We don’t need to explain why/whether predicting “endogenous” activations is good, if we accept hypothesis that that’s how brain is wired—it runs prediction learning by default. It makes sense, because the affected cluster of neurons doesn’t know if this activation is exo or endo. Prediction learning for endo activations is conceptually the learning of shortcuts: if screw model activation predictably leads through a chain of intermediate steps to “being worried” model, then a good predictor would learn to activate the latter model right away after seeing screw.
We don’t need to explain why/whether predicting “endogenous” activations is good, if we accept hypothesis that that’s how brain is wired—it runs prediction learning by default. It makes sense, because the affected cluster of neurons doesn’t know if this activation is exo or endo.
Prediction learning for endo activations is conceptually the learning of shortcuts: if screw model activation predictably leads through a chain of intermediate steps to “being worried” model, then a good predictor would learn to activate the latter model right away after seeing screw.
That makes sense, thanks!