This analysis investigates whether the lexical structure of a dream-defined by how characters, locations, and actions interlink-serves as a biomarker for psychological health. Utilizing Structural Network Analysis, we aimed to identify if higher levels of mental distress correlate with either fragmented narrative networks or overly rigid, repetitive clustering patterns in dream reports. The data reveals a significant structural invariance across all distress categories. Despite varying emotional intensities, the Mean Clustering Coefficient remained remarkably consistent at approximately 0.71 to 0.72 across all four distress quartiles. A regression analysis of the Distress Index against clustering showed a horizontal distribution with no statistically significant linear correlation, suggesting that the underlying “logic” of dream construction does not degrade or transform based on the dreamer’s level of psychological distress. The resilience of these network metrics suggests that while the content of dreams may reflect a person’s mental state, the mathematical framework of dream formation is a robust cognitive constant. For future iterations of this study, we recommend pivoting from broad structural metrics to semantic sentiment analysis or node-specific centrality, as the fundamental network topology appears to be a universal human trait unaffected by transient psychological distress.
Mentor: Paul McKee
Project poster (PDF)
