The Thermodynamics of Self: Identity as a Dissipative Structure and Biomarkers of Entropic Rigidity in Psychopathology

Abstract

This theoretical article proposes a novel paradigm for understanding mental health and psychopathology through the lens of non-equilibrium thermodynamics and complex systems theory. It conceptualizes the human ego/self as a psychic dissipative structure—a dynamic, open system that maintains its organization through continuous energy and information exchange, resisting the natural entropic tendency toward disorder. The work presents an integrative model synthesizing: Physics of dissipative structures (Prigogine) Neuroscience of the Default Mode Network (DMN) as the neural substrate of self-narrative Psychoanalytic drive theory reinterpreted thermodynamically (Eros as negentropy, Thanatos as attraction to minimal energy states) Clinical phenomenology of suffering and identity Computational psychiatry approaches Key innovations include: Thermodynamic mapping of psychopathology: A novel 2D coordinate system (Entropy × Free Energy) that classifies mental disorders as pathological attractors in four quadrants: Rigid-Pressurized (e.g., anxiety disorders) Rigid-Exhausted (e.g., melancholic depression) Chaotic-Pressurized (e.g., acute psychosis) Chaotic-Exhausted (e.g., dissociative states) Biomarker proposal: Introduction of Lempel-Ziv Complexity (LZc) as a quantitative measure of "entropic rigidity" for clinical stratification and treatment guidance, particularly for psychedelic therapy safety screening. Personalized intervention framework: Treatment recommendations based on the system's thermodynamic position, advocating for either entropy-increasing (e.g., psychedelics for rigid states) or structure-promoting (e.g., antipsychotics for chaotic states) interventions. The article bridges theoretical physics, neuroscience, and clinical practice, offering a unified model that explains both normal identity maintenance and pathological states through universal thermodynamic principles. It contributes to the emerging field of computational psychiatry while providing practical clinical implications for diagnosis, treatment personalization, and safety assessment in novel interventions.