I don't think EEGs can really give the spatial and temporal resolution we really need to extract the necessary information for thought decoding (or encoding).
Working with a NN, the brain can probably negotiate the relevant parameters (let's say frequency modulation across one channels with four bins, across 4 spots on the brain), that's 4^4 = 64 values across whatever timebox of resolution you get. That's enough to encode english letters, which itself probably is an underprovisioned mechanism of data transfer).
I wouldn’t be surprised if the biofeedback allows the user to retrain their brain to encode information in low frequency signals—the raw channel capacity necessary to transmit text is quite low, plus the reader NN can also use context if hooked up to a recurrent submodel.