For many years, philosophers and researchers have been interested in the concept of dreaming. These explorations can be traced back to Aristotle and later on to Descartes, who introduced the Dream Argument in 1641, which stated that dreaming questions what is reality and makes us doubt our senses. In the article published by Konkoly et al., researchers from various educational institutions tested to see how well people could communicate while experiencing lucid dreaming. There were a total of 36 participants, all ranging from the amount of lucid dreaming experienced. One notable patient suffered from narcolepsy. In this experiment, researchers would ask questions and prompt the participants to do little tasks or answer the questions all while they were in REM sleep and were possibly lucid dreaming. Certain “yes” or “no” questions were taught to be answered a certain way like a head shake or a hand movement, depending on the answer willing to be given by the participant. The results from this experiment were very captivating. Most of the participants understood and answered the questions correctly, such as simple math questions. The participants later recalled hearing the questions, not always directly from the person asking them but sometimes in disoriented ways such as through a radio or from a TV (Konkoly et al., 2021). This research makes me question how memory plays a role in the lucid dreams that people often encounter during REM sleep and if better memory can affect the profoundness of sleeping.
Recently, Amo et al., took a similar take on this experiment and focused on eye gestures with 2-D electrooculography. The 2 deep neural networks incorporated into this experiment tested for gesture organization and classification and the other for translating these eye movements into language sentences. There were two studies conducted and both yielded high results for accuracy meaning that the encoding and decoding of the prompts were mostly accurate amongst the participants. The first study showed a 78% accuracy using the CNN model and the second study demonstrated an 100% accuracy for decoding and maintaining the overall message of the prompt (Amo et al., 2025). Additionally interesting, the participants varied in their position, either being upright and eyes slightly open or laying down with the eyes closed and both positions still yielded significantly high results.
While still on the topic of lucid dreaming, Mallet experimented with memory and lucid dreaming. In this experiment, participants were asked to change the scenery of the dream to fit more realistic environments or memories. Participants were asked to analyze a scene such as “a rubber snake coiled upwards in a striking position” and then asked to re-create this scene as vividly as they could while lucid dreaming at home. The results showed that from the 23 participants, only 9 were able to re-create this environment in their dreams but out of those 9, 2 were in a semi-lucid dream and another was not lucid dreaming (Mallet, 2020). Some of the participants who claimed they were able to shape their lucid dreams also claimed that they were animating some objects, making them not as realistic as the scene showed them to be. These results demonstrate that although lucid dreaming can be somewhat moldable, it is not always accurate and our memory does not always serve us the best in being able to work while unconscious.
References
Amo, V., Godt, N., Leugering, J., Appel, K. (2025). Levering Deep Neural Networks for Lucid Dreaming Communication via Two-Dimensional Electrooculography. Dreaming, 35(S1).
https://research.ebsco.com/c/i22ucx/viewer/pdf/ydkkhupxyb?route=details
Konkoly, et al. (2021). Real Time Dialogue between Experimenters and Dreamers during REM
Sleep. Current Biology, 31(7). https://www.sciencedirect.com/science/article/pii/S09609-
82221000592
Mallet, R. (2020). Partial Memory Reinstatement While (Lucid) Dreaming to Change the Dream
Environment. Science Direct, 83. https://www.sciencedirect.com/science/article/pii/S105-
3810020300295
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