AI digs through 3,700 accounts of dreams and waking life, finds method in the madness

Your brain apparently spends the night remixing reality rather than simply replaying it, according to researchers armed with AI and more than 3,700 accounts of dreams and waking life. Researchers at Italy's IMT School for Advanced Studies Lucca used natural language processing (NLP) to analyze more than 3,700 reports of dreams and waking experiences from 287 adults and found dreams are neither random mental noise nor faithful replays of the day's events. Instead, the sleeping brain appears to recycle memories, emotions, familiar places, and imagined possibilities into entirely new scenarios. Published in Communications Psychology, the study combined two weeks of dream and daily experience diaries with data on participants' personalities, sleep quality, cognitive abilities, and psychological traits. Researchers used NLP to compare the semantic structure of the waking and dream reports. Everyday settings such as workplaces, hospitals, and classrooms were combined with unrelated places, shifting viewpoints, or unfamiliar surroundings, while different parts of a person's life could merge into a single scene. The findings suggest dreams do not replay reality so much as rebuild it from familiar parts. Dream reports also varied with participants' traits and attitudes. Those prone to mind-wandering tended to report dreams that jumped quickly from one scene to another, while those who said dreams were personally meaningful generally described more vivid and immersive experiences. The researchers also looked at dream reports collected during the COVID-19 lockdown by a separate team at Sapienza University of Rome. Compared with more recent reports, those dreams contained more references to confinement, barriers, restrictions, and heightened emotions, reflecting the reality people were living through at the time. "Our findings show that dreams are not just a reflection of past experiences, but a dynamic process shaped by who we are and what we live through," said lead author Valentina Elce. "By combining large-scale data with computational methods, we were able to uncover patterns in dream content that were previously difficult to detect." The work also hints at a new role for AI. Rather than asking researchers to read and categorize thousands of dream reports themselves, the team used NLP to spot patterns across the entire dataset. The software's assessments closely matched those of independent human reviewers, suggesting it could make large-scale dream studies far less laborious. Before you ask ChatGPT why your dentist turned into your boss, the research has some obvious limitations. It relies on people remembering and accurately describing their dreams, and it doesn't explain why we dream in the first place. However, it does suggest dreams have more structure than random neural noise - even if your brain still insists on making you sit an exam you forgot to revise for. (R)