Hello,

I am not sure of the specific details that may (or may not) be required to ask this question meaningfully, and I apologise (though nobody is actually really offended) potentially for any lack of important details needed to answer the question meaningfully. But given my current circumstances (that I have limited access to the internet at the moment), I ask kindly that posters don't get me too bogged down on answering small details, and instead try and answer the question as meaningfully as possible given any possible limitations. Many times it may be preferable to pick apart the small details for accuracy and added meaning, but still there is always some intuition involved.

The question is about the number of equations in neuroscience research.
What I would like to know, is, as I put it, how many 'excess' equations would be involved in neuroscience research, when, combining potentially chips and computerised devices with the (biological) brain, and trying to extract a specific function from the brain which may be beyond or slightly beyond normal reach.
An example is: If researchers want certain objects to be invisible no matter what. Now, in this case, for this hypothetical example; an example chosen to illustrate that a specific function could be extracted, I am not talking about making something invisible according to the computer, or the chip, erasing the image from the environment and then transferring the changed image to the brain; I am talking about changing the actual mind's perception so that it cannot see the object, without a changed image being transferred (which would be easier). This satisfies a very specific example of manipulating the function of the mind/brain.

Now, I am aware that since there are, say, 86 billion neurons in the human brain, there must be at least millions upon millions of unknown variables for neuroscience in general. However, a large proportion of these unknown variables wouldn't become equations to be used in the calculation of this one specific function.

What I see, is that in neuroscience research, each function would require continual refinement of equations, or a series of equations that would be computed into the system. I wonder, and I ask, concerning the current state of our refined methods for neuroscience research, how many 'excess' equations would be involved, specifically as the calculations are refined and refined (further refined). By 'excess' equations, I mean that: say if you had 1000 ways of approaching the research to begin with, combining different potentials of the brain in different ways from known angles (known practical methods and equations), and then it is found that, say, many of these equations need refining further. Perhaps for each starting equation, you would then need to choose from different variables that may potentially work, so, although this may be grossly inaccurate, you have 1000, then 3 variables for each at step 1, then another 3, and another 3. You would have 1000 X 3 X 3 X 3 X 3 X 3 X 3 and so on. A bit like calculating the probabilities for unique arrangements in a deck of cards. I don't know how long it would go on for a specific function in neuroscience, but what I wonder is, how many 'excess' equations there would be. Because, 1 out of every 3 variables may be useful for the next independent equation, meaning that there would be 2 'excess' equations.

According to Khan academy website, and this is a topic about equations for 'circuits,' "As we learned when solving simultaneous equations in algebra, the number of independent equations you need to solve a system is equal to the number of unknown variables."

The next part of my question is: do you think each variable and equation would be tested extremely slowly, maybe with respect to chemical alterations to the brain and many kinks in the chips and computerised technology? I am aware that AI itself requires millions of equations for certain successful functions.

The last question is: If say, many teams of researchers found the solution to the hypothetical problem (of making an object invisible), how far may this reduce the number of 'excess' equations for another problem, such as, refining the next problem which would be, I don't know, maybe, placing your hand on different objects in the dark and your mind perceiving a hand print on certain objects, to the exact shape of your hand and the angle of the hand at the time?

I hope this is a well reasoned question, but I am aware that it may be highly inaccurate and potentially useless, because my background is not mathematics.
Thank you for your time.

Dude, neuroscience doesn't even know what consciousness is, and you're asking how many equations it would take to render invisible the experience of one object.

My gast is utterly flabbered.

Well I think you may be right. I mean, even if consciousness is somewhat more emergent and complicated with undefined phenomenological substance, perhaps certain functions of the brain are more easily defined through a unique process of refinement mixed with trials (trials and error), with a calculable success rate of x number of equations.
I am thinking that there must be a sensible estimate, perhaps by mathematicians, as something less alien than the phenomenological what if? The ghost from the Ether, and that mathematically there is something that leans towards an answer.
Sorry for sounding pretentious, and I am indeed in agreement with you, but the question may allow some answer.

jomsur wrote:Well I think you may be right. I mean, even if consciousness is somewhat more emergent and complicated with undefined phenomenological substance, perhaps certain functions of the brain are more easily defined through a unique process of refinement mixed with trials (trials and error), with a calculable success rate of x number of equations.
I am thinking that there must be a sensible estimate, perhaps by mathematicians, as something less alien than the phenomenological what if? The ghost from the Ether, and that mathematically there is something that leans towards an answer.
Sorry for sounding pretentious, and I am indeed in agreement with you, but the question may allow some answer.

You're new (welcome by the way) so won't know that I'm actually an idealist, though this has nothing to do with my previous response. It just seems ludicrous to ask the question(s) you have asked when neuroscience is still in diapers/nappies relative to the subject/issues at-hand. I mean, if we don't understand how consciousness/experience comes about, what means do we have of estimating the number of equations it would take to render invisible the experience of one object?

In all seriousness, if anyone here comes up with a number in response to your question, then rest assured that they've completely plucked it from their southerly hole.

jamest wrote:Dude, neuroscience doesn't even know what consciousness is, and you're asking how many equations it would take to render invisible the experience of one object.

My gast is utterly flabbered.

If you had enough equations, they'd tell you that really, your flabber is utterly ghasted. If I'm wrong, I would feel somewhat less than or equalled to zero.

Perhaps instead of extracting function, blocking image from becoming lets say conscious would do the trick of making an object invisible. Kind of like hypnoses. About equations, I do not understand the subject nor OP so I have to pass.

crank wrote:

jamest wrote:Dude, neuroscience doesn't even know what consciousness is, and you're asking how many equations it would take to render invisible the experience of one object.

My gast is utterly flabbered.

If you had enough equations, they'd tell you that really, your flabber is utterly ghasted. If I'm wrong, I would feel somewhat less than or equalled to zero.

I'm not going to bother arguing against the arguable assumption that there are X amount of equations to explain any phenomenon. Instead, I'll stick to saying that it is ludicrous to estimate the number of equations required to explain a phenomenon we do not even understand.

Southerly hole stuff.

I did find a website, for reference, if useful.
The title is Mathematical modelling in neuroscience: neuronal activity and it's modulation by astrocytes.