Decoding Dreams

Decoding Dreams

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Neuroscientist Yukiyasu Kamitani recorded dream appearances of 20 key objects, such as “male” or “room,” and used a machine-learning algorithm to correlate those concepts with fMRI images to find patterns that could be used to predict what people were dreaming about without having to wake them.

Such information could help inform the study of why people dream, an elusive question in neurobiology. “Knowing what is represented during sleep would help to understand the function of dreaming,” Kamitani says. Analyzing more than 200 dream reports—some 30–45 hours of interviews with each of three participants—Kamitani and his colleagues at the ATR Computational Neuroscience Laboratories in Kyoto, Japan built a “dream-trained decoder” based on fMRI imagery of the V1, V2, and V3 areas of the visual cortex.

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