An Integrated Foundation of Cognitive Behavioral Therapy Using Load Minimization Theory (LMT) and Computational Cognitive Science  〜As a Load Optimization Process in Menopausal Disorders and PMS/PMDD〜

This study does not present results from a rigorous clinical trial; rather, it is a theoretical proposal based on computational simulation. Although cognitive behavioral therapy (CBT) has demonstrated strong clinical efficacy, its underlying mechanisms remain partially opaque. This paper proposes Load Minimization Theory (LMT) and integrates it with computational cognitive science (predictive coding, Bayesian brain, and dynamical systems theory) to reformulate CBT as a total load optimization process. Hormonal fluctuations in menopausal disorders and premenstrual syndrome (PMS/PMDD) are explicitly modeled as exogenous perturbations. Numerical simulations over two menstrual cycles show that LMT-CBT alone can reduce total load by 25–35%, while combination with pharmacotherapy yields an additional 15–25% reduction. These findings provide a computational foundation for CBT, especially in hormone-related psychiatric symptoms, and support the expansion of insurance-covered CBT under the 2026 Japanese medical fee revision. They also suggest new directions for AI-assisted personalized interventions.