Imagine before getting into bed, you choose the type of content you want to see in your dream. The day after, you’re excited to grab some popcorn and rewatch the dream, like a movie, in front of your friends.
That all sounds like a dream itself, but we’re getting there, sort of.
As interesting as dreams are, our knowledge of dreaming is currently limited. Once we’ve woken up, we aren’t able to go into much detail, and forget most of our dreams within just a couple of minutes. Although many scientists have theorized explanations as to why we dream, none are universally accepted, and it’s not at all understood.
Still, many researchers and engineers find themselves interested in the phenomenon. I mean, why create technology solely for waketime when we spend nearly 1/3 of our lifetimes asleep? While dream research has continuously been deemed “woo-woo,” there’s been a number of fascinating dream science developments in the past couple of years, many of which seem taken out of a sci-fi novel.
They can generally be separated into three categories: dream stimulation, dream analysis, and dream imaging.
Stimulating and Controlling Dreams
At MIT Media Lab’s Fluid Interfaces Group, so-called dream engineers are building technology that actively interacts with your sleeping mind. By combining sleep tracking and external stimuli, they aim to manipulate the content of one’s dream.
Dormio is a hand-worn sleep stage tracker that takes advantage of hypnagogia, the semi-lucid state before sleep.
Inspired by the Steel Ball technique, the dreamer records audio cues on the paired Dormio app. The audio cue must match what the subject wants to dream about (for example, a cue for forest dreams could be a tree). Dormio then detects the switch to hypnagogia through biosignals, which triggers the audio prompts to play. In their studies, the researchers found that 67% of the Dormio subjects’ dream reports mentioned dreams that incorporated a tree when the word was used.
You can experiment with the Dormio web-app yourself. Since biosignals can’t be tracked without the glove, at-home users must enter time estimates into the timer-based session.
Masca is their eye mask that detects sleep state changes by tracking eye movement. Unlike some existing eye masks, Masca doesn’t require amplifiers or electrodes.
The lab has also worked with our sense of smell because it influences dreamer cognition but doesn’t awaken them. The team developed Essence, a wearable, smartphone-controlled olfactory device that serves as another form of external stimuli for experimentation.
Cocoon merges all of these existing prototypes into one fictional machine that displays their vision for the future.
Other companies primarily focus on lucid dreaming stimulation, desirable due to lucid dreaming’s rarity (only 23% of people have them at least one time a month), and therapeutic benefits. The majority of the technology follows the same design — they’re sleep analyzing headbands that use stage tracking to detect the REM phase, which then triggers lucid dreaming stimuli (audio, light, electrical currents, etc).
Dream + Dream Pattern Analysis
While inducing dreams is certainly an exciting feat, we’re still far from understanding dreams themselves. Thanks to AI, however, researchers are conducting more elaborate studies than ever before.
A recent dream study found that COVID-related dreams (of all kinds) are surging. The research team fed their dream data into an AI algorithm, which scanned for repeated words. It was able to categorize 33 groups of dreams based on the theme.
“The computational linguistics-based, AI-assisted analytics that we used is really a novel approach in dream research,” lead Dr. Anu-Katriina Pesonen told Frontiers Science News. “We hope to see more AI-assisted dream research in future. We hope that our study opened the development towards that direction.”
Similarly, in August, researchers at Roma Tre University reported findings that support the continuity hypothesis of dreams. For their massive study of 24,000 dreams, the researchers designed an innovative dream analysis technique, “a tool that automatically scores dream reports using the Hall and Van de Castle system.”
Scientists have also been taking small steps towards dream imaging. In 2011, UC Berkeley researchers had subjects watch movie trailers and were able to reproduce low-res videos from their brain activity. In 2016, they improved upon the process.
These developments are essential in order to someday screen dreams. Before we are able to “record” an entire dream, we must learn how to reconstruct images from the brain itself.
More recently, independent dream researcher David Oldis collaborated with the University of Texas at Austin’s Cognitive Neuroscience Lab to create an animated reconstruction of movement within a dream. They used electromyography which, “measures muscle response or electrical activity in response to a nerve’s stimulation of the muscle.”
The endgame? They hope that one day, they will be able to reconstruct an entire dream complete with imagery, transcribed speech, and motor behavior.
There are still many ethical issues regarding this surge of dream tech. Sci-fi, like Inception, has taught us to heed such concerns. How will privacy be handled? What about dream exploitation, like using it for marketing purposes? How can we stop this technology from fueling addiction and escapism?
All important things to consider in the coming years, as clearly, this type of technology is no longer a distant dream.