I was interested in a post on Mind Hacks about looking at the brain as a Bayesian probability machine. The aspect that got me was the modeling and the importance of prediction.
I was reminded of ideas that I wrote down in the early 80s.
We can view ourselves as having a nervous system with many functions, one of the major ones being the function of mind. The mind function consists of building, maintaining and refining a model of reality; using the model to predict, plan, decide, initiate and control responses to the world; storing an edited form of the model as a memory of experience for comparison and learning. During introspection we only have access to consciousness, the memory being formed, and not the model itself.
The Mind Hacks post reviews an article from the New Scientist by Gregory T. Huang about the work of Friston and Hinton at
(Bayesian statistics) asks the question ‘what is the probability of the belief being true, given the data so far?’. The NewSci article looks at the work neuroscientist Karl Friston, who increasingly believes that from the level of neurons to the level of circuits, the brain operates as if it uses Bayesian statistics. The essential idea is that the brain makes models upon which it bases predictions, and these models and predictions are updated in a Bayesian like-way as new information becomes available.
Picture the brains circuits working to minimize the prediction error of a reality model and doing this by using feedback loops. I envisaged a different type of feedback (something on that in future posts) but the principle is very similar.
Friston created a computer simulation of the cortex with layers of neurons passing signals back and forth. Signals going from higher to lower levels represent the brains internal predictions, while signals going the other way represent sensory input. As new information comes in, the higher neurons adjust their predictions according to Bayesian theory. This may seem awfully abstract, but theres a concrete reason for doing it: it tells Friston what patterns of activity to look for in real brains.
It is great to look forward to this and similar ideas being experimentally tested!!