Dreams are shaped by your personality, experiences, and even global events. Your brain transforms everyday life into vivid, often surreal stories while you sleep.
Why do some dreams feel vivid and lifelike while others seem disjointed or hard to understand? A new study from researchers at the IMT School for Advanced Studies Lucca offers answers, showing that both personal traits and shared life experiences shape what we dream about.
Large Study Tracks Dreams and Daily Experiences
Published in Communications Psychology, the study examined more than 3,700 descriptions of dreams and waking experiences from 287 participants ranging in age from 18 to 70. Over a two-week period, participants recorded their experiences each day. Researchers also collected detailed data on sleep patterns, cognitive abilities, personality traits, and psychological characteristics.
AI Analysis Reveals Patterns in Dream Content
The team used advanced natural language processing (NLP) methods to analyze the meaning and structure of dream reports. This approach allowed them to study dreams in a systematic and measurable way. The results show that dreams are not random or chaotic. Instead, they reflect a complex interaction between internal factors such as mind-wandering tendencies, interest in dreams, and sleep quality, and external influences, including major societal events like the COVID-19 pandemic.
How the Brain Reworks Reality During Sleep
By comparing descriptions of daily life with dream reports, researchers found that the brain does not simply replay waking experiences. Instead, it reshapes them. Familiar settings like workplaces, hospitals, or schools are not reproduced exactly. They are transformed into vivid scenes that often combine different elements and shift perspectives in unexpected ways.
This process suggests that dreams actively reconstruct reality. The mind blends memories with imagined or anticipated experiences, creating new scenarios that can feel immersive or even surreal.
Personality and Life Events Influence Dream Style
Dream experiences vary widely from person to person. Individuals who tend to mind-wander more often reported dreams that were fragmented and constantly shifting. In contrast, those who believe dreams are meaningful and important described richer and more immersive dream environments.
The study also explored how large-scale events affect dreaming. Data collected during the COVID-19 lockdown by researchers at Sapienza University of Rome, and later compared with findings from the IMT School team, showed that dreams during that period were more emotionally intense and frequently included themes of restriction and limitation. Over time, these patterns became less pronounced, suggesting that dream content changes as people psychologically adapt to major life events.
Dreams Reflect a Dynamic Mental Process
“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,” explains Valentina Elce, researcher at the IMT School and lead author of the paper. “By combining large-scale data with computational methods, we were able to uncover patterns in dream content that were previously difficult to detect.”
AI Opens New Possibilities for Dream Research
The study also highlights the growing role of artificial intelligence in understanding dreams. NLP models were able to capture the meaning and structure of dream reports with accuracy comparable to human independent evaluators. This opens the door to new ways of studying consciousness, memory, and mental health on a larger scale and with greater consistency.
Reference: “Individual traits and experiences predict the content of dreams” by Valentina Elce, Giorgia Bontempi, Serena Scarpelli, Bianca Pedreschi, Pietro Pietrini, Luigi De Gennaro, Michele Bellesi, Giulio Bernardi and Giacomo Handjaras, 28 April 2026, Communications Psychology.
DOI: 10.1038/s44271-026-00447-2
This research was supported by a grant from the BIAL Foundation (#091/2020) and by the TweakDreams ERC Starting Grant (#948891). The work was conducted at the IMT School for Advanced Studies Lucca in collaboration with researchers from Sapienza University of Rome and the University of Camerino.
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