Symbiotic Lifestyle-Cognition Dynamics: A Multi-Modal Analysis of Interaction Effects on Human Memory Performance

Traditional cognitive science approaches examine lifestyle factors (sleep, stress, diet, exercise) as independent predictors of cognitive performance. However, emerging evidence suggests these factors operate as symbiotic systems with non- linear interaction effects that remain poorly understood. We analyzed a large-scale dataset of 80,000 participants (ages 18–59) to investigate how lifestyle factors interact to influence memory performance. Using machine learning approaches com- bined with interaction term analysis, we identified symbiotic cou- pling patterns between physiological response metrics (reaction time), cognitive state (cognitive scores), and lifestyle variables (sleep duration, stress, screen time, exercise, caffeine intake). Our analysis revealed strong symbiotic interactions, with the reaction time and cognitive score coupling emerging as the dom- inant predictor of memory performance ( r  = 0.559, p <  0.001). Gradient boosting models achieved 66.4% explained variance ( R ²  = 0.664) in memory test scores, significantly outperforming additive models. We identified four distinct cognitive-lifestyle phenotypes through unsupervised clustering, each characterized by unique interaction signatures. The stress level × screen time interaction (feature importance = 0.101) emerged as the second-most critical factor, suggesting a previously underappreciated synergistic pathway. These findings demonstrate that lifestyle factors operate through symbiotic coupling mechanisms rather than additive ef- fects. The identification of interaction-based phenotypes provides a novel framework for personalized cognitive interventions and challenges the reductionist paradigm in cognitive health research.