I was having a chat over coffee yesterday with some members of the Mathematics Department here at the University of Cape Town, one of whom happens to be an expert at Bridge, actually representing South Africa in international competitions. That’s a much higher level than I could ever aspire to so I was a bit nervous about mentioning my interest in the game, but in the end I explained that I have in the past used Bridge (and other card games) to describe how Bayesian probability works; see this rather lengthy post for more details. The point is that as cards are played, one’s calculation of the probabilities of where the important cards lie changes in the light of information revealed. It makes much more sense to play Bridge according to a Bayesian interpretation, in which probability represents one’s state of knowledge, rather than what would happen over an ensemble of “random” realisations.

This particular topic – and Bayesian inference in general – is also discussed in my book *From Cosmos to Chaos* (which is, incidentally, now available in paperback). On my arrival in Cape Town I gave a copy of this book to my genial host, George Ellis, and our discussion of Bridge prompted him to say that he thought I had missed a trick in the book by not mentioning the connections between Bayesian probability and neuroscience. I hadn’t written about this because I didn’t know anything about it, so George happily enlightened me by sending a few review articles, such as this:

I can’t post it all, for fear of copyright infringement, but you get the idea. Here’s another one:

And another…

*Nature Reviews Neuroscience 11, 605 (August 2010) | doi:10.1038/nrn2787-c1*

**A neurocentric approach to Bayesian inference ** Christopher D. Fiorillo

**Abstract** A primary function of the brain is to infer the state of the world in order to determine which motor behaviours will best promote adaptive fitness. Bayesian probability theory formally describes how rational inferences ought to be made, and it has been used with great success in recent years to explain a range of perceptual and sensorimotor phenomena.

As a non-expert in neuroscience, I find these very interesting. I’ve long been convinced that from the point of view of formal reasoning, the Bayesian approach to probability is the only way that makes sense, but until reading these I’ve not been aware that there was serious work being done on the possibility that it also describes how the brain works in situations where there is insufficient information to be sure what is the correct approach. Except, of course, for players of Bridge who know it very well.

There’s just a chance that I may have readers out there who know more about this Bayes-Brain connection. If so, please enlighten me further through the comments box!

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