Predictive Processing

Predictive processing, also known as predictive coding, suggests that the content of our experiences and perceptions of the world are primarily based on predictive models our brains have constructed through our previous experiences. Our brains, locked inside the confines of a skull, have the unenviable task of trying to determine the causes of our sensory signals. By using predictive models to determine our perception, our brains are able to go beyond the data of our senses to form, what feel like, concrete experiences of phenomena in the world. In a sense, our brains are constantly trying to solve what philosophers call an inverse inference problem, where we don’t have direct access to the causes of our sensory signals. Our sensory signals are the effects of phenomena out there in the world that do not necessarily reflect the nature of the causes that produced them. And with this limited data, our brains fill in the missing gaps by producing models that predict their causes.

But in predictive processing, our senses still play an important role in our overall perception, as our predictions, so-called “priors,” and generative models of the world are constantly cross referenced with what our senses are telling us. This cross referencing inevitably leads to prediction errors, as our models don’t always neatly match up with what our senses tell us. These errors then play a vital role in helping the brain update it’s predictions, giving it more data to choose from for the next scenario in which it finds itself. source

Fun little example about how the world we see is only a subset of what we could have experienced: