Scanning your Brain with 100,000,000,000 wires?

https://www.quantamagazine.org/how-computationally-complex-is-a-single-neuron-20210902/

The most basic analogy between artificial and real neurons involves how they handle incoming information. Both kinds of neurons receive incoming signals and, based on that information, decide whether to send their own signal to other neurons. While artificial neurons rely on a simple calculation to make this decision, decades of research have shown that the process is far more complicated in biological neurons. Computational neuroscientists use an input-output function to model the relationship between the inputs received by a biological neuron’s long treelike branches, called dendrites, and the neuron’s decision to send out a signal.

This function is what the authors of the new work taught an artificial deep neural network to imitate in order to determine its complexity. They started by creating a massive simulation of the input-output function of a type of neuron with distinct trees of dendritic branches at its top and bottom, known as a pyramidal neuron, from a rat’s cortex. Then they fed the simulation into a deep neural network that had up to 256 artificial neurons in each layer. They continued increasing the number of layers until they achieved 99% accuracy at the millisecond level between the input and output of the simulated neuron. The deep neural network successfully predicted the behavior of the neuron’s input-output function with at least five — but no more than eight — artificial layers. In most of the networks, that equated to about 1,000 artificial neurons for just one biological neuron.

Absolute napkin math while I'm sleep deprived at the hospital, but you're looking at something around 86 trillion ML neurons, or about 516 quadrillion parameters. to emulate the human brain. That's.. A lot.

Now, I am a doctor, but I'm certainly no neurosurgeon. That being said, I'm not sure it's particularly conducive to the functioning of a human brain to stuff it full of metallic wires. Leaving aside that Neuralink and co are very superficial and don't penetrate particularly deep into the cortex (do they even have to? Idk, the grey matter is on the outside anyway), it strikes me as electrical engineer's nightmare to even remotely get this wired up and working. The crosstalk. The sheer disruption to homeostasis..

If I had to bet on mind uploading, the first step would be creating an AGI. To make that no longer my headache, of course.

Not an option? Eh, I'd look for significantly more lossy options than to hook up every neuron. I think it would be far easier to feed behavioral and observational data alongside tamer BCIs to train a far more tractable in terms of size model to mimic me, to a degree indistinguishable for a (blinded) outside observer. It certainly beats being the world's Literal Worst MRI Candidate, and probably won't kill you outright. I'm not sure the brain will be remotely close to functional by the time you're done skewering it like that, which makes me assume the data you end up collecting any significant degree into the process will be garbage from dying neuronal tissue.

People have been trying to do this with a tiny worm. That project has not yet been successful.

(epistemic status: same as the post, I don't know neuroscience)

I mis-heard the song version and had a different interpretation of something, but it actually seems like a good idea to consider so here it is :). 

Remove the assumption that the biological version of oneself needs to survive the process. Then, perform very quick scan of all the neurons on a very short timescale without worrying about the brain being destroyed afterwards, only about accurately scanning all the neurons before that happens. Would this data of the whole brain for a very short time (maybe some fraction of a second) be enough to digitally reconstruct the mind and run it?

Maybe it wouldn't be because of neuroscience reasons I wouldn't know, or 'neural spikes over time' not being predictable from the very-short-timespan data (again for some reason I wouldn't know). Also, maybe such a fast scan is not physically possible with current technology (I'd guess that something more efficient than inserting 100 billion wires would be needed).

But if it were possible and feasible, I think it would be worth it, the world's at stake after all. I'd volunteer.

This post happens to be an example of limiting-case analysis, and I think it's one of the most generally usefwl Manual Cognitive Algorithm [LW(p) · GW(p)]s I know of. I'm not sure about its optimal scope, but TAP:

• WHEN: I ask a question like "what happens to a complex system if I tweak this variable?" and I'm confused about how to even think about it (maybe because working-memory is overtaxed)…
• THEN: Consider applying limiting-case analysis on it.
  • That is, set the variable in question to its maximum or lowest value, and gain clarity over either or both of those cases manually. If that succeeds, then it's usually easier to extrapolate from those examples to understand what's going on wrt to the full range of the variable.

I think it's a usefwl heuristic tool, and it's helped me with more than one paradox.^[1] I also often use "multiplex-case analysis" (or maybe call it "entropic-case"), which I gave a better explanation of in the this comment [LW · GW].

1. ^{^}

   A simple example where I explicitly used it was when I was trying to grok the (badly named) Friendship paradox, but there are many more such cases.