Introduction

Neurobiological systems embody solutions to many difficult problems such as associative memory, learning, pattern recognition, motor coordination, vision and language. It appears they do this via massive parallel processing within and between specialized structures. The mammalian brain is a marvel of coordinated specialization. There are separate areas for each sense modality, with massive intercommunication between areas. There are topographic maps, many specialized neuron types, and quasi-regular small-scale structure (columns and layers) which vary from area to area to accommodate local needs, and plasticity in connections between neurons. Feedback occurs on many levels. This complexity is apparently necessary for the kind of multi-mode processing that brains perform, but it's not clear how much of this structure is necessary to perform isolated tasks such as vision or speech recognition; nor do we know if nature's solutions are optimal. (See chapter 8 of Oster & Wilson (1978), for example, for an interesting discussion of optimization in biology.)

Regardless of whether the brain represents the optimal structure for cognitive processes, it is the only successful one we know of. By analyzing it and modeling it, we may learn the principles on which it operates, and presumably be able to apply these principles to computer technology.