Looks like a good approach and the error rate of 3% is really good, I guess. Did they mention how they got the input data? I couldn't find it.
They use 250 ECG electrodes as input. I think that means it's above the skin, so not invasive.
Machine translation of cortical activity to text with encoder–decoder framework
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Re: Machine translation of cortical activity to text with encoder–decoder framework
#12Looks like a good approach and the error rate of 3% is really good, I guess. Did they mention how they got the input data? I couldn't find it.
They use 250 ECG electrodes as input. I think that means it's above the skin, so not invasive.
Re: Machine translation of cortical activity to text with encoder–decoder framework
#13Really cool to see progress made here but this won't be available for public use any time soon (likely decades). One of the biggest challenges with decoding brain signals is getting a large number sensors that detect voltages from a very localized region of the brain. This study was done with ECoG (Eletro-Cortico-Gram) which involves implanting small electrodes directly on the surface of the brain. Nearly all consume…
If I may add : EEG is also a pain to put in place (you have to put gel, correctly put the cap etc.) and it's very easy to pollute your signal by merely moving a bit or even blinking.
Re: Machine translation of cortical activity to text with encoder–decoder framework
#14Really cool to see progress made here but this won't be available for public use any time soon (likely decades). One of the biggest challenges with decoding brain signals is getting a large number sensors that detect voltages from a very localized region of the brain. This study was done with ECoG (Eletro-Cortico-Gram) which involves implanting small electrodes directly on the surface of the brain. Nearly all consume…
Re: Machine translation of cortical activity to text with encoder–decoder framework
#15Really cool to see progress made here but this won't be available for public use any time soon (likely decades). One of the biggest challenges with decoding brain signals is getting a large number sensors that detect voltages from a very localized region of the brain. This study was done with ECoG (Eletro-Cortico-Gram) which involves implanting small electrodes directly on the surface of the brain. Nearly all consume…
Re: Machine translation of cortical activity to text with encoder–decoder framework
#16Can we remove the tracking query-string from this link, please? It works fine without it: https://www.nature.com/articles/s41593-020-0608-8.epdf Edit. Sorry, seems to only show the first page if you remove the token.
Re: Machine translation of cortical activity to text with encoder–decoder framework
#17Really cool to see progress made here but this won't be available for public use any time soon (likely decades). One of the biggest challenges with decoding brain signals is getting a large number sensors that detect voltages from a very localized region of the brain. This study was done with ECoG (Eletro-Cortico-Gram) which involves implanting small electrodes directly on the surface of the brain. Nearly all consume…
What's your opinion on Neuralink?
Re: Machine translation of cortical activity to text with encoder–decoder framework
#18Really cool to see progress made here but this won't be available for public use any time soon (likely decades). One of the biggest challenges with decoding brain signals is getting a large number sensors that detect voltages from a very localized region of the brain. This study was done with ECoG (Eletro-Cortico-Gram) which involves implanting small electrodes directly on the surface of the brain. Nearly all consume…
Sparse signal reconstruction is a massive and very possible thing to do using IIRC various forms of FFT.
I think this has already been done, and probably consumer devices will be using sparsity to reconstruct cortical signals with sufficient detail for this.
Re: Machine translation of cortical activity to text with encoder–decoder framework
#19Really cool to see progress made here but this won't be available for public use any time soon (likely decades). One of the biggest challenges with decoding brain signals is getting a large number sensors that detect voltages from a very localized region of the brain. This study was done with ECoG (Eletro-Cortico-Gram) which involves implanting small electrodes directly on the surface of the brain. Nearly all consume…
Re: Machine translation of cortical activity to text with encoder–decoder framework
#20Would that actually translate to decoding the process of turning abstract thoughts into words?
The researchers also note that their models are vulnerable to over-fitting because of the paucity of training data, and they only used a 250-word vocabulary. Neuralink also has a strong commercial incentive to inflate the results, so I'm not too sure about this.
It's great to see progress in these areas, but it seems that technologies like eye-tracking and P300 spellers are probably going to be more reliable and less invasive for quite some time.