"the brain is continually generating predictions about sensory signals"

"Let’s return to our imagined brain, quiet and dark inside its skull, trying to figure out what’s out there in the world. We can now recognise this challenge as an ideal opportunity to invoke Bayesian inference. When the brain is making best guesses about the causes of its noisy and ambiguous sensory signals, it is following the principles of the Reverend Thomas Bayes.

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the idea that perception happens through a continual process of prediction error minimisation. According to this idea, the brain is continually generating predictions about sensory signals and comparing these predictions with the sensory signals that arrive at the eyes and the ears – and the nose, and the skin, and so on. The differences between predicted and actual sensory signals give rise to prediction errors. While perceptual predictions flow predominantly in a top-down (inside-to-outside) direction, prediction errors flow in a bottom-up (outside-to-inside) direction. These prediction error signals are used by the brain to update its predictions, ready for the next round of sensory inputs. What we perceive is given by the content of all the top-down predictions together, once sensory prediction errors have been minimised – or ‘explained away’ – as far as possible.

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And it is prediction error minimisation that provides the connection between controlled hallucinations and Bayesian inference. It takes a Bayesian claim about what the brain should do and turns it into a proposal about what it actually does do. By minimising prediction errors everywhere and all the time, it turns out that the brain is actually implementing Bayes’ rule. More precisely, it is approximating Bayes’ rule. It is this connection that licenses the idea that perceptual content is a top-down controlled hallucination, rather than a bottom-up ‘readout’ of sensory data."

Trechos retirados de "Being You: A New Science of Consciousness" de Anil Seth.