Ok guys, time to weigh in. Of course we aren't trying to claim that
all brain processing reduces to Bayes. Our claim is that we experience the statistical likelihood of our beliefs about our input data (from sense organs or from long-term memory retrieval) as a sense of confidence. If that sense is actually generated by a heuristic computation rather than a neural implementation of Bayes rule is almost irrelevant, because the end product looks identical to Bayes in the ways that matter for use of a confidence variable in computation. We work through the mathematics of how statistical confidence should appear in different projections of decision data here:
http://www.biorxiv.org/content/early/2016/01/01/017400.abstr...
(To appear in http://www.mitpressjournals.org/loi/neco in the next month or so)
By necessity, we had to study decisions that could be replicated in a lab, so no mass-killings of cows. That being said, the brain is constantly faced with a statistical analysis problem - to figure out what's really happening outside of itself. A Bayesian machine is much more useful to assign a classification to sense data and compute its likelihood, than to determine whether your elders are correct when they insist that God is going to cause a plague in 2 years if we don't burn some bovines. Point being, the brain can construct and switch between (occasionally hilarious) decision making strategies depending on context - especially in the murkier, information-impoverished realm of social decision making.
Dealing with sense and memory data is a problem common to all animals, and evolution has had millions of generations to reject suboptimal processors. Processing language and abstract symbols to reinforce tribal social cohesion or implement a political agenda is a different category of decision that is newer in evolutionary terms, and definitely buggier. I hope this helps clear what we are and aren't claiming!
As an aside (since this is the right crowd!) we open-sourced the circuit design files, firmware and APIs for the real-time stimulus generator we used here:
https://github.com/sanworks/PulsePal
with documentation here:
https://sites.google.com/site/pulsepalwiki/home
and here:
http://journal.frontiersin.org/article/10.3389/fneng.2014.00...
This system allowed us to shut off the ongoing audio click streams within 100 microseconds of a decision button press - so we could look backwards in time at the precise evidence stream used to make each choice and confidence report, for clues about what algorithm the brain used to process the streams. The follow-up study (under review) uses this data to evaluate different models of how decision and confidence computations are implemented in real-time.