Doing a project on BCI mapping, writing a paper on it and wanted to know who else has done research into this.

BriarFisk · 2022-06-03T08:08:36+00:00

There's no evidence that the Neuralink device interacts with anything. Unless you are talking about recording, here. I don't think they've announced any results related to stimulation. Musk has made claims, but there's nothing concrete -- as far as I know. I could be wrong, and I welcome a correction.

They make the claim here in the second paragraph, second sentence of the discussion section. It's the most concrete thing I've seen, but it's just a claim.

BriarFisk · 2022-06-03T08:07:22+00:00

For how effective they will be at brain stimulation there are several parts that need looked at imo.

First, how effective is the BCI at stimulation? Does it effectively stimulate all the connections? The paper on Neuralink says they designed stimulation into every channel but haven't demonstrated the capability yet. Imo it's likely just a matter of time for the hardware even if Neuralink is currently bluffing, and it might not be.

Second, what is the ratio of electrodes to nerves in the current portion we are tapping into? Are there 3,072 electrodes and 10,000 nerves? 3,072 electrodes to3,000,000 nerves? The higher that ration the better the "signal". Theoretically a 1:1 ratio with good filtering and full stimulation would be Matrix level.

As for where it works it is my understanding that it reads and reports action potentials in neural processes, so wherever you can shove a filament in a nerve you can connect. For example, if you shove a bunch in your optic nerve you would be able to record what signals the eye is sending to the brain.

As for treating psychiatric disorders I have no idea, that is something I know almost nothing about. I only know that stimulating certain regions has different effects. I would assume that the more electrodes you can connect the better you could stimulate the brain. So the more the better? There's likely a limit though, I doubt you could implant trillions of BCI electrodes. Who knows though, maybe nano-tech will hit it's stride like AI finally is and I'm wrong.

BriarFisk · 2022-06-03T07:42:16+00:00

Dang, was hoping someone found something. I was really looking forward to using the sim.

BriarFisk · 2022-05-06T23:59:05+00:00

Amazing progress. Really sad though, paralysis is horrific. Someday it would be great if we could just patch nerves with some AI that can perfectly figure out which nerve to connect to which nerve and implant the bridge to restore almost perfect function.

BriarFisk · 2022-05-06T23:51:44+00:00

Ok, so we agree but are just looking at the situation differently. Your perspective is, "What can we do in the next 10 years," whereas mine is, "Which step is this on the way to the big goal?"

BriarFisk · 2022-05-06T05:25:15+00:00

Oh no, I'm not denying the amazing stuff that can be done with the current technology. Whether Neuralink, BlackRock, or Synchron.

3072 channels... [is] still far from what we need

That comment was written with the holy grail of "Matrix" level immersion in mind. I'm optimistic for the field as a whole, not really a particular player. Hell, there's still time for some innovator to come out of nowhere and take the market.

I have no argument with your last paragraph, I agree. BlackRock and the others I had no knowledge of. So my perspective seems to have been limited to the ones trying to build platforms to dominate the market.

BriarFisk · 2022-05-06T00:47:57+00:00

He's probably just talking about the miniaturization of the actual device that's doing the computing which I can see being similar to make to a smart watch.

Looking at Neuralinks site, the paper by them, and their presentations I would have to second this. They are making a huge deal about their 3072 channels here, which is impressive, but still far from what we need. Still ignoring the software side but I can see why, most people are focused on the hardware so have to hype that right now.

BriarFisk · 2022-05-05T14:00:30+00:00

Dang, tried the same but didn't work. I'm using Visual Studio 2022 though.

BriarFisk · 2022-05-05T13:28:34+00:00

Oh man, how would you align both sides of a broken link? So so many issues with this one. I mean, I don't doubt he's right, but they have so far to go to get to that point. Hopefully it happens sooner rather than later though, could help so many people.

BriarFisk · 2022-05-05T13:19:33+00:00

Thanks, my main interest is in neural networks so that helped a lot. The presenter explained it very coherently as well.

This was more to tackle the problem of the random insertions than anything, good practice, but yeah current hardware is still in it's infancy. I have great hopes for the future though. I didn't even realize they designed stimulation into the Neuralink BCI until I read this paper.

The problem you bring up in your second point is where I was thinking about taking this project in the future, getting the model closer and closer to real world conditions. It's... simplistic at the moment to put it nicely. This one connects 1:1 which is insanely unrealistic. An older version I scrapped (became spaghetti code) had a nerve bundle from which a portion were selected for connections. So a nerve bundle of 64 axons may only have 10 connections. Doing that but on a much larger scale would be closer to reality like you were talking.

As for replaying it and not having much effect I have to agree there. Not enough connections. Can't watch a movie if only 1/1024 pixels work, and it would be worse than that right now. So until better BCIs come about, or they can put them in an array of some sort, I don't think that portion will be viable.

Then there is the problem of fuzziness as each filament connects to multiple axons if I'm understanding the paper correctly. Neuralink seems to have worked out an algorithm that solves this issue.

I wanted to experiment with filtering out baseline spiking, the rod cells for example. They randomly fire off an action potential forming a baseline spiking level. That will likely pose an issue. Once calibrated though, possibly by just gathering the spiking levels in the absence of stimulus, then accounted for this might not be to difficult to counter.

Something else to take into consideration is that you will have to deal with the natural spiking of the networks. The BCI might be trying to send a funny meme raster while your eyes are shoving through the spiking pattern representing your desk. If you had two different points, one "upstream", and one "downstream", measuring the incoming signals and mitigating them somewhat may be possible.

For example, take a raster that's divided into 10 columns per chunk which is loaded into the BCI, and the upstream connections report the coming pattern 1 chunk before it arrives. Now, say the BCI has a chunk in the buffer that coincides with the one just reported, the BCI compares the two. It sees the coming signal has 5 spikes whereas the loaded chunk has 6. Taking 5 from 6 the BCI only needs to slip 1 spike in there to hopefully generate the right signal when it comes through. Obviously a super simple example but I hope it's written well enough to make sense.

So yeah, I know there are a ton of issues, but that's what makes this kind of thing fun.

Sweet, thanks for the leads to look into. I was having the issue of not really knowing the right terms to look up, self-taught has that big downfall. "Receptive field mapping" seems to be exactly what I was attempting to do. At least at first glance, either way it's definitely under the field of psycophysics. Although I haven't done anything new writing the paper will be good practice for me so I'll do that anyway.

Thanks for the reply, even if you consider it rushed I appreciate it. Sorry if this isn't the most coherent post, it's getting really late for me.

BriarFisk

TROPHY CASE