 1992
We begin with a brief consideration of the {\it 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 {\it subsymbolic} information processing, in which knowledge is represented in terms of very large numbers--or even continua--of {\it 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 {\it field computation}, a kind of continuous information processing that emphasizes spatially continuous {\it 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.