Analysis of family‐wise error rates in statistical parametric mapping using random field theory

• Published in: Human brain mapping Vol. 40; no. 7; pp. 2052 - 2054
• Main Authors: Flandin, Guillaume, Friston, Karl J.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.05.2019; John Wiley and Sons Inc
• Subjects: Brain; Brain - diagnostic imaging; Brain - physiology; Brain mapping; Brain Mapping - methods; Brain Mapping - statistics & numerical data; Data Interpretation, Statistical; Error analysis; family‐wise error rate; Field theory; Fields (mathematics); Humans; Image processing; Magnetic Resonance Imaging - methods; Magnetic Resonance Imaging - statistics & numerical data; Mapping; Medical imaging; Neuroimaging; Neurology; Quantum theory; random field theory; Special Section: On the Topic of Cluster Failure; statistical parametric mapping; Statistics; topological inference; topological inference; family-wise error rate; random field theory; statistical parametric mapping
• ISSN: 1065-9471; 1097-0193
• DOI: 10.1002/hbm.23839

This technical report revisits the analysis of family‐wise error rates in statistical parametric mapping—using random field theory—reported in (Eklund et al. []: arXiv 1511.01863). Contrary to the understandable spin that these sorts of analyses attract, a review of their results suggests that they endorse the use of parametric assumptions—and random field theory—in the analysis of functional neuroimaging data. We briefly rehearse the advantages parametric analyses offer over nonparametric alternatives and then unpack the implications of (Eklund et al. []: arXiv 1511.01863) for parametric procedures. Hum Brain Mapp, 40:2052–2054, 2019. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.