Comprehending how the brain functions is probably the greatest intellectual and scientific challenge we face. We have virtually no knowledge of the neural mechanisms of relatively simple brain processes, such as perception, motor planning, and retrieval of memories, and we are completely ignorant regarding more complex processes, such as cognition, thinking, and learning.

The cerebral cortex (and particularly its most recently developed part, the neocortex) is considered essential for carrying out these higher brain functions. Although the neocortex has been divided into many subareas, each subarea contains many small modules composed of the same building elements, which are interconnected in essentially the same manner. I subscribe to the belief that the same basic computations are carried out by each small region of the neocortex. Understanding the nature of these computations and their neurophysiological mechanisms is a major challenge for science today.

There are many strategies for attacking these questions. Some researchers believe that one must first prepare detailed descriptions of all the types of neurons and of their internal and external connections. Others believe that the most urgent need is to construct appropriate models to describe how the brain might work. Between these extreme bottom-up and top-down strategies there is room for a multitude of intermediate approaches. The work reported here exemplifies one such approach. It combines anatomical observations, electrophysiological measurements, and abstract modeling in order to obain a quantitative description of cortical function.