United thematically by seemingly infinite dimensions, formless creatures, and figures melting at the seams, the works of Salvador Dali are perhaps best described as hallucinatory snapshots. Dali, enigmatic in death as in life, possessed a distinct creative genius and painting style that captured the thin line between reality and fantasy
While the sources of Dali’s artistic visions have been the subject of a great deal of scholarship and debate, researchers at the Massachusetts Institute of Technology have turned their attention to Dali’s peculiar sleep practices. Like Thomas Edison, Edgar Allen Poe, and Ludwig van Beethoven, Dali believed strongly in the creative impulses unleashed during what is now referred to as hypnagogia – the “semi-lucid sleep stage” that occurs between wakefulness and the Rapid Eye Movement (REM) stage. Each night, Dali would go to bed with a steel ball in his hand. As his muscles relaxed in the transition from hypnagogia to REM, the ball would drop to the floor and wake him – thereby allowing Dali to recall and record his hypnagogic ideas, dreams, and visions. Hypnagogia has typically been studied within the context of narcolepsy and other sleep disorders, but it is experienced by every human being as he or she falls asleep. Cambridge University researcher Valdas Noreika describes the hypnagogic state as a “natural fragmentation of consciousness,” in which the brain produces vivid imagery, abstract scenes, audio experiences, and rapid thoughts without any particular connection to one another. Given that the hypnagogic state was of such importance to many of the world’s intellectual and cultural polymaths, it is perhaps no surprise that unlocking the potential of this unconstrained state of being is of tremendous interest to modern neuroscientists. In the past decade, tangible and previously unthinkable strides in the field have been facilitated by advanced brain activity mapping tools and deep-learning technologies.
In 2018, the aforementioned team of researchers at MIT successfully developed and tested an automated version of Dali’s dream capture system. The device, known as Dormio, is a piece of wearable technology that uses biosignal detection (muscle relaxation, heart rate, skin conductivity, etc) to determine when the wearer is transitioning from hypnagogia to REM. At the transitional point, the Dormio signals to either an accompanying “social robot,” known as Jibo, or a Jibo-based smartphone app to emit audio intended to rouse the wearer back to a semi-sleeping state. Jibo prompts the wearer to recall as much as possible about their dreams, recording them as they do so. Jibo can also voice basic categorical and item words – “fork,” for example, or “rabbit” – to test if the wearer’s next iteration of dreams will have such cues integrated into them. Though seemingly abstract, Dormio and its underlying neuroscience have been featured at the National Academy of Sciences, at the 2018 CHI Conference, and even on ABC’s 60 Minutes as a potential revolution in sleep-tracking technology and a critical step toward understanding the human mind’s unconscious processes.
Rather than risk the influence of so-called “hypnagogic amnesia” on collected data, other hypnagogia researchers have chosen to bypass human recall entirely and focus instead on measurable brain waves. At the University of Texas at Austin’s Cognitive Neuroscience Lab, for example, Daniel Oldis and David M. Schnyer are leveraging electromygram (EMG) and nerve conduction diagnostic tools to discover parallels in brain activity during states of sleep and of wakefulness. Oldis and Schnyer have been able to match electrical nerve impulses sent to various limbs or to the mouth to trigger speech that are consistent across hypnagogic semi-consciousness and waking consciousness. Identified impulses are then modeled on a digital avatar to “mimic the individual’s dream movement.”
In a similar vein, neuroscientists and computer scientists at the University of California-Berkeley, under the leadership of Professor Jack Gallant, have combined functional Magnetic Resonance Imaging (fMRI) and deep-learning computing to reconstruct dynamic images from brain activity, specifically blood flow. The underlying artificial intelligence learns and iterates on the patterns of the brain’s reaction as it “sees” certain images or image types, thereby enabling it to categorize and attempt to recreate the reaction in pixel-image form.
In 2018, Kyoto University Professor Yukiyasu Kamitani built on Gallant’s work to produce an optimized deep-learning technique for independent computer construction of “internal images” of the mind. Kamitani believes his “approach can be extended to reconstruct diverse types of subjective states, such as illusions, hallucinations, and dreams, thereby providing a new window into internal contents of the brain.” Five years prior, Kamitani received recognigion for developing a technique for scanning the brains of napping humans for prior-exposure image recognition patterns and algorithmically translating the basic content of the related dreams into short videos. Kamitani’s process achieved a 70% accuracy rate in comparison to test subjects’ content recall.
As with any new technology or new application of existing technologies (in this case, medical diagnostics), there is a tendency to develop an unrealistic view of the near-term horizon. While some researchers claim that a consumer-targeted device for tracking and decoding dream activity will become available in less than five years, any device produced with even the most advanced science currently available will not be able to record or replay any imagery. Instead, it would more likely be able to tell a user the general content category of their dreams – people, for example, or birds.
“We are opening a window into the movies in our minds.”Professor Jack Gallant, University of California-Berkeley
Even in light of these more limited parameters, however, the current direction of dream-focused technological development is exciting not only for its apparent ability to turn science fiction into reality, but also for its potentially far-reaching implications. For instance, so-called “dream decoding” could be used to better understand, or even communicate, with non-verbal individuals, coma patients, and those who are otherwise unable to express the products of their internal machinations. A window into the activity of the unconscious brain would also provide unprecedented insights into the human psyche, imagination, learning abilities, and memory formation processes. By opening up the “mind’s eye,” we will be opening ourselves to an entirely new conception of the mind itself.