I first (roundaboutly) mentioned Karl Friston’s “unified theory of the brain” back in January. Now it is half a year later, and I still cannot say I am any further in gleaning any great understanding from his paper. Thankfully, New Scientist sums it up for the layman in this week’s issue.

Although we know tons and tons of details about the brain, we are almost completely lacking in ideas of how to connect all those details. Similar situations existed in physics and biology before the likes of Einstein and Darwin (respectively), and Karl Friston is attempting to follow in their footsteps by describing a simple theory that explains a wide range of neuroscience phenomenon.

Friston’s ideas build on an existing theory known as the “Bayesian brain”, which conceptualises the brain as a probability machine that constantly makes predictions about the world and then updates them based on what it senses. … Instead of estimating the distance to an object as a number, for instance, the brain would treat it as a range of possible values, some more likely than others.

Importantly, these predictions are ever evolving. Any new information the brain receives influences the predictions, constantly minimizing error whenever possible. However, describing the brain as a “probability machine” has involved a number of different approaches, all of which would need to be tied together to create an overarching unified theory.

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