Yeah but if something is in the general circulation (bloodstream), then it’s going everywhere in the body. I don’t think there’s any way to specifically direct it.
The point wouldn’t be to direct it, but to have different mixtures of chemicals (and timings) to mean different things to different organs.
Loose analogy: Suppose that the intended body behaviors (“kidneys do X, heart does Y, brain does Z” for all combinations of X, Y, Z) are latent features, basic chemical substances and timings are components of the input vector, and there are dramatically more intended behaviors than input-vector components. Can we define the behavior-controlling function of organs (distributed across organs) such that, for any intended body behavior, there’s a signal that sets the body into approximately this state?
It seems that yes. The number of almost-orthogonal vectors in d dimensions scales exponentially with d, so we simply need to make the behavior-controlling function sensitive to these almost-orthogonal directions, rather than the chemical-basis vectors. The mappings from the input vector to the output behaviors, for each organ, would then be some complicated mixtures, not a simple “chemical A sets all organs into behavior X”.
This analogy seems flawed in many ways, but I think something directionally-like-this might be happening?
Just because the number of almost-orthogonal vectors in d dimensions scales exponentially with d, doesn’t mean one can choose all those signals independently. We can still only choose d real-valued signals at a time (assuming away the sort of tricks by which one encodes two real numbers in a single real number, which seems unlikely to happen naturally in the body). So “more intended behaviors than input-vector components” just isn’t an option, unless you’re exploiting some kind of low-information-density in the desired behaviors (like e.g. very “sparse activation” of the desired behaviors, or discreteness of the desired behaviors to a limited extent).
The above toy model assumed that we’re picking one signal at a time, and that each such “signal” specifies the intended behavior for all organs simultaneously...
… But you’re right that the underlying assumption there was that the set of possible desired behaviors is discrete (i. e., that X in “kidneys do X” is a discrete variable, not a vector of reals). That might’ve indeed assumed me straight out of the space of reasonable toy models for biological signals, oops.
The point wouldn’t be to direct it, but to have different mixtures of chemicals (and timings) to mean different things to different organs.
Loose analogy: Suppose that the intended body behaviors (“kidneys do X, heart does Y, brain does Z” for all combinations of X, Y, Z) are latent features, basic chemical substances and timings are components of the input vector, and there are dramatically more intended behaviors than input-vector components. Can we define the behavior-controlling function of organs (distributed across organs) such that, for any intended body behavior, there’s a signal that sets the body into approximately this state?
It seems that yes. The number of almost-orthogonal vectors in d dimensions scales exponentially with d, so we simply need to make the behavior-controlling function sensitive to these almost-orthogonal directions, rather than the chemical-basis vectors. The mappings from the input vector to the output behaviors, for each organ, would then be some complicated mixtures, not a simple “chemical A sets all organs into behavior X”.
This analogy seems flawed in many ways, but I think something directionally-like-this might be happening?
Just because the number of almost-orthogonal vectors in d dimensions scales exponentially with d, doesn’t mean one can choose all those signals independently. We can still only choose d real-valued signals at a time (assuming away the sort of tricks by which one encodes two real numbers in a single real number, which seems unlikely to happen naturally in the body). So “more intended behaviors than input-vector components” just isn’t an option, unless you’re exploiting some kind of low-information-density in the desired behaviors (like e.g. very “sparse activation” of the desired behaviors, or discreteness of the desired behaviors to a limited extent).
The above toy model assumed that we’re picking one signal at a time, and that each such “signal” specifies the intended behavior for all organs simultaneously...
… But you’re right that the underlying assumption there was that the set of possible desired behaviors is discrete (i. e., that X in “kidneys do X” is a discrete variable, not a vector of reals). That might’ve indeed assumed me straight out of the space of reasonable toy models for biological signals, oops.