Quantum Simulation of Brain Network Dynamics in Psychological Disorders

Abstract

Psychological disorders are increasingly conceptualized as disruptions in large-scale brain network dynamics rather than impairments confined to isolated neural regions. Although classical computational and statistical approaches have advanced the study of neural connectivity, they often fall short in representing the nonlinear, probabilistic, and context-dependent characteristics of brain activity. Quantum simulation offers an alternative modeling framework by employing quantum-inspired mathematical principles—including superposition, entanglement, and interference—to describe complex neural interactions and their temporal evolution. This paper investigates the potential of quantum-inspired simulation techniques to model brain network dynamics associated with psychological disorders such as depression, anxiety, schizophrenia, and neurodevelopmental conditions. By representing neural systems as probabilistic networks capable of occupying multiple functional states simultaneously, quantum-based models provide a powerful means of capturing cognitive variability, network instability, and pathological state transitions. Drawing on insights from neuroscience, quantum cognition, and computational psychiatry, the study highlights how quantum-inspired simulations may contribute to improved mechanistic understanding, predictive modeling, and personalized approaches to mental health treatment.