Jumping to conclusions: a network model predicts schizophrenic patients' performance on a probabilistic reasoning task.

This article extends computational models of schizophrenia that focus on the negative aspects of this syndrome to behavioral biases that are associated with a positive symptom of schizophrenia, namely delusions. The phenomenon studied is the "jump-to-conclusions" style of reasoning that is characterized by delusional patients--in comparison with controls--whereby they make less-informed decisions when an option to collect more decision-specific information is available. Simulations show that these differences can be mimicked by modulating the gain parameter-associated with variations in dopamine level-in a simple network model.