Matrix-Style Instant Learning Could Be One Step Closer

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20:07 December 14, 2011

Researchers have used functional magnetic resonance imaging technology to help test subjec...

Researchers have used functional magnetic resonance imaging technology to help test subjects improve at visual tasks

How would you like to have the ability to play the piano downloaded into your brain? You might not end up with the same sense of achievement, but it sure would be a lot quicker and easier than years of lessons and practicing. Well, we're not there yet (and perhaps we never should be), but that sort of scenario is now a little closer to reality, thanks to research conducted at Boston University and ATR Computational Neuroscience Laboratories in Kyoto, Japan.

The basic idea is this: using a technique known as decoded neurofeedback, or DecNef, people could be trained to alter their brain activity, so that it matched that of someone already possessing a certain skill.

Scientists at the two institutions used functional magnetic resonance imaging (fMRI) to observe the visual cortex activity pattern of test subjects as they viewed striped circles placed in various orientations. The researchers then used DecNef to train the subjects to change their brain pattern, so that it more closely resembled a predetermined target pattern. This was done by presenting them with an image of a green circle, which got larger the closer they got to achieving the target pattern.

It was found that once subjects had matched that pattern repeatedly, their performance at a given visual task (discriminating between different orientations of the striped circles) improved, and stayed that way for some time. This approach even worked when the subjects weren't aware of what the visual task was that they were being trained for.

While the instant acquisition of complex skills, such as flying a helicopter as seen inThe Matrix, might not be possible any time soon, the researchers believe that DecNef might also have therapeutic value, as people with mental disorders could be trained to match the brain activity patterns of healthy individuals.

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