Why do some dreams feel so vivid and realistic, while others are confusing or hard to remember? New research from the IMT School for Advanced Studies Lucca suggests that the answer lies in a combination of personal traits and shared life experiences, both of which influence what we see and feel while sleeping.

The study, published in Communications Psychology, examined more than 3,700 reports in which 287 participants aged 18 to 70 described both dreams and waking experiences. Over a two-week period, the participants kept daily records of their experiences. At the same time, the researchers collected detailed data on sleep habits, cognitive abilities, personality traits, and psychological profiles.

AI Reveals Hidden Structure in Dreams

To analyze this large dataset, the researchers used advanced natural language processing tools. These methods enabled them to systematically examine the meaning, themes, and structural patterns of dream descriptions, rather than relying solely on subjective case-by-case analyses. Through the use of AI, recurring motifs, emotional content, and linguistic connections across thousands of reports were made visible. The results showed that dreams are neither random nor chaotic. Instead, they reflect a complex interplay between individual characteristics—such as a tendency to daydream, interest in dreams, emotional processing, and sleep quality—and external influences, including significant societal events like the COVID-19 pandemic, which has been shown to influence the content and mood of dreams.

By comparing participants’ descriptions of their daily experiences and their dreams, the researchers found that the brain during sleep does not simply replay waking life. Rather, it is an active processing process: experiences are reorganized, emotionally evaluated, and reassembled in a transformed form. Familiar environments such as workplaces, hospitals, or schools are not reproduced exactly, but are transformed into altered, often more intense scenarios. In doing so, the brain combines different memory fragments, shifts perspectives, and creates transitions that would not be possible in the waking state. This “reworking” could play an important role in processing experiences, consolidating memories, and integrating emotional content.

This process suggests that dreams actively reconstruct reality rather than passively reflecting it. The brain blends memories with imaginary, future, or anticipated events, thereby creating new, often surreal scenarios. Neuroscientifically, it is assumed that networks involved in memory, emotion, and imagination are engaged in this process. Dreams could thus represent a kind of “mental simulation field” in which the brain plays through various possibilities, reevaluates experiences, and creates creative connections. These findings provide important evidence that dreaming may play a functional role in learning, adaptation, and psychological stability—and is not merely a random byproduct of sleep.

Personality and Life Events Influence Dream Style

Not everyone dreams in the same way. People who tend to daydream more frequently reported dreams that were fragmented, changed rapidly, and often featured abrupt scene changes. This type of dreaming likely reflects a more associative way of thinking, in which the brain freely shifts between memories, impressions, and ideas. In contrast, those who attach greater significance to dreams and assume they have deeper meaning tended to experience richer and more immersive dream environments. Their dreams were often more structured, emotionally intense, and rich in detail, suggesting that attention and personal attitudes toward dreams can influence how vividly and coherently they are experienced and remembered. Overall, this suggests that individual personality traits and cognitive styles play an important role in how the brain organizes information during sleep and translates it into dream imagery.

The study also examined how large-scale events affect dreaming. Data collected during the COVID-19 lockdown by researchers at La Sapienza University in Rome and later compared with the IMT team’s findings showed that dreams during this period were significantly more emotionally intense and frequently included themes such as restrictions, confinement, or loss of control. Many people reported scenarios in which they were locked up, had gotten lost, or were unable to escape situations—motifs that reflect real-life circumstances during isolation. Over time and with increasing adaptation to the changed living conditions, these patterns gradually faded. This suggests that dream content evolves in parallel with psychological processing and adaptation to major life changes. Dreams thus appear not only to reflect personal experiences but also to function as a kind of emotional processing system that helps mentally cope with collective stress situations and profound changes.

AI Opens New Pathways for Dream Research

“Our findings show that dreams are not merely a reflection of past experiences, but a dynamic process shaped by who we are and what we are going through,” explained Valentina Elce, a researcher at the IMT School and lead author of the study. “By combining large-scale data with computer-assisted methods, we were able to uncover patterns in dream content that were previously difficult to detect.” This makes it clear that dreams are not simply random images, but structured mental processes that link individual personality, current life circumstances, and emotional experiences. The use of large datasets makes it possible for the first time to analyze these connections systematically and across many people, rather than relying solely on individual dream reports.

The study also illustrates how artificial intelligence—particularly natural language processing methods—can fundamentally advance dream research. NLP models were able to capture the meaning, emotional tone, and structural characteristics of dream reports with an accuracy that matches that of human evaluators or, in some cases, even complements it. This allows large amounts of subjective experiential data to be evaluated consistently without individual interpretations distorting the results. This approach opens up new possibilities for investigating complex topics such as consciousness, memory processing, and mental health on a much larger scale. In the long term, this could help identify typical patterns in dreams associated with specific mental states or disorders, thereby enabling the development of new diagnostic or therapeutic approaches.

This approach opens up new possibilities for investigating complex topics such as consciousness, memory processing, and mental health on a much larger scale. At the same time, the results also reveal a close connection to chronobiology, as dreams are closely linked to the sleep-wake cycle and, in particular, to REM sleep phases, which are controlled by the internal clock. The temporal organization of sleep thus plays a key role in determining when and with what intensity such processing occurs in the brain.