hen Justine Henin-Hardenne rips a
cross-court forehand at the Australian Open or Tom Brady, the New
England Patriots quarterback, dodges an onrushing defender, each
looks like the very definition of living in the moment. Like other
great athletes, they often appear to rely on speed, strength and
lightning-fast reactions.
There seems to be little time for highly advanced quantitative
analysis that weighs current observations against past experiences
to suggest a plan of attack.
But this kind of analysis is precisely what the human brain does
when facing a physical challenge, according to a study by two
European scientists published in the current issue of Nature. The
more uncertainty that people face — be it caused by wind on a tennis
court, snow on a football field or darkness on a country highway —
the more they make decisions based on their subconscious memory and
the less they depend on what they see.
Among researchers, the combining of new information with
conventional wisdom is known as Bayesian analysis, and it has become
increasingly popular in recent years. Once controversial, because it
muddies supposedly pure scientific data with subjective opinion
about which prior research is relevant to a particular study, it has
gained adherents as the explosion of computing power has allowed the
method's complex formulas to be performed on a basic laptop
computer.
With the encouragement of the Food and Drug Administration,
medical-device makers use the method to test new devices that are
only slightly different from their predecessors. Computer companies
use Bayesian methods to build spam filters for e-mail, said Dr.
Michael Lynch, the chief executive of Autonomy, a British software
company, and governments use it to try to prevent terrorism,
combining data from security cameras and X-ray machines with
criminal profiles.
"In academia, the Bayesian revolution is on the verge of becoming
the majority viewpoint, which would have been unthinkable 10 years
ago," said Bradley P. Carlin, a professor of public health at the
University of Minnesota and a Bayesian specialist.
Stephen M. Stigler, a professor of statistics at the University
of Chicago who considers himself to be roughly in the middle of the
spectrum in the Bayesian debate, added: "It's not a controversial
subject. Twenty years ago, it was."
In everyday life, of course, people have been using the ideas
underlying Bayesian analysis since well before it became the vogue
in science labs, or even before Thomas Bayes, an 18th-century
British minister and mathematician, formalized the method in a paper
that was published two years after he died. When crossing a street,
people rely on both what they see and what they remember about the
speed of cars on similar roads. When deciding whether to take a sick
child to a doctor, parents consider the current symptoms as well as
the child's history and their general knowledge of illness.
"The human brain knows about Bayes's rule," said Konrad P.
Körding, a postdoctoral researcher at the Institute of Neurology in
London, who conducted the study published in Nature along with
Daniel M. Wolpert, a professor at the institute.
The new research stands out because it offers a detailed window
into how the Bayesian thought process works, showing the point when
uncertainty becomes great enough to give past experience an edge
over current observation.
Each participant in the experiment sat down and placed a hand on
a tabletop. A projection of a computer screen blocked their view of
the hand. The goal was to guide a cursor, which followed the
movement of the hand, from one side of the screen to a target on the
other side.
Adding to the uncertainty, the cursor usually appeared slightly
to the right of the hand, and the participants caught at most a
quick glimpse of it when it was halfway across the screen.
Sometimes, the cursor appeared as a discrete point; other times, it
was an ill-defined cloud.
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