mri_overlay5“Our dreams might seem like subjective, private experiences, but they produce objective, consistent pieces of data that can be analyzed by others.”

Unimaginable to sound but researchers from Kyoto, Japan, say that they have built something of a “dream-reading machine”, which learned enough about the neurological patterns of three research participants to predict their sleeptime visualizations with 60 percent accuracy. The study, published today in Science is believed to be the first of its kind in which objective data has been culled about the contents of a dream.

Using an MRI, EEG, a learning software and a library of online images, the researchers tried their special algorithm on test subjects during rounds of sleeping. What they found is they could measure brain activity during dreams and correlate that information with different images to predict what subjects are seeing.

The deepest, longest dreams occur during REM sleep, which typically begins after a few hours of sleeping. But quick, sporadic hallucinations also occur during stage 1 of non-REM sleep, which starts a few minutes after you sleep. The researchers sought to track the visualizations during this stage.

The algorithm got it right 60 percent of the time, a proportion the researchers say can’t be explained by chance but still there is a long way to go in this particular field of science.