%0 Journal Article %1 doi:10.1073/pnas.1602413113 %A Eklund, Anders %A Nichols, Thomas E. %A Knuttson, Hans %D 2016 %J Proceedings of the National Academy of Sciences %K cognitive_neuroscience fmri neuroscience %N 28 %P 7900-7905 %R 10.1073/pnas.1602413113 %T Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates %U https://www.pnas.org/doi/abs/10.1073/pnas.1602413113 %V 113 %X Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated using real data. Here, we used resting-state fMRI data from 499 healthy controls to conduct 3 million task group analyses. Using this null data with different experimental designs, we estimate the incidence of significant results. In theory, we should find 5% false positives (for a significance threshold of 5%), but instead we found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of a number of fMRI studies and may have a large impact on the interpretation of weakly significant neuroimaging results.

@article{doi:10.1073/pnas.1602413113, abstract = {Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated using real data. Here, we used resting-state fMRI data from 499 healthy controls to conduct 3 million task group analyses. Using this null data with different experimental designs, we estimate the incidence of significant results. In theory, we should find 5% false positives (for a significance threshold of 5%), but instead we found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of a number of fMRI studies and may have a large impact on the interpretation of weakly significant neuroimaging results.}, added-at = {2024-08-13T19:31:07.000+0200}, author = {Eklund, Anders and Nichols, Thomas E. and Knuttson, Hans}, biburl = {https://www.bibsonomy.org/bibtex/2cad56ef41540b503da547e64df7f9b38/alupiani}, doi = {10.1073/pnas.1602413113}, eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.1603113}, interhash = {1e6428c3130fdc96a98923f47712b91e}, intrahash = {cad56ef41540b503da547e64df7f9b38}, journal = {Proceedings of the National Academy of Sciences}, keywords = {cognitive_neuroscience fmri neuroscience}, number = 28, pages = {7900-7905}, timestamp = {2024-08-13T19:31:07.000+0200}, title = {Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates}, url = {https://www.pnas.org/doi/abs/10.1073/pnas.1602413113}, volume = 113, year = 2016 }