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Comment by kurtosis | Hacker News Reader

Here's a contrary view: There is a very famous tradition in biology of deriving the form and function of organisms by a mathematical optimization (see D'arcy Thompson). It shouldn't be surprising that the nervous system would converge on Bayesian stats. The dutch book argument shows that any other method of updating beliefs about the world will lose money in a gambling strategy. If "gambling" is replaced by "foraging" or "mating" then Bayes is the optimal way to play. (whether we're playing for the interests of the organism or its genes)

But saying that the brain is Bayesian is not that profound. It's like saying that the brain is ruled by electricity. The key is what priors are being modeled, how is inference implemented with neurons, and what constraints, or "hyperparameters" are built into these priors.

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"But saying that the brain is Bayesian is not that profound."

And, furthermore, it's not really a new idea.

Judea Pearls work in the late 80's suggested something along these lines. I have also seen suggested that some of Marvin Minskys groundlaying work back in the 60's pointed in this direction, but YMMV on that one.

You obviously know more about the science and math here than I do. So I'm offering these thoughts deferentially. I'm coming at this as a jack of all trades type who did a ton of philosophy of mind and cognitive science stuff in college but somewhat deficient with the hard science.

"What priors are being modeled"

I think this is the most interesting thing. There is so much information about how memories are recreated as you remember them, and about memory being unreliable. Even if you had an answer to the question "what priors are being modeled?", it would need to be indexed to a time. Indexing your question to times is where it gets interesting.

This would create a question that would be a lot harder and necessary to understand to get at the truth of this. Something like "How can the constantly changing sea of fragmented memories we base our idea of self on serve as reliable priors at all." Or, less poetically and more formally:

Given a person, P, at 2 times, T1 and T2, and two sets of priors, M1 and M2, such that M1 and M2 belong to P, at T1 and T2, respectively, and between T1 and T2, P obtained exactly one datum, D, what is the relationship between M1 at T1 in P, and (M2-D) at T2 in P?

And, generally, what calculus explains the relationship between Mx at Tx in P, and (My-Dn) at Ty in P, where Dn is the sum of the data P acquired between Tx and Ty?

I don't think M1 is equivalent to M2-D in the first, and I don't think that My-Dn is equivalent to Mx in the second. I think all the evidence about memories being inconsistent, recreated, count towards my intuition. I also think the way things like a sudden smell can cause priming of memories, or an emotional state can alter memory recall suggest this.

"how is inference implemented with neurons"

This seems like the most trivial, least profound, and most uninteresting part. We know that the brain does these inferences, and we know that even very simple systems based on cellular automation can be turing complete and make inferences. The particular details will not shed light on the fundamental problems understanding mind.

"what constraints, or "hyperparameters" are built into these priors."

It sounds to me like their idea that hallucinations and delusions as breakdowns of Bayesian statistics functionality would bear fruit that could answer this question, although I don't have an answer.

I also wonder, wasn't "the brain is ruled by electricity" a profound insight for it's time?

I've always thought of Noam Chomsky's "language acquisition device" as a kind of prior on the space of languages that's hardwired into the brain. The process of learning a language consists of fitting the parameters of this model to the sense data that each child is immersed in. Of course Bayes' rule provides one way to update our guess about the parameters of this model given the current data but who knows if that's what's really going on. I think the evidence is pretty strong that this flexibility in the space of priors over language only lasts a for small precious window until we become adults, and then we're all stuck with lame accents. So it does indeed have some time dependence.

When I was talking about the implementation of inference I was referring to the people doing experiments trying to figure out the "neural code" - Questions like: how much information is conveyed by a single spike? Is there any meaning in the rate of the spikes? How much information is there in a coincidence when two or more neurons fire simultaneously? What rules govern the plasticity of the activation or inhibition relationships among neurons? Does any of this have anything to do with probability? A great book on this is "Spikes" by de Ruyter and Bialek et. al.

I didn't mean to sound dismissive about the electricity thing - I think hodgkin and huxley were both given medicine nobels for their work on the nerves. I guess the electricity thing really goes back the 1700's when galvani made a dead frog move with electric current.

"I think the evidence is pretty strong that this flexibility in the space of priors over language only lasts a for small precious window until we become adults, and then we're all stuck with lame accents."

I think this is true for most people, not everyone.

If this is true for most people, we can locate these differences by comparing autistic people who quickly acquire languages as adults with normal people. It's interesting that autistic people skilled with language often don't have noticeable accents in that language, even with a language they learn in adulthood.

This flexibility in the space of languages involves a honing of perception. As you learn your first language, you become better at perceiving the sounds of that language, but your ability to perceive the sounds of another language go down. For example, a person who speaks exclusively english speaker cannot discern between sounds that would have different meanings that a chinese speaker would easily hear.

(Deferentially), I think you are wrong about where the hardwiring occurs. I think the hardwiring that limits most peoples ability to learn language arises is perception, not the space of priors. I believe if you could change the hardwiring that occurs in making sensory discriminations relevant to the language, the "space of priors" would still show the ability to learn language. It's true that there is a precious window for most people to learn languages, but that's because the perceptual paths get hardwired, not the memory and processing that make up what we seem to be calling the "space of priors"

But, that's not the scale of time dependance I was thinking. Even if the scale of time dependence was 5 seconds, and the new data was just seeing it was raining out, the way your brain understands the concept of rain involves accessing memories it destroys and recreates as part of recognizing "rain", as well as the particulars of your emotional state and what's going into your sense of smell, so much that the set of priors 5 seconds before would be different then the ones now, even if you took out the information about it raining.

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