The effect of using group-averaged or individualized brain parcellations when investigating connectome dysfunction in psychosis

Functional magnetic resonance imaging (fMRI) is widely used to investigate functional coupling (FC) disturbances in a range of clinical disorders. Most analyses performed to date have used group-based parcellations for defining regions of interest (ROIs), in which a single parcellation is applied to each brain. This approach neglects individual differences in brain functional organization and may inaccurately delineate the true borders of functional regions. These inaccuracies could inflate or underestimate group differences in case-control analyses. We investigated how individual differences in brain organization influence group comparisons of FC using psychosis as a case study, drawing on fMRI data in 121 early psychosis patients and 57 controls. We defined FC networks using either a group-based parcellation or an individually tailored variant of the same parcellation. Individualized parcellations yielded more functionally homogeneous ROIs than did group-based parcellations. At the level of individual connections, case-control FC differences were widespread, but the group-based parcellation identified approximately 7.7% more connections as dysfunctional than the individualized parcellation. When considering differences at the level of functional networks, the results from both parcellations converged. Our results suggest that a substantial fraction of dysconnectivity previously observed in psychosis may be driven by the parcellation method, rather than by a pathophysiological process related to psychosis. Functional magnetic resonance imaging is widely used to map how brain network dysfunction is affected by diverse diseases. A fundamental step in this work involved defining specific brain regions, which act as network nodes in the analysis. Most research to date has used a one-size-fits-all approach, defining such regions on a template brain that is then applied to individual people, which neglects the potential for variability in regional borders and brain organization. Here, we show that using an individualized approach to region definition results in more valid area definitions and more conservative estimates of brain network dysfunction in people with psychosis, indicating that at least some of the group differences reported in the extant literature may be due to differences in regional definitions rather than a consequence of the illness itself.