bottom-up attention (ie attention due to interesting stimulus) can be more or less captured by surprise
Hmm. That’s not something I would have said.
I guess I think of two ways that sensory inputs can impact top-level processing.
First, I think sensory inputs impact top-level processing when top-level processing tries to make a prediction that is (directly or indirectly) falsified by the sensory input, and that prediction gets rejected, and top-level processing is forced to think a different thought instead.
If top-level processing is “paying close attention to some aspect X of sensory input”, then that involves “making very specific predictions about aspect X of sensory input”, and therefore the predictions are going to keep getting falsified unless they’re almost exactly tracking the moment-to-moment status of X.
On the opposite extreme, if top-level processing is “totally zoning out”, then that involves “not making any predictions whatsoever about sensory input”, and therefore no matter what the sensory input is, top-level processing can carry on doing what it’s doing.
In between those two extremes, we get the situation where top-level processing is making a pretty generic high-level prediction about sensory input, like “there’s confetti on the stage”. If the confetti suddenly disappeared altogether, it would falsify the top-level hypothesis, triggering a search for a new model, and being “noticed”. But if the detailed configuration of the confetti changes—and it certainly will—it’s still compatible with the top-level prediction “there’s confetti on the stage” being true, and so top-level processing can carry on doing what it’s doing without interruption.
So just to be explicit, I think you can have a lot of low-level surprise without it impacting top-level processing. In the confetti example, down in low-level V1, the cortical columns are constantly being surprised by the detailed way that each piece of confetti jiggles around as it falls, I think, but we don’t notice if we’re not paying top-down attention.
The second way that I think sensory inputs can impact top-level processing is by a very different route, something like sensory input → amygdala → hypothalamus → top-level processing. (I’m not sure of all the details and I’m leaving some things out; more HERE.) I think this route is kinda an autonomous subsystem, in the sense that top-down processing can’t just tell it what to do, and it’s not trained on the same reward signal as top-level processing is, and the information can flow in a way that totally bypasses top-level processing. The amygdala is trained (by supervised learning) to activate when detecting things that have immediately preceded feelings of excitement / scared / etc. previously in life, and the hypothalamus is running some hardcoded innate algorithm, I think. (Again, more HERE.) When this route activates, there’s a chain of events that results in the forcing of top-level processing to start paying attention to the corresponding sensory input (i.e. start issuing very specific predictions about the corresponding sensory input).
I guess it’s possible that there are other mechanisms besides these two, but I can’t immediately think of anything that these two mechanisms (or something like them) can’t explain.
What if we don’t like global workspace theory?
I dunno, I for one like global workspace theory. I called it “top-level processing” in this comment to be inclusive to other possibilities :)
Hmm. That’s not something I would have said.
I guess I think of two ways that sensory inputs can impact top-level processing.
First, I think sensory inputs impact top-level processing when top-level processing tries to make a prediction that is (directly or indirectly) falsified by the sensory input, and that prediction gets rejected, and top-level processing is forced to think a different thought instead.
If top-level processing is “paying close attention to some aspect X of sensory input”, then that involves “making very specific predictions about aspect X of sensory input”, and therefore the predictions are going to keep getting falsified unless they’re almost exactly tracking the moment-to-moment status of X.
On the opposite extreme, if top-level processing is “totally zoning out”, then that involves “not making any predictions whatsoever about sensory input”, and therefore no matter what the sensory input is, top-level processing can carry on doing what it’s doing.
In between those two extremes, we get the situation where top-level processing is making a pretty generic high-level prediction about sensory input, like “there’s confetti on the stage”. If the confetti suddenly disappeared altogether, it would falsify the top-level hypothesis, triggering a search for a new model, and being “noticed”. But if the detailed configuration of the confetti changes—and it certainly will—it’s still compatible with the top-level prediction “there’s confetti on the stage” being true, and so top-level processing can carry on doing what it’s doing without interruption.
So just to be explicit, I think you can have a lot of low-level surprise without it impacting top-level processing. In the confetti example, down in low-level V1, the cortical columns are constantly being surprised by the detailed way that each piece of confetti jiggles around as it falls, I think, but we don’t notice if we’re not paying top-down attention.
The second way that I think sensory inputs can impact top-level processing is by a very different route, something like sensory input → amygdala → hypothalamus → top-level processing. (I’m not sure of all the details and I’m leaving some things out; more HERE.) I think this route is kinda an autonomous subsystem, in the sense that top-down processing can’t just tell it what to do, and it’s not trained on the same reward signal as top-level processing is, and the information can flow in a way that totally bypasses top-level processing. The amygdala is trained (by supervised learning) to activate when detecting things that have immediately preceded feelings of excitement / scared / etc. previously in life, and the hypothalamus is running some hardcoded innate algorithm, I think. (Again, more HERE.) When this route activates, there’s a chain of events that results in the forcing of top-level processing to start paying attention to the corresponding sensory input (i.e. start issuing very specific predictions about the corresponding sensory input).
I guess it’s possible that there are other mechanisms besides these two, but I can’t immediately think of anything that these two mechanisms (or something like them) can’t explain.
I dunno, I for one like global workspace theory. I called it “top-level processing” in this comment to be inclusive to other possibilities :)