Machine translation of cortical activity to text with encoder–decoder framework
Really cool to see progress made here but this won't be available for public use any time soon (likely decades).<p>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 consumer devices use EEG (Electro Encephelo Gram) which involves putting sensors on the surface of the skin.<p>Commercially available ECoG is highly unlikely as it requires an extremely invasive brain surgery. For ethical reasons the implants from the study we're likely implanted to help diagnose existing life threatening medical issues.<p>Decoding speech from EEG won't work as well as ECoG a number of reasons. First the physical distance between the sensors and the brain Means the signals you pick up aren’t localized. Second the skin and skull are great low pass filters and filter out really interesting signals at higher frequencies, 100-2KHZ. Additionally these signals have a really low signal power because they're correlated with neuronal spiking.<p>ECoG does a really good job picking on these signals because the sensor is literally on the surface of the brain. Its really hard to pick up these signals reliably with EEG.