Brain Scanner Can Tell What You're Looking At

Brain Scanner Can Tell What You're Looking At - Via WIRED:

Tell me what you see.

On second thought, don't: A computer will soon be able to do it, simply by analyzing the activity of your brain.

That's the promise of a decoding system unveiled this week in Nature by neuroscientists from the University of California at Berkeley.

The scientists used a functional magnetic resonance imaging machine -- a real-time brain scanner -- to record the mental activity of a person looking at thousands of random pictures: people, animals, landscapes, objects, the stuff of everyday visual life. With those recordings the researchers built a computational model for predicting the mental patterns elicited by looking at any other photograph. When tested with neurological readouts generated by a different set of pictures, the decoder passed with flying colors, identifying the images seen with unprecedented accuracy.

"No one that I know would ever have guessed our decoder would do this well," study co-author Jack Gallant said.

As the decoder is refined, it could be used to explore the phenomenon of visual attention -- concentration on one part of a complicated scene -- and then to illuminate the dimly understood intricacies of the mind's eyes.

"One day it may even be possible to reconstruct the visual content of dreams," Gallant said.

After that, the decoding model could be harnessed for more visionary purposes: early warning systems for neurological diseases or interfaces that allow paralyzed people to engage with the world.

Other uses may not be so noble, such as marketing campaigns crafted for maximum mental penetration or invasions of mental privacy mounted in the name of fighting terrorism and crime.

Those technologies remain decades away, but researchers say it's not too soon to think about them, especially if research progresses at the pace set by this study.

Earlier decoders could only tell whether someone looked at a general type of image -- at a dog, for example -- but couldn't identify more specific photos, such as a small dog eating a bone. They've also been incapable of predicting what thought patterns an image would provoke.

The Berkeley model overcame both those limitations.

(Read Original Article - Via WIRED.)