Undoubtedly, mental disorders can be counted amongst the most complex objects of scientific inquiry, which is not only a result of their multi-level casual hierarchy, mostly consisting of several to dozens of intrinsic and extrinsic factors, but also some very intricate criteria of diagnosis. It is nearly impossible to apply typological thinking to them, due to the fact that they form wide spectra of manifestations defeating any attempt to classify them as a discrete entity with a well-defined set of constituent symptoms. For the abovementioned reasons, until recently, the science of psychopathology lacked any serious candidate for a unifying theoretical framework able to offer, at least, some draft explanation of the mental disorders’ ultimate causes.

Indubitably, understanding mental disorders in terms of their proximate (i.e. mechanistic, neurobiological) causes is of great importance for both science and practice of medicine but offers no valuable answer to questions regarding the emergence of a certain disorder in a population.  To answer such a question one must delve deeply into the evolutionary biology and reframe the research perspective. Unsurprisingly, both populational and phylogenetical approach shed new light on the origin of mental disorders, describing them as unavoidable failures of complex systems.

The fruitful union of computational biology and psychopathology aims to use computational modelling for the sake of creating the unified large-scale picture of mental disorders. According to so-called null-hypothesis, any sufficiently complex process influenced by, at least, several genetic and environmental factors, each of which in a highly variable manner, will be manifested as a broad spectrum of phenotypes, described roughly by the bell-shaped curve. In other words, this model predicts that abnormal cognition and behavior occurs in any population of organisms by default and needs no special explanation at all. Low-frequency abnormalities (around 1%-3%) are the natural result of high variability of a functional phenotype. Bipolar disorder, schizophrenia and autism, all fall into this category.

Other interesting model includes viewing mental disorders as the by-product of the bodily behavioral defense system. Computational models of the human immune system provide some promising preliminary results about the possible costs and benefits of supplementing the innate and adaptive immunity with a set of non-specific avoidance mechanisms based on the smoke-detector principle. It can be applied to better understand specific phobias and OCD (Obsessive-Compulsive Disorder), to name just a few examples.

Some mental disorders can also be modelled as diseases of homeostasis and mismatch, resulting from the dysregulation of set points, which were primarily adjusted by natural selection to match the ancestral environment, where daily tribulations were radically different from the challenges of modern life. Interesting examples being depression and some eating disorders.

1) Giudice, M., (2018), Evolutionary Psychopathology. A Unified Approach.

2) Érdi, P., Bhattacharya, B., Cochran, A. (2017), Computational Neurology and Psychiatry.

3) Wallace, R. (2017), Computational Psychiatry. A Systems Biology Approach to the Epigenetics of Mental Disorders.

4) Shackelford, T.K., Zeigler-Hill, V., (2017), The Evolution of Psychopathology.

5) Brune, M., (2016), Textbook of Evolutionary Psychiatry and Psychosomatic Medicine. The Origins of Psychopathology.