What is the core function of a healthy adaptive brain? This researcher says its function is not merely to sort the input of our senses, but to create predictive models based on the cumulative weight of that input. This hypothesis strikes me as rather obvious and thus not entirely insightful. Though that’s plainly not an opinion shared by many, who believe an orderly brain is one that disregards its own predicted models in favor of those espoused by the Huffington Post.
Here’s how the article described the function of this seemingly tertiary organ.
The main purpose of the brain, as we understand it today, is it is basically a prediction machine that is optimising its own predictions of the environment it is navigating through. So, vision starts with an expectation of what is around the corner. Once you turn around the corner, you are then negotiating potential inputs to your predictions – and then responding differently to surprise and to fulfilment of expectations.
‘So that’s what’s called the predictive processing framework, and it’s a proposed unifying theory of the brain. It’s basically creating an internal model of what’s going to happen next.’
So a functioning brain is one that forms accurate models about what it will actually see next. Such as a bushman on the Serengeti whose brain predicts he will soon see the inside of a lion’s intestinal tract upon realizing one is in full sprint for his neck. This model is one likely to incentivize enthusiastic flight, and thus result in a bushman who lives to model another day. In contrast, inaccurate models about lion behavior tend to have a suppressive effect on bushman longevity. More interesting is the fact that this effect is noted even where inaccurate models are socially mandated.
But how does this apply in a sense relevant to us?
You have forward models, so while you’re cycling, you predict the trajectory of the cars, of your own movement on the entire world, in real time. You update your predictions (of) the future model that you create in order to cycle through the city without being run over.
‘These models are very good because you have this experience, and only now and then you need to update these models, or you update them (in real time) because you’re turning a corner. So you’re updating with your memory, your predictions, and a slight slip of the internal model comes about because you’re surprised: “Oh it’s not this street.” So, while you’re cycling, you’re negotiating a future model with another future model because you’re updating these creations of your predictions.’
So for instance if you suddenly found yourself cycling through East St. Louis at night, your model would need to be updated to predict the cost of your mortician. And while your model is ingesting that input, you’re negotiating a future model that asks “What if everywhere was East St. Louis?” This inducing a motivation that everywhere not be East St. Louis, thus prompting proselytizing such that others will share your conviction. Fortunately, your predictive brain alerts you to the fact that expressing this preference for a non ESL world is likely to result in social shaming, harassment, and unemployment. So your brain negotiates this hurdle by accurately predicting that parroting false platitudes about diversity will enable sufficient income to subsidize a life far away from it. The most common camouflage for these revealed preferences is called Good Schools.
And that is the true marvel of man’s predictive brain. He can anticipate what subterfuge and signaling are necessary to pretend that his mind has accurately modeled nothing whatsoever. Thus, like a canny opossum, the modern brain protects itself by playing dead.
It’s quite an interesting adaptation…until everywhere is East St. Louis.