The Human Brain as a Hard Drive

I have always been somewhat put off by fields of endeavor that require large amounts of rote memorization. This is why I chose physics over biology as an undergraduate; I assumed that with physics I could simply derive everything from first principles while with biology, due to the lack of knowledge regarding mechanistic relations in biological systems, was more a matter of memorizing large amounts of names and reactions. No doubt I was also somewhat unsure of my powers of memory; just memorizing correct spellings could give me fits. But I still believe that the human mind is much better suited as an analysis tool rather than a data storage device.

While working with clinicians I am often amazed at how much information they have memorized. In the medical television series "ER" actors posing as doctors frequently rattle off diseases, symptoms, diagnoses and possible treatments but we all know they just memorized these minutes before the cameras started rolling. In reality many doctors do have this type of encyclopedic memory. Dr. John Hutton of the Cincinnati Children's Hospital Medical Center told me that he had memorized about 400 diseases that he could name, diagnose and treat. Based on that knowledge, he could then infer on several times more diseases. Although this volume of knowledge is a tremendous advantage in clinical care, WebMD lists over 4,000 diseases and conditions and the numbers are constantly increasing. We have reached a point where the biomedical knowledge base has overwhelmed the memory capacity of the human brain.

Although it would be easy enough to develop a system to provide rapid information retrieval at the point-of-care, what we really need is rapid knowledge retrieval; information that has already gone through preliminary processing and can deliver answers, not just pages out of medical journals. This is the leading edge of clinical informatics; a fledging field with some daunting challenges.

Basic Research

This is where is all begins; from the creative minds of scientists allowed to pursue their ideas, hunches, dreams, etc. The main mission of scientific research institutions is to conduct basic research; research whose goal is the advancement of knowledge. It is a creative and exploratory process that is motivated by the curiosity of the researcher. Basic research is conducted without a targeted end point; it proceeds from one discovery to the next without a firm idea of what the next discovery will be. Nevertheless, basic research often uncovers new inventions that may have practical applications, applications that may even become commercial.

The process of conducting and funding basic research at an academic institution follows a cyclic pattern: the generation of ideas, grant submission and funding, research, publication of results which leads to the generation of more ideas and the cycle continues. Due to the close relationship between university research labs and the government granting organizations, and the entrenched processes the support the cycle, this cycle can continue as a virtually closed system. The bill, however, is picked up by the taxpayer, a taxpayer who may be interested in where all this money is going. This leads to two ways out of the virtuous (vicious) cycle:

1. The government granting organizations want to provide some sort of metric for demonstrating the benefits of their work.
2. The research organizations want to generate revenues from sources other than the granting organizations.

Although numbers of publications and/or patents are metrics that are often used to measure the productivity of research, they fall a bit flat to the general public. What the public seems most interested in are: jobs and products. If research can generate jobs and the corresponding revenues and/or produce products that are useful to society, the general public will support the spending programs.

The virtuous cycle of grant writing, research and publication is well trod and fairly reliable, the path of technology transfer is much less so. Although there have been attempts to provide ways of funding this path, it is nevertheless fraught with risk. And, for most researchers, embarking on the tech transfer path may mean a reduction in their research productivity; something most researchers that have worked hard to build a reputation are loath to do.