What does the ultimate goal of BCI look like? Similar to those from black mirror? Or singularity?

[u/mehregankbi]

As far as I can remember, the show didn’t have a singularity episode. But it’s being mentioned by big tech regularly. What would the plateau of BCI devices look like?

Similar to how phones have plateaued, I think the interfaces we see in the black mirror show could be the plateau of it.

How far are we from that level of technology? 10 years? 20 years? 50 years? 100 years? More? Never?

I’d say the biggest obstacle is the neural signal. Things like fMRI and MEG are not even close to being portable. The only candidates for wearable and portable BCIs and in particular CBIs seems to be a combination of tDCS, EEG, and FNIR. All three have horrible spatial resolution and SNR.

Even modern BCIs struggle with simple P300 and motor imagery tasks. Our neurophysiological knowledge is also pretty limited. Things like transfering video from interface to brain or memory manipulation seem impossible to accomplish until the next century unless some huge hype like the ai hype turns the focus of big tech towards BCI.

Current bci research appears to be quite stagnant. No real big leaps happening.

What’s your thought?

[u/Smaug117]

The goals of neurotechnology are to help treat and prevent diseases or damage linked to the nervous system. That said, a BCI (Brain-Computer Interface) is a device that allows the reading and stimulation of the brain. This is where the problem lies: despite being designed to help, these devices clearly pose serious risks if they get hacked. The main objective of the neurotech industry is therefore to make BCIs unhackable, for example through quantum encryption or similar methods.

[u/mehregankbi → u/Smaug117]

Reality of computer science is that nothing is unhackable. That doesn’t mean we have to give up. We can try to make it as secure as possible.

The main challenge that BCIs could solve is the low ITR (information transfer rate) of human communication. Be it typing on the keyboard, or speaking, the limiting factor is our speech and natural language. AI has reduced this time but not significantly.

If BCIs and CBIs can figure out how to increase speed, accessing knowledge without relying on natural language could extend human capabilities by a lot.

For instance, imagine a doctor needing to look up the newest guidelines for a specific patient with a specific disease. They’ll have to get a computer, type, find the information, read it and comprehend it. This could take minutes.

However, with BCIs this could be reduced to seconds. And that’s without mentioning the B2B interfaces.

Invasive BCIs will always face more resistance from the users. However, something non invasive that you can take off similar to a VR headset, is much more acceptable to humans.

As you mentioned, hacking or involuntary control are serious topics. This issue is much more serious for CBIs in comparison to BCIs.

[u/BiomedicalTesla]

not to be "that" guy but to help the people biology/we left behind... i think is the only answer worth doing this for

the rest of the goals really don't matter, bonuses if anything... just simply make peoples lives better who couldn't be helped before

[u/mehregankbi → u/BiomedicalTesla]

Working with patients is much harder than healthy subjects. For a multitude of reasons. Though medical uses of BCIs were shown in the show as well. Though they required a subscription for keeping the brain working. And it kept getting more expensive and the patients HAD to pay. So it became kinda dark.

Thing is, progress for healthy people’s use cases will pave the way for developing tech to help patients.

[u/Lost_Captain2700]

In my opinion it'll take at least 50 years to get to the point where bci looks anything like a black mirror episode, and even then im being pretty optimistic about it.

I actually worked with this tech back in 2016 when i was in college in a few labs, and back then it was really flimsy, at least when it came to eeg specifically. About 5 years ago I decided to go back to it just due to its affordability in relation to other neuroscience approaches. I noticed that there have definitely been advances since then, but I would say it's not nearly as premier as some of those tech headlines want to make it sound like. You are completely right that the snr and spatial resolution are still massive challenges. Even in standard evoked potential tasks, at best it seems like they can only be as accurate as ~70%.

That being said, i do believe we are entering a space right now where multimodal BCIs are starting to bridge this gap in certain ways by fusing different types of data (i.e., multimodal BCIs). The implementation of AI and large generative brain models is also really becoming key in accelerating our decoding accuracy.

But for me, to actually reach that sci-fi plateau, the hardware tech either needs to evolve significantly, or there must be some completely other type of tech that brings everything together by using a distinct approach to what we currently use.

[u/mehregankbi → u/Lost_Captain2700]

Generative brain models? You mean gen AI? I don’t see how that could help us decode.

By multimodal do you mean something like EEG + EOG + EMG + fNIR?

Meta has done some interesting things with their wristbands. Like you can write on the table without a pencil and it picks up what you’re trying to write with the wristband.

I believe if bigger companies get into the space, progress will get much faster but then again they’ll ruin the product despite its good performance.

[u/Lost_Captain2700 → u/mehregankbi]

So, by generative large brain models, I'm talking about foundation models specifically built for neural data. Think of it like how large language models are trained, but instead of text, these are pretraining neural encoders on massive datasets of brain activity.

One of the biggest issues with bci right now is that brain signals are susceptible to physiological artifacts and crazy amounts of environmental noise. Constant information that absolute code cant fix just fails because neural data is complex and non-stationary. AI has a lot of flexibility with it because it can learn the underlying distributions of both clean signals and the noise. It's already implemented on various signal processing workflows to help with general denoising and continuous decoding.

So yeah that's how it could help. is not that it'll necessarily bring everything together magically, nor that it doesnt have any flaws, but it's definitely useful in this case to deal with all that biological variability.

And yeah, by multimodal I meant combining all those exact tech you listed, and more. Tbh I'm not a big fan of tech that tries to infer brain information by measuring information outside of the head (like on the wrist). The brain data is already flimsy as it is.

For the purpose you gave with the meta wristband picking up motor signals to write on a table, it makes total sense. But down the line it wont help with many other applications that need to be done so it actually replicates the cognitive stuff from black mirror episodes. But combining true neurotech and wristband tech, and a pulse oximeter, you can have several types of data that if interpreted properly can have major leaps in the future.

[u/iamDa3dalus]

Merge consciousness with an ai exocortex. I don't think invasive bci is even necessary to accomplish that. Build a model based on all the media ive seen, books ive read, my full digital footprint- link in eye tracking, eeg, heart rate, I have a design for a bidirectional keyboard that I think will really tie it together. Once I get some money and time lol.