Computational and cognitive approaches for the therapy development in depression

The cognitive model of depression postulates that patients with depression - and people at increased risk - have a negativity bias in attention and memory. The resulting negative interpretation of life experiences and expectancy of negative consequences (catastrophizing) ushers into a circle of negative mood, pessimism and anhedonia. In this model, the dysfunctional cognitive schema, which is caused by a combination of genetic and developmental factors, is a core mechanism of the clinical syndrome and a key target for therapeutic intervention. In this article I discuss the experimental evidence for such dysfunctional schemata especially with regard to negative biases in attention and memory. Computational decision theory can explain how overweighting negative (and underweighting positive) information can lead to behavioural symptoms of depression (psychomotor retardation) and a fundamentally pessimistic outlook. Such a negative bias can hinder healthy emotion regulation and thus establish vulnerability for depression. The increasing understanding of cognitive processes in depression is clinically relevant for the development of early detection tools and forms a basis for the development of new interventions in the fields of computer-based training (for example "cognitive bias modification") and self-regulation of brain activity (neurofeedback).