I suppose so; the University of California, Berkeley, has been conducting numerous experiments with brain technology, and coming up with ways to potentially read people's minds.  The data gathered could prove to be rather useful to people suffering from mental disabilities and give them their own, unique form of communication.

"Someday, people whose ability to speak has been damaged by illness or injury may be able to vocalize anyway with the help of technology. Researchers at the University of California, Berkeley, have made strides toward translating the words a person thinks into real speech.

The researchers used 15 patients undergoing neurosurgery as subjects.

They placed electrodes on the subjects' brains, then recorded the activity detected as the subjects listened to a conversation. This recorded data was reconstructed and played back.

Algorithms were used to process the data.

The subjects were exposed to both English words and nonsensical words, and the system worked equally well for both.

That means once the technology becomes practicable, it could be used anywhere.

"The approach was based on auditory features, so it's not specific to English," research team leader Brian Pasley, a post-doctoral student at UC Berkeley's Helen Wills Neuroscience Institute, told TechNewsWorld.

Details of the Research

Up to 256 surface electrode arrays were placed on the surfaces of the superior and middle temporal gyri of the participants' brains.

The superior temporal gyrus includes the primary auditory cortex, which is responsible for the sensation of sound, and Wernicke's area, which is involved in processing speech so it can be understood as language.

It's not clear how the middle temporal gyrus functions, but it's been connected with various processes, including distance contemplation, facial recognition, and accessing the meaning of words while reading.

The participants listened to words for five to 10 minutes while neural signals were recorded from the electrode arrays. Those signals were recorded and played back.

Pasley used two different computational models to match the spoken sounds to the pattern of activity in the electrodes. The better of the two reproduced a sound close enough to the original word that the researchers could correctly guess the word."

Source: Tech News World