Probabilistic association learning in schizophrenia

Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry

Neuroimaging studies have consistently found structural cortical abnormalities in individuals with schizophrenia, especially in structural hubs. However, it is unclear what abnormalities predate psychosis onset and whether abnormalities are related to behavioral performance and symptoms associated with psychosis risk. Using surface-based morphometry, we examined cortical volume, gyrification, and thickness in a psychosis risk group at long-term risk for developing a psychotic disorder (n = 18; i.e., extreme positive schizotypy plus interview-rated attenuated psychotic symptoms [APS]) and control group (n = 19). Overall, the psychosis risk group exhibited cortical abnormalities in multiple structural hub regions, with abnormalities associated with poorer probabilistic category learning, a behavioral measure strongly associated with psychosis risk. For instance, the psychosis risk group had hypogyria in a right posterior midcingulate cortical hub and left superior parietal cortical hub, as well as decreased volume in a right pericalcarine hub. Morphometric measures in all of these regions were also associated with poorer probabilistic category learning. In addition to decreased right pericalcarine volume, the psychosis risk group exhibited a number of other structural abnormalities in visual network structural hub regions, consistent with previous evidence of visual perception deficits in psychosis risk. Further, severity of APS hallucinations, delusional ideation, and suspiciousness/persecutory ideas were associated with gyrification abnormalities, with all domains associated with hypogyria of the right lateral orbitofrontal cortex. Thus, current results suggest that structural abnormalities, especially in structural hubs, are present in psychosis risk and are associated both with poor learning on a psychosis risk-related task and with APS severity.

Probabilistic Category Learning and Striatal Functional Activation in Psychosis Risk

BACKGROUND

Psychosis risk is associated with striatal dysfunction, including a previous behavioral study that found that psychosis risk is associated with impaired performance on a probabilistic category learning task (PCLT; ie, the Weather Prediction Task), a task strongly associated with striatal activation. The current study examined whether psychosis risk based on symptom levels was associated with both poor behavioral performance and task-related physiological dysfunction in specific regions of the striatum while performing the PCLT.

METHODS

There were 2 groups of participants: psychosis risk (n = 21) who had both (a) extreme levels of self-reported psychotic-like beliefs and experiences and (b) interview-rated current attenuated psychotic symptoms (APS); and a comparison group (n = 20) who had average levels of self-reported psychotic-like beliefs and experiences. Participants completed the PCLT during fMRI scanning.

RESULTS

The current research replicated previous work finding behavioral PCLT deficits at the end of the task in psychosis risk. Furthermore, as expected, the psychosis risk group exhibited decreased striatal activation on the task, especially in the associative striatum. The psychosis risk group also displayed decreased activation in a range of cortical regions connected to the associative striatum. In contrast, the psychosis risk group exhibited greater activation predominantly in cortical regions not connected to the associative striatum.

CONCLUSIONS

Psychosis risk was associated with both behavioral and striatal dysfunction during performance on the PCLT, suggesting that behavioral and imaging measures using this task could be a marker for psychosis risk.