If you want to get into that level of technical granularity then there are major things that need to change before applying the PP methodology in the paper to real biological neurons. Two of the big ones are brainwave oscillations and existing in the flow of time.
Mostly what I find interesting is the theory that the bulk of animal brain processing goes into creating a real-time internal simulation of the world, that this is mathematically plausible via forward-propagating signals, and that error and entropy are fused together.
When I say “free energy minimization” I mean the idea that error and surprise are fused together (possibly with an entropy minimizer thrown in).
If you want to get into that level of technical granularity then there are major things that need to change before applying the PP methodology in the paper to real biological neurons. Two of the big ones are brainwave oscillations and existing in the flow of time.
Mostly what I find interesting is the theory that the bulk of animal brain processing goes into creating a real-time internal simulation of the world, that this is mathematically plausible via forward-propagating signals, and that error and entropy are fused together.
When I say “free energy minimization” I mean the idea that error and surprise are fused together (possibly with an entropy minimizer thrown in).