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Predictive Coding has been Unified with Backpropagation

You guys will probably find this Slate Star Codex post interesting:

Scott summarizes the Predictive Processing theory, explains it in a very accessible way (no math required), and uses it to explain a whole bunch of mental phenomena (attention, imagination, motor behavior, autism, schizophrenia, etc.)

Can someone ELI5/TLDR this paper for me, explain in a way more accessible to a non-technical person?

- How does backprop work if the information can't flow backwards?
- In Scotts post, he says that when lower-level sense data contradicts high-level predictions, high-level layers can override lower-level predictions without you noticing it. But if low-level sensed data has high confidence/precision - the higher levels notice it and you experience "surprise". Which one of those is equivalent to the backdrop error? Is it low-level predictions being overridden, or high-level layers noticing the surprise, or something else, like changing the connections between neurons to train the network and learn from the error somehow?