Using Computational Psychiatry to Rule Out the Hidden Causes of Depression

Abstract

In an ideal world, our understanding of the causes of psychiatric disorders would progress by testing mechanistic hypotheses in experimental studies, using the results of these studies to identify situations in which the hypotheses fail and then refining, or even discarding, the hypotheses in response to these failures. The reality has been somewhat less Popperian—mechanistic hypotheses in psychiatry tend to drift slowly out of fashion as attention moves to the next big thing, rather than because they have been disproved. We are rarely presented with strong negative results that challenge the currently dominant mechanistic account. Given that negative results are an essential corrective to the scientific process, why are they so rarely found in the mechanistic literature?