A mind-reading machine may soon be a reality

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London: Imagine a machine that can read what is going on your mind. Well, it may soon be a reality as scientists claim to have successfully decoded brain signals related to vision.

Researchers from the University of Glasgow said they were able see how the brain tuned into different brainwave patterns to code different visual features.

Professor Philippe Schyns, who led the study, said: "How the brain encodes the visual information that enables us to recognise faces and scenes has long been a mystery.

"It`s a bit like unlocking a scrambled television channel. Before, we could detect the signal but couldn`t watch the content; now we can," he was quoted as saying by the Daily Mail.

For their study, the researchers showed six volunteers images of people`s faces displaying different emotions such as happiness, fear and surprise.

In a series of trials, parts of the images were randomly covered so that, for example, only the eyes or mouth were visible.

Participants were then asked to identify the emotion being displayed while electrodes attached to the scalp measured the volunteers` brainwaves.

The scientists were able to show that brainwaves varied greatly according to which part of the face was being looked at.

"Beta" waves, with a frequency of 12 hertz, carried information about the eyes, while four hertz "theta" waves were linked to the mouth.

Information was also encoded by the phase, or timing, of the brainwave, and less so by its amplitude, or strength.

Professor Schyns said: "While we are able to detect EEG activity in certain areas of the brain when particular tasks are performed, we`ve not known what information is being carried in those brainwaves.

"What we have done is to find a way of decoding brainwaves to identify the messages within."

Professor Schyns said the study revealed how the brain tuned into different brainwave patterns to code different visual features.

"It is a bit like radiowaves coding different radio stations at different frequency bands," he added. "This work has huge potential in the development of brain-computer interfaces.

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