Computational psychiatry 2.0 and implications for stress research
Stress-related disorders are highly prevalent in modern society and pose significant challenge to humans health. Being recently emerged branch of psychiatry, computational psychiatry is geared toward mathematical modeling of psychiatric disorders. Harnessing power of computer sciences and statistics may bridge the complex nature of psychiatric illnesses with hidden brain computational mechanisms. Stress represents an adaptive response to environmental threats but, while getting chronic, it leads to progressive deflection from homeostasis or result in buildup of allostatic load, providing researches with unique opportunity to track patterns of deviations from adaptive responding toward full-blown disease development. Computational psychiatry toolkit enables us to quantitatively assess the extent of such deviations, to explicitly test competing hypotheses which compare the models with real data for goodness-of-fit and, finally, to tethering these computational operations to structural or functional brain alterations as may be revealed by non-invasive neuroimaging and stimulation techniques.\n\nIt is worth noting that brain does not directly face environmental demands imposed on human or animal, but rather through detecting signals and acting out via bodily systems. Therefore, it is of critical importance to take homeostatic and allostatic mechanisms into account when considering sophisticated interactions between brain and body and how their partnership may result in establishment of stress-susceptible or resilient profiles.\n\nIn this article, with a particulate focus on brain-gut interactions, we outline several possible directions to widen the scope of application of computational approach in mental health care field trying to integrate computational psychiatry, psychosomatics and nutritional medicine