Imagine that a debilitating illness, stroke or accident has left you entirely paralyzed. You’re fully conscious but unable to move or even communicate with those around you. People in this condition—known as Locked-in Syndrome—suffer greatly, locked in their own minds, appearing superficially to be in a persistent vegetative state despite a full inner life.
A new device, described in a paper published yesterday in the journal Current Biology, may offer hope to those locked-in: a new use of fMRI technology to read minds. The experimental setup allows individuals to “type” 27 symbols (26 letters and a space) without saying a word or moving a muscle, but rather by simply engaging in different thought patterns. The system could someday provide a practical means of daily communication for those who are unable to move.
According to Scientific American, the lead author of the study, Bettina Sorger of Maastricht University in the Netherlands, first started thinking about communicating with paralyzed patients after an experience she had about 10 years ago while working as a nurse. A patient who was recovering from anesthesia in the intensive care unit and seemed incapable of movement or speech suddenly tried to choke her. Then, a week later, he ran into Sorger while fully conscious and promptly apologized. She was stunned to realize that although he had little control over his movements while partially anesthetized, he was fully conscious and could even remember his actions a week later. Perhaps there could be some way to enable such patients in such a situation to communicate via mental activity alone, she thought.
Now Sorger is a researcher in neurocognition, and she and her colleagues have created a proof-of-concept device that could someday be used for those either temporarily or permanently paralyzed to achieve this goal. In the study, six healthy adults learned how to answer questions by mentally “typing” individual letters on a computer screen.
The participants first underwent one hour of training to learn how to pick various letters by distinct thought patterns. While lying inside a functional magnetic resonance imaging (fMRI) machine—which precisely measures activity in different parts of the brain by detecting the amount of blood flow—they stared at a table that included all 26 letters and a symbol for space. The letters were arranged in three rows, and each row was associated with a different type of mental task: motor imagery (such as tracing a shape in the mind), mental calculation (such as performing a multiplication problem), or inner speech (such as silently reciting a piece of text). Additionally, different columns of letters were illuminated on the screen at different times for different durations, in a consistent sequence.
To select a letter, participants waited for that letter’s column to light up, and then performed the specific type of mental task associated with that letter’s row as long as the letter stayed lit. For example, to select the letter ‘L’ in the graph below, the participant would wait 10 seconds for the onset delay until the row lit up, then would perform a mental calculation for a full 10 seconds, until the column with ‘C’, ‘L’ and ‘U’ dimmed. If they continued the mental task for 20 seconds, instead of 10, an ‘M’ would be detected.
Because the fMRI machinery is capable of distinguishing among the mental activity patterns that fit each of the three tasks, and can also track when and for exactly how long the task was mentally performed, the system could use both of these parameters to figure out which letter the participant meant to select. The participants painstakingly “typed” out letters to answer a variety of questions, such as “what is your name?” and “what movie did you see last?”
The system was able to accurately determine the first letter of each response a respectable 82 percent of the time, but an innovative use of context-dependent text recognition software—the same type that enables your smartphone to figure out you meant to type “great” instead of “grear”—meant that the first letter was correctly detected 95 percent of the time when the second letter was taken into account, and 100% once the third one was typed.
Although the system required a bulky fMRI machine and was performed with healthy participants, it’s easy to imagine how this could eventually be adapted to be used for those unable to speak or move. The grid could even be changed based on the context, with, say, pictures of food choices or room temperatures presented instead of letters. With practice, the process of choosing letters could likely be accelerated, too, and entire commonly used words could even be selected instead of letters.
This new system joins a number of other mind-reading interface devices developed in recent years to give locked-in patients the chance to communicate. As these systems are improved and refined, we might see them in hospitals such as the one Sorger once worked in to let these patients literally share their thoughts. “Even if one person benefits,” she says, “I would be very happy.”