Locked-in, Reaching-out

Salvation for locked-in patients — those so completely paralyzed that they can’t speak, or often even blink to let us know that there’s a consciousness still there trapped inside their bodies — may be a long, long way away. But something else important is drawing closer: ways for these patients to communicate with the outside world. The New York Times carried a story Wednesday about a team of researchers in Britain and Belgium who have been studying patients in vegetative states, trying to make contact. Out of 54 vegetative and “minimally conscious” patients, five turned out to be reachable via fMRI:

To open a channel of communication, they instructed one of them, the 29-year-old man, to associate thoughts about tennis with “yes” and thoughts about being in his house with “no.”

They then asked questions, repeating the procedure numerous times, switching the associations — tennis with yes, then with no — to make sure the patient was in fact making conscious choices. The researchers had previously tested the technique in healthy volunteers.

“We asked basic biographical questions, like ‘Is your father’s name Thomas?’ and ‘Have you ever been to the United States?’ ” said Adrian M. Owen, a neuroscientist at the Medical Research Council in Cambridge, England, who developed the method and was a co-author of the paper. “We then checked whether the answers were correct. They were.”

Thinking about playing tennis made brain regions associated with movement light up on the scanner; thinking about being in a house made regions associate with spatial relationships light up. And, thus, the researchers were able to create a very simple, very indirect language for “yes” and “no.”

Getting “yes” or “no” answers, however, isn’t the limit of what we may be able to do for locked-in patients in the near future. Take, for instance, this remarkable work, published in PLoS ONE. In short, what this team of scientists is creating is a speech synthesizer that would plug directly (and, after implantation, wirelessly) into a locked-in person’s brain.

We’ve already seen systems that allow locked-in patients to type (even Tweet!) through a Brain-Computer Interface (BCI) using technologies like EEG helmets. But these BCI typing systems are very slow and labor intensive. The ultimate, long-term goal of this BCI speech-synthesizer technology would be to use signals from the brain’s speech motor cortex (the part of the brain that tells your voice what to do) to create something approximating actual, real-time speech.

You can take a look at this diagram to get a sense of what the system does:

Signals collected from an electrode implanted in the subject's speech motor cortex are amplified and sent wirelessly across the scalp as FM radio signals. The signals are then routed to an electrophysiology recording system for further amplification, analog-to-digital conversion, and spike sorting. The sorted spikes are sent to a Neural Decoder which translates them into commands for a Speech Synthesizer. Audio signals from the synthesizer are fed back to the subject in real time. (from PLoS ONE)

Basically, through electrodes implanted in the brain, it sends a wireless signal to a neural decoder, which then tells the speech synthesizer what to do. The system was tested on a 26-year-old male suffering from locked-in syndrome due to a brain stem stroke incurred at age 16. The stroke left the brain areas responsible for consciousness, cognition, and higher-level aspects of movement control intact, while eliminating nearly all voluntary movement.

While this young man’s abilities with the synthesizer are, in the words of the study, “limited to producing a small set of vowels,” it’s the proof-of-concept that matters here. The researchers found that even in a very short training session with the system, the participant’s average hit rate in being able to create a desired sound rose from 45% on the first block to 70% on the last block across sessions — reaching a high of 89% in the last block of the last session.

You can see how the training works in the video below: