'Mind-reading' device comes closer to reality as scientists decode 'internal voices'
ANI | Feb 1, 2012, 05.54PM IST
'Mind-reading' device comes closer to reality as scientists decode 'internal voices'
Scientists have succeeded in decoding electrical activity in a region of the human auditory system called the superior temporal gyrus (STG), analyzing which, they were able to reconstruct words that subjects listened to in normal conversation.
WASHINGTON: Scientists could soon be able to eavesdrop on the constant, internal monologs that run through people's minds, or hear the imagined speech of those patients who cannot speak, a new study has revealed.
The scientists at the University of California, Berkeley have succeeded in decoding electrical activity in a region of the human auditory system called the superior temporal gyrus (STG). By analyzing the pattern of STG activity, they were able to reconstruct words that subjects listened to in normal conversation.
"This is huge for patients who have damage to their speech mechanisms because of a stroke or Lou Gehrig's disease and can't speak," said Robert Knight, Professor of Psychology and Neuroscience at UC Berkeley.
"If you could eventually reconstruct imagined conversations from brain activity, thousands of people could benefit.
According to first author Brian N. Pasley, a post-doctoral researcher at UC Berkeley, this research is based on sounds a person actually hears.
"But to use this for a prosthetic device, these principles would have to apply to someone who is imagining speech," cautioned Pasley.
"There is some evidence that perception and imagery may be pretty similar in the brain. If you can understand the relationship well enough between the brain recordings and sound, you could either synthesize the actual sound a person is thinking, or just write out the words with a type of interface device."
Pasley tested two different methods to match spoken sounds to the pattern of activity in the electrodes.
The patients then heard a single word and Pasley used two different computational models to predict the word based on electrode recordings.
The better of the two methods was able to reproduce sound close enough to the original word for him and fellow researchers to correctly guess the word better than chance.
"We think we would be more accurate with an hour of listening and recording and then repeating the word many times," Pasley said.
But because any realistic device would need to accurately identify words the first time heard, he decided to test the models using only a single trial.
"I didn't think it could possibly work, but Brian did it," Knight said.
"His computational model can reproduce the sound the patient heard and you can actually recognize the word, although not at a perfect level," Knight added.
The study has been recently published in the open-access journal PLoS Biology.
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