NeuroImage
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Randomized Controlled Trial
Determining the optimal level of smoothing in cortical thickness analysis: a hierarchical approach based on sequential statistical thresholding.
The extent of smoothing applied to cortical thickness maps critically influences sensitivity, anatomical precision and resolution of statistical change detection. Theoretically, it could be optimized by increasing the trade-off between vertex-wise sensitivity and specificity across several levels of smoothing. But to date neither parametric nor nonparametric methods are able to control the error at the vertex level if the null hypothesis is rejected after smoothing of cortical thickness maps. ⋯ The hierarchical method was further validated in a cross-sectional study comparing moderate Alzheimer's disease (AD) patients with healthy elderly subjects. Results suggest that the extent of cortical thinning reported in previous AD studies might be artificially inflated by the choice of inadequate smoothing. In these cases, interpretation should be based on the location of local maxima of suprathreshold regions rather than on the spatial extent of the detected signal in the statistical parametric map.