Most decisions in our lives are done in the presence of uncertainty. When I play an approaching tennis ball I will not exactly know where it will land on the court. When I want to know if someone is my friend I will have to estimate this. If I am a doctor and I want to know the disease that a patient has I have to do an informed estimate. And equally if I move my arm I will have to estimate where exactly in space it is.
A branch of mathematics, Bayesian statistics, allows optimally estimating variables in the presence of uncertainty, even if one has prior knowledge of some properties of the system or several sensors. This theory can be proven to be mathematically optimal and many modern artificial intelligence applications such as speech recognition use these methods.
In my studies I show that people when they move their hands use exactly the
same mathematical tricks. I can show that people intuitively use Bayes-rule.
Körding, KP. and Wolpert, D. (2004) Bayesian Integration in Sensorimotor Learning, Nature 427:244-247 [pdf]
Bayes rule goes back to
Reverent Thomas Bayes (1701-1761) whos essays were published
after his death by the Royal Society. It however only made any impact after it
got independently discovered by the French mathematician Laplace.
We want to find out what cats are interested in. To find out what they
look at we mount a miniture CCD to their heads.
We then have them
explore the local park and record videos of the world from a cat's perspective.
avi divx compression (high quality 4M)
realplayer (low quality, 3M)
We then analyze what cats see using these cat-cam videos.
It could be that the neurons in the brain that deal with hearing and seeing are in fact identical --- except that they learn from different inputs.
CounterThis research is carried out at neuroinformatics Zürich which is part of University and ETH Zürich.