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

Abstract 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.


The effects of variation in parcel size
) = 4.68,  = 0.032).Panel c shows homogeneity scores for every parcel for group-based and individualized parcellation.Light colored parcels in d represent parcels showing significant difference in homogeneity scores, between parcellation approaches, for   < 0.05.Homogeneity is displayed in inflated surfaces with the group-based parcellation.e The distribution of the Pearson's coefficient of correlation comparing FC matrices derived from group-based and individualized parcellation.Matrices were positively correlated and ranged between 0.637 and 0.874 (median = 0.770).f Distributions of -values quantifying FC differences between patients and controls at each edge and for individualized parcellation (() = 0.253(1.28))and for group-based parcellation (() = 0.310(1.48)).The difference between the individualized and group-based parcellations were statistically significant, according to a Wilcoxon Sign Rank Test ( = 3.471,  < 0.0001).g Shift function for the two t-distributions.Each circle represents the difference between each decile of both distributions, as a function of the deciles in group-based distribution and the bars represent the 95% boot-strap confidence interval associated with the difference.

Figure 2 -b
Figure 2 -Spatial and functional properties of group-based vs individualized parcellation,

Figure 3 -b
Figure 3 -Spatial and functional properties of group-based vs individualized parcellation,

Figure 4 -
Figure 4 -Correlation between FC matrices derived from different parcellation

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Figure5-Edge-level regional and network-level case-control FC differences according

Figure 6 -
Figure6-Edge-level regional and network-level case-control FC differences according . Panels a, c and e are based on group parcellation.Panels c and d show the degree of each region in the NBS component for the group and individualized parcellations, respectively.Edges are represented by grey lines.The upper triangle of each matrix in panels e and f shows the total number of NBS component edges (raw counts) falling within and between seven canonical networks.The lower triangles show the same data normalized for network size (normalized counts).Visvisual network; SomMotsomatomotor network; DorsAttndorsal attention network; SalVentAttnsalience/ventral attention network; Contcontrol network; Default -Default Mode Network.

Figure 7 -
Figure 7 -Edge-level regional and network-level case-control FC differences according

Figure 8 -
Figure 8 -Changes in parcels size and its correlation to node degree and edge

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Figure 9 -Changes in parcels size and its correlation to node degree and edge

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Figure 10 -Changes in parcels size and its correlation to node degree and edge

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Figure 11 -Changes in parcels size and its correlation to node degree and edge