Generating surrogate brain maps through random rotation of geometric eigenmodes

COEX 

The brain expresses activity in complex spatiotemporal patterns, reflecting cytoarchitectural and genetic influences that possess specific spatial properties. These brain patterns, also known as brain maps, frequently have high smoothness and spatial organization, i.e., spatial autocorrelation (SA), reflecting its central position in modern neuroimaging analyses [1–6]. In regimes of high SA, correlation between two brain maps can be spuriously elevated leading to false positive associations. An appropriate null hypothesis test to exclude false positives requires surrogate brain maps that preserve SA. Here we introduce "eigenstrapping", a technique for generating null hypotheses for maps possessing SA. This method uses geometric eigenmodes derived from various surfaces to produce surrogate brain maps that preserve SA. We show that these surrogate maps appropriately represent the null distribution and control false positives for cortical maps with SA, providing a versatile approach for investigations of cortical and subcortical topography.