How does the timing work out for dopamine to affect the development of long-term potentiation? I just recently learned (indirectly from this source) that long-term potentiation/depression only takes place when you have large/small amounts of dopamine present at the relevant synapse. However, my understanding is that early in the process of learning behavior, dopamine isn't released until after a reward is received. If I'm a monkey who has to look one way or the other to get some juice, by the time I drink the juice and get the resulting dopamine, the neurons I used to move my eye are presumably not firing any more, right? So then how does this work? Is it that:


There's a slow bootstrapping process. Something like: first the
monkey has to learn that the taste of juice leads to the reward of
sugar. Then the monkey has to learn that the sight of juice
correlates to the taste, and extend the chain one step further,
etc., etc., such that by the time you actually have the monkey in
the lab there's a very small inferential step needed to plug into a
larger reward chain.
The neurons don't actually stop firing. There is some sort of
system in play that keeps the neurons firing afterwards, waiting for
fluctuations in dopamine level to tell it whether or not it should
increase or decrease long term potentiation.
Something I haven't thought of?
The ability of dopamine to work on different time scales is discussed by Schultz. More generally, the basic idea of prediction error reinforcement based learning and DA is that the prediction error signal "propagates back in time". There is some doubt for how temporally precise this DA signal actually is, and if DA is fast enough to support RPE TD learning.

Does that answer the question?