Oh, hmm. In my head, the short-term predictors in the cerebellum are for latency-reduction and discussed in the last post, and meanwhile the short-term predictors in the telencephalon (amygdala & mPFC) are for flinching and discussed here. I think the cerebellum short-term predictors and the telencephalon short-term predictors are built differently for different purposes, and once we zoom in beyond the idea of “short-term prediction” and start talking about parameter settings etc., I really don’t lump them together in my mind, they’re apples and oranges. In the conversation thus far, I thought you were talking about the telencephalon (amygdala & mPFC) ones. If we’re talking about instability from the cerebellum instead, we can continue the Post #4 thread.
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I think I said some things about low-pass filters up-thread and then retracted it later on, and maybe you missed that. At least for some of the amygdala things like flinching, I agree with you that low-pass filters seem unlikely to be part of the circuit (well, depending on where the frequency cutoff is, I suppose). Sorry, my bad.
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A common trope is that the hippocampus does one-shot learning in a way that vaguely resembles a lookup table with auto-associative recall, whereas other parts of the cortex learn more generalizable patterns more slowly, including via memory recall (i.e., gradual transfer of information from hippocampus to cortex). I’m not immediately sure whether the amygdala does one-shot learning. I do recall a claim that part of PFC can do one-shot learning, but I forget which part; it might have been a different part than we’re talking about. (And I’m not sure if the claim is true anyway.) Also, as I said before, with continuous-time systems, “one shot learning” is hard to pin down; if David Burns spends 3 seconds on the ladder feeling relaxed, before climbing down, that’s kinda one-shot in an intuitive sense, but it still allows the timescale of synapse changes to be much slower than the timescale of the circuit. Another consideration is that (I think) a synapse can get flagged quickly as “To do: make this synapse stronger / weaker / active / inactive / whatever”, and then it takes 20 minutes or whatever for the new proteins to actually be synthesized etc. so that the change really happens. So that’s “one-shot learning” in a sense, but doesn’t necessarily have the same short-term instabilities, I’d think.
Oh, hmm. In my head, the short-term predictors in the cerebellum are for latency-reduction and discussed in the last post, and meanwhile the short-term predictors in the telencephalon (amygdala & mPFC) are for flinching and discussed here. I think the cerebellum short-term predictors and the telencephalon short-term predictors are built differently for different purposes, and once we zoom in beyond the idea of “short-term prediction” and start talking about parameter settings etc., I really don’t lump them together in my mind, they’re apples and oranges. In the conversation thus far, I thought you were talking about the telencephalon (amygdala & mPFC) ones. If we’re talking about instability from the cerebellum instead, we can continue the Post #4 thread.
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I think I said some things about low-pass filters up-thread and then retracted it later on, and maybe you missed that. At least for some of the amygdala things like flinching, I agree with you that low-pass filters seem unlikely to be part of the circuit (well, depending on where the frequency cutoff is, I suppose). Sorry, my bad.
~
A common trope is that the hippocampus does one-shot learning in a way that vaguely resembles a lookup table with auto-associative recall, whereas other parts of the cortex learn more generalizable patterns more slowly, including via memory recall (i.e., gradual transfer of information from hippocampus to cortex). I’m not immediately sure whether the amygdala does one-shot learning. I do recall a claim that part of PFC can do one-shot learning, but I forget which part; it might have been a different part than we’re talking about. (And I’m not sure if the claim is true anyway.) Also, as I said before, with continuous-time systems, “one shot learning” is hard to pin down; if David Burns spends 3 seconds on the ladder feeling relaxed, before climbing down, that’s kinda one-shot in an intuitive sense, but it still allows the timescale of synapse changes to be much slower than the timescale of the circuit. Another consideration is that (I think) a synapse can get flagged quickly as “To do: make this synapse stronger / weaker / active / inactive / whatever”, and then it takes 20 minutes or whatever for the new proteins to actually be synthesized etc. so that the change really happens. So that’s “one-shot learning” in a sense, but doesn’t necessarily have the same short-term instabilities, I’d think.