Does Parametric fMRI Analysis with SPM Yield Valid Results? - An Empirical Study of 1484 Rest Datasets
2012 (English)In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 61, no 3, 565-578 p.Article in journal (Refereed) Published
The validity of parametric functional magnetic resonance imaging (fMRI) analysis has only been reported for simulated data.Recent advances in computer science and data sharing make it possible to analyze large amounts of real fMRI data. In this study,1484 rest datasets have been analyzed in SPM8, to estimate true familywise error rates. For a familywise significance threshold of5%, significant activity was found in 1% - 70% of the 1484 rest datasets, depending on repetition time, paradigm and parametersettings. This means that parametric significance thresholds in SPM both can be conservative or very liberal. The main reason forthe high familywise error rates seems to be that the global AR(1) auto correlation correction in SPM fails to model the spectra ofthe residuals, especially for short repetition times. The findings that are reported in this study cannot be generalized to parametricfMRI analysis in general, other software packages may give different results. By using the computational power of the graphicsprocessing unit (GPU), the 1484 rest datasets were also analyzed with a random permutation test. Significant activity was thenfound in 1% - 19% of the datasets. These findings speak to the need for a better model of temporal correlations in fMRI timeseries.
Place, publisher, year, edition, pages
Elsevier, 2012. Vol. 61, no 3, 565-578 p.
Functional magnetic resonance imaging (fMRI), Familywise error rate, Random field theory, Non-parametric statistics, Random permutation test, Graphics processing unit (GPU)
National CategoryEngineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-76118DOI: 10.1016/j.neuroimage.2012.03.093ISI: 000304729800006PubMedID: 22507229OAI: oai:DiVA.org:liu-76118DiVA: diva2:512488
funding agencies|Linnaeus Center CADICS||Swedish Research Council||Neuroeconomic research group at Linkoping University||GPU hardware||2012-03-282012-03-282014-04-25Bibliographically approved