University of Toronto researchers, who have developed this optical brain imaging technique in collaboration with Canada's largest children's rehabilitation hospital here, say it will help decode thoughts of people with speech disability.
By measuring near-infrared light absorbed in brain tissue when a person made a decision, the researchers were able to predict accurately up to 80 percent their preference for one thing over the other, a university release said Monday.
"This is the first system that decodes preference naturally from spontaneous thoughts," the release quoted study leader and biomedical engineering student Sheena Luu as saying.
As part of their study, the researchers chose nine adults who were first asked to rate eight drinks on a scale of one to five.
After this, they were made to wear a headband fitted with fibre-optics emitting light into the pre-frontal cortex of their brain, and then shown two drinks on a computer and asked to make a decision about which they liked more.
As they made the decision, their brain activity was monitored on a computer specially programmed to recognize the unique pattern of this activity associated with preference.
To their surprise, the computer accurately predicted which drink any individual would prefer 80 percent of the time.
Explaining this, Luu said, ``When your brain is active, the oxygen in your blood increases and depending on the concentration, it absorbs more or less light.
"In some people, their brains are more active when they don't like something, and in some people they're more active when they do like something."
The study leader added, "Preference is the basis for everyday decisions. When children with disabilities can't speak or gesture to control their environment, they may develop a learned helplessness that impedes development."
The study will help them develop a portable, near-infrared sensor that rests on the forehead and relies on wireless technology to know the preferences of disabled people who cannot speak or walk, the university release said.
The study has been published in The Journal of Neural Engineering.