YinYang Dynamic Neurobioological Modeling and Diagnostic Analysis of Major Depressive and Bipolar DisordersIEEE Transactions on Biomedical Engineering
AbstractSince millions suffer from major depressive and bipolar disorders, the modeling, characterization, classification, and diagnostic analysis of such mental disorders bear great significance in medical and pharmaceutical research. Yin Yang bipolar sets are introduced for neurobiological modeling and diagnostic analysis of such disorders. It is shown that bipolar sets and a bipolar dynamic modus ponens (BDMP) build a technological bridge from a linear, static, and closed world to a nonlinear, dynamic, and open world of equilibria, quasi-equilibria, or nonequilibria and provide a novel model for bipolar neurobiological diagnostic analysis with added rigor to the current standard. It is shown that bipolar inference can help in understanding both the classic manifestations and the counterintuitive symptoms of bipolar disorders with applications in clinical psychopharmacology. Mathematical and visual characterizations of core features of such disorders are presented. A unified diagnosis and outcome model of different treatments are presented for different types of bipolar disorders. The significance and novelty of this work is twofold: 1) it introduces YinYang into biomedicine for the understanding of certain neurobiological disorders and fosters a new standard model for clinical, therapeutic, and pharmacological research and applications; 2) it presents a mathematical basis for the characterization of mood regulation in individuals and/or a cohort of patients with applications in biomedical engineering and potential applications in nanotechnologies for integrated care of major depressive and bipolar disorders.
Citation InformationWen-Rang Zhang, A. K. Pandurangi and Karl E. Peace. "YinYang Dynamic Neurobioological Modeling and Diagnostic Analysis of Major Depressive and Bipolar Disorders" IEEE Transactions on Biomedical Engineering Vol. 54 Iss. 10 (2007) p. 1729 - 1738
Available at: http://works.bepress.com/wen-ran_zhang/38/