The cognitive neuropsychiatry of prediction systems in psychosis

While psychotic disorders such as schizophrenia represent a significant clinical burden for the individual and large costs for the society, not much is known about the underlying causes.

The effort to explain psychotic disorders must include an information processing level since subjective experiences and thoughts are fundamentally altered. We have suggested that there is an unstable low-level information processing in psychosis.

In order to compensate for such noise, overly strong top-down influence from prefrontal circuits are recruited and may cause psychotic symptoms like delusions. In the present project we test our hypotheses using a multi-imaging approach.

We will perform dynamic network analyses, i.e. connectomics, in MRI-datasets on psychosis patients, and associated phenotypes, with a focus on alterations in prefrontal circuits.

We will relate our results to longitudinal behavioral outcomes and treatment effects as well as genetic risk and synaptic density (measured with PET).

The results will probe whether these measurements can be used in future precision medicine for clinical assessment of patients.

We will also perform task-based functional imaging studies (fMRI and MEG) of psychosis patients to study belief formation dependent on prefrontal cortex, and test causality of these circuits with brain stimulation in non-patients.

The project also supports core costs of several ongoing clinical projects such as Karolinska Schizophrenia Project (KaSP).