Development of Cerebellar-Cortical Functional Connectivity in Youth and Its Prediction of Psychosis

Abstract Cerebellum dysfunction is known to be strongly implicated in the pathogenesis of psychosis. Our past research has provided converging evidence that functional dysconnectivity in the cerebellar-cortical circuitry is a robust neural anomaly that is ubiquitously manifest across different clinical stages and brain states in psychotic patients, predictive of psychosis onset, and related to genetic risk for psychosis. Therefore, cerebellar-cortical dysconnectivity is likely to reflect a pathological trait arising from abnormal neurodevelopment, emphasizing the importance of understanding the developmental trajectories of cerebellar-cortical connectivity and their associations with psychosis. To this end, we will utilize data from four large neurodevelopment datasets with resting-state fMRI scans and extensive clinical and cognitive assessments, including the Lifespan Human Connectome Project in Development (HCP-D), the Philadelphia Neurodevelopmental Cohort (PNC), the North American Prodrome Longitudinal Study Phase 3 (NAPLS-3) and NAPLS Phase 2 (NAPLS-2), with a total of > 3000 individuals from 5 to 21 years old. We will use the HCP-D dataset as the benchmark to chart normal development curves of cerebellar-cortical connectivity from childhood to early adulthood, and use the PNC dataset to comprehensively investigate how deviations from these normative curves predict psychotic-like symptoms and cognitive disturbances during neurodevelopment. The results will be summarized into individualized “cerebellar risk scores” and used for prediction of psychosis onset in the NAPLS-3 and NAPLS-2 datasets. Overall, the outcomes from this study will 1) provide detailed insights into the developmental patterns of cerebellar-cortical connectivity in typically and atypically developed youth; 2) bridge the gap between systems-level cerebellar dysfunction and its cognitive and symptom correlates during neurodevelopment; and 3) generate an individualized, generalizable, cerebellum-based risk score that can be leveraged for future psychosis prediction and early intervention studies.