Modeling the symptoms of psychopathology: A pluralistic approach

Abstract

Our understanding of mental disorders has traditionally focused on syndromes and symptom clusters rather than on the nature of the symptom and signs themselves. Using a core symptom of depression, anhedonia, as an extended example, this paper illustrates how the development of multiple models of symptoms, at various scales of analysis, may advance the explanation and classification of mental disorders. We begin by outlining the Phenomena Detection Method (PDM), which links different phases of the inquiry process to provide a methodology for conceptualizing the symptoms of psychopathology and for constructing multi-level models of the pathological processes that comprise them. Next, we apply the PDM to anhedonia, building a compositional explanation of this core symptom by way of multiple models across four scales (levels): molecular, neural, cognitive, and phenomenological. Finally, we evaluate our approach in comparison to existing strategies for understanding mental disorders.