Quantifying the Dynamics of Central Systemic Degeneration in Schizophrenia

Abstract

Schizophrenia is a mental condition defined by widespread, complex and inspecific symptoms. This complexity prevented many attempts to provide a simple explanation, a reliable cure or even a neurobiology-based diagnosis. Statistics has been so far the preferred method used in psychiatric research in conjunction with clinical data. However, regression-based analyses are generally limited by reliance upon their linear and static nature and emphasized (depending on the study) either unusually high or unusually low levels of one variable at a time (brain activation, cortisol, dopamine etc). Relatively little research has been conducted to reconcile these discrepancies. We review a recent stress/vulnerability hypothesis of systemic degeneration in schizophrenia. Eased on the biophysics of the stress cascade, schizophrenic symptoms are viewed as an end-stage of a cyclic process: prefrontal-limbic systemic degeneration as triggered by environmental stress acting on a pre-existing vulnerability, so that the prefrontal-limbic system can be considered a quantifiable dynamical system evolving under external perturbations. We propose that a nonlinear systems analysis could best address the complex mechanisms of the disease. While dynamics has already successfully addressed regulation of various somatic systems, psychiatry has only started using similar methods to understand mental disorders as complex nonlinear systems. Recent imaging and bioengineering technologies are promoting a fresh research trend, and concepts of nonlinear dynamics (chaos, fractality or bifurcation theory) are now considered a suitable framework for describing the temporal architecture of the brain. We review some of our dynamical approaches to prefrontal-limbic degeneration in schizophrenia, including theoretical modeling and collaborative work with imaging time series from schizophrenia patients. We describe how a latent predisposition can remain dormant until a triggering event activates a threshold in the dynamics of the system (with each individual's vulnerability setting the threshold level) moving it into an unstable regime. Pharmacological treatment can be used to provide external inhibitory control over the system, but the intrinsic dynamics quite possibly remains in the unstable regime and is more prone to relapses. We finally discuss this work's overreaching goal: developing a neurophysiology-based quantitative chart of brain architecture profiling, usable by clinicians to complement the current behavior-based DSM diagnostic methods.