Function follows form. At least in nature. That's a key premise computational neurobiologists use to create computer generated models of brain structures in order to better understand how the brain works. "We start with the assumption there's a very strong relationship between structure and function," a shorts-clad Jim Bower tells me, true to form himself me one unseasonably hot afternoon, when the temperatures in Pasadena are surging past 90 and everyone is seeking refuge inside air conditioned building. "If you look at, say, a car and a bicycle, just by understanding the structure -- in a car, there are multiple seats and an engine, while there isn't in a bicycle -- you know something about how these two different things are used because structure reflects the functions. Similarly, if you could see the neuron and really understand the structure of the neuron, then you would understand the computations performed. "Function follows form," he repeats.

"We believe that so deeply," he adds, "that the models we build start with the form first, and then we use these models to try and understand something about the function." Bower and associates are ardent advocates of computer modeling techniques because they believe they are the only way to understand the intricate "wet wiring" of the brain. "The incorporation of such modeling techniques into the repertoire of basic neuroscientific research is absolutely essential for the eventual success of the field," Bower noted in the journal Trends in Neuroscience. "Even in so-called `simpler systems' it is clear great amounts of detailed physiological and anatomical data alone are not enough to infer how the neural circuits work. Nervous systems are simply too complex to be understood without the quantitative approach that modeling provides."

One might venture to say that just as an electric train set gives a child its first overview of the function of a transportation system within human society and the natural landscape, computer modeling techniques are a vaste and sophisticated "toy" for scientists seeking a more complex picture of how the brain works.

--Linda Marsa