Peak p-values and false discovery rate inference in neuroimaging.
Neuroimage 2019;
197:402-413. [PMID:
31028923 DOI:
10.1016/j.neuroimage.2019.04.041]
[Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 04/12/2019] [Accepted: 04/14/2019] [Indexed: 11/22/2022] Open
Abstract
Peaks are a mainstay of neuroimage analysis for reporting localization results. The current peak detection procedure in SPM12 requires a pre-threshold for approximating p-values and a false discovery rate (FDR) nominal level for inference. However, the pre-threshold is an undesirable feature, while the FDR level is meaningless if the null hypothesis is not properly defined. This article provides: 1) a peak height distribution for smooth Gaussian error fields, which does not require a screening pre-threshold; 2) a signal-plus-noise model where FDR of peaks can be controlled and properly interpreted. Matlab code for calculation of p-values using the exact peak height distribution is available as an SPM extension.
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