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 Mind-reading machine knows what the eye can see

This story is from the category The Brain
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Date posted: 06/03/2008

Researchers from the University of California, Berkeley, US, have developed a much more sophisticated algorithm for the extraction of visual stimuli from human brain signals.

Previously, the best we could hope for, was to detect neuron firing patterns in relation to named subjects in the field of view.

Using a computational model that uses functional MRI (fMRI) data to decode information from an individual's visual cortex, the results are a long long way from perfect, but are finally on a track that leads to being able to eventually take the entirety of visual images from the brain.

"Our research makes substantial advances towards being able to decode mental content from brain activity as measured using fMRI," Kay Kendrick, a co-author of the study, said. "In fact, our results suggest it may soon be possible to reconstruct our visual experiences from brain activity."

The team first used fMRI to measure visual cortex activity in people looking at more than a thousand photographs. This allowed them to develop a computational model and "train" their decoder to understand how each person's visual cortex processes information.

Next, participants were shown a random set of just over 100 previously unseen photographs. Based on patterns identified in the first set of fMRIs, the team was able to accurately predict which image was being observed.

"It is going to be particularly powerful in the field of visual perception and possibly the field of decoding motor responses," says John-Dylan Haynes of the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany.

The research also hints that scientists might one day be able to access dreams, memories and imagery, says Haynes, providing the brain processes dreams in a way that is analogous to visual stimuli.

"The difficulty is that that it's very hard to set up models for other types of complex thoughts, such as memories and intentions."

See the full Story via external site: technology.newscientist.com



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