Simulation of mental disorders: I. concepts, challenges and animal models

The complexity of the human brain and the difficulties in identifying and dissecting the biological, social and contextual underpinnings of mental functions confound the study of the etiology and pathophysiology of mental disorders. Large-scale computer simulation of the human brain was recently proposed as a method to circumvent some of these difficulties. In this two-part paper, we discuss selected conceptual and pragmatic issues pertaining to the mental illness simulation in general and computer simulation in particular. We address the merits and limitations of two generic types of simulation vehicles, biological simulation in animal models (Part I) and virtual simulation in computer models (Part II), in the study of mental disorders in humans. We point to the need to tailor the vehicle and method of simulation to the goal of the simulation, and suggest future directions for maximizing the utility of mental illness simulation. We argue that at the current state of knowledge, the biological-phenomenological gap in understanding mental disorders markedly limits the ability to generate high-fidelity biological and computational models of mental illness. Simulation focusing on limited realistic objectives, such as mimicking selected distinct biological and phenomenological attributes of specific mental symptoms, may however serve as a useful tool in exploring mental disorders.