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Dream-Reading Machine Helps Decode Brain Activity, Study Shows

April 04, 2013

Dream-Reading Machine Helps Decode Brain Activity, Study Shows

An fMRI scan. Photographer: Stegerphoto via Getty Images

Dreams can be decoded using a machine, a step furthering efforts to understand spontaneous brain activity, according to a study published in the journal Science.

Scientists examined three subjects’ brain activity during the early stage of sleep using functional magnetic resonance imaging, or fMRI, and repeatedly woke them up to describe their dreams, the study showed. The researchers, from the Advanced Telecommunications Research Institute and Nara Institute of Science and Technology in western Japan, found correlations between participants’ fMRI patterns and verbal accounts.

The findings published today are a step toward creating a communication pathway between patients unable to verbalize their thoughts and an external device, according to Yukiyasu Kamitani, a co-author of the study. The imaging method can also be used to examine other patterns of brain activity during sleep and rest, known to be linked to mental illnesses including schizophrenia and depression, he said in an e-mail.

The private nature of dreams has hampered objective analysis before this method was established, the authors wrote.

Little is known about the causes of many brain disorders such as dementia, expected to afflict 65.7 million people by 2030, an increase of 85 percent from two decades earlier, according to the London-based Alzheimer’s Disease International.

U.S. President Barack Obama last week announced the BRAIN Initiative, which will spend $100 million to map the interactions between brain cells and neurological circuits. The campaign, starting next year, may lead to new treatments for some of the most common brain disorders led by Alzheimer’s, epilepsy and brain injuries, Obama said April 2.

To contact the reporter on this story: Kanoko Matsuyama in Tokyo at kmatsuyama2@bloomberg.net

To contact the editor responsible for this story: Jason Gale at j.gale@bloomberg.net


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