The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Cluster success: fMRI inferences for spatial extent have acceptable false-positive rates.
Abstract
In an editorial (this issue), I argued that Eklund, Nichols, and Knutsson's 'null data' reflected resting-state/default network activity that inflated their false-positive rates. Commentaries on that paper were received by Nichols, Eklund, and Knutsson (this issue), Hopfinger (this issue), and Cunningham and Koscik (this issue). In this author response, I consider these commentaries. Many issues stemming from Nichols et al. are identified including: (1) Nichols et al. did not provide convincing arguments that resting-state fMRI data reflect null data. (2) Eklund et al. presented one-sample t-test results in the main body of their paper showing that their permutation method was acceptable, while their supplementary results showed that this method produced false-positive rates that were similar to other methods. (3) Eklund et al. used the same event protocol for all the participants, which artifactually inflated the one-sample t-test false-positive rates. (4) At p < .001, using two-sample t-tests (which corrected for the flawed analysis), all the methods employed to correct for multiple comparisons had acceptable false-positive rates. (5) Eklund et al. contrasted resting-state periods, which produced many significant clusters of activity, while null data should arguably be associated with few, if any, significant activations. Eklund et al.'s entire set of results show that commonly employed methods to correct for multiple comparisons have acceptable false-positive rates. Following Hopfinger along with Cunningham and Koscik, it is also highlighted that rather than focusing on only type I error, type I error and type II error should be balanced in fMRI analysis.
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“thresholded at P < 0.05, FWE-corrected at the cluster level. In line with recent recommendations for the control of false-positives in cluster-based correction approaches an initial cluster forming threshold of P < 0.001 was applied to data with a resolution of 3 × 3 × 3 mm (Eklund et al., 2016; Slotnick, 2017).”
From Oxytocin Enhancement of Emotional Empathy: Generalization Across Cultures and Effects on Amygdala Activity (2018) · cites this paper as Slotnick, 2017
Citations
Cites
Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates
Eklund, A., Nichols, T. E., & Knutsson, H. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1602413113 · Cited by 3,487
Scanning the horizon: towards transparent and reproducible neuroimaging research
Poldrack, R. A., Baker, C. I., Durnez, J., Gorgolewski, K. J., Matthews, P. M., Munafò, M. R., Nichols, T. E., Poline, J.-B., Vul, E., & Yarkoni, T. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.167 · Cited by 1,410
Type I and Type II error concerns in fMRI research: re-balancing the scale
Lieberman, M. D., & Cunningham, W. A. (2009) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsp052 · Cited by 1,342
Analysis of family‐wise error rates in statistical parametric mapping using random field theory
Flandin, G., & Friston, K. J. (2017) · Human Brain Mapping · doi:10.1002/hbm.23839 · Cited by 232
Low-Frequency Fluctuations of the Resting Brain: High Magnitude Does Not Equal High Reliability
Mao, D., Ding, Z., Jia, W., Liao, W., Li, X., Huang, H., Yuan, J., Zang, Y., & Zhang, H. (2015) · PLoS ONE · doi:10.1371/journal.pone.0128117 · Cited by 30
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- Cox R. W., Brain Connectivity
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On testing for spatial correspondence between maps of human brain structure and function
Alexander-Bloch, A. F., Shou, H., Liu, S., Satterthwaite, T. D., Glahn, D. C., Shinohara, R. T., Vandekar, S. N., & Raznahan, A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.070 · Cited by 947
Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease
Siddiqi, S. H., Schaper, F. L. W. V. J., Horn, A., Hsu, J., Padmanabhan, J. L., Brodtmann, A., Cash, R. F. H., Corbetta, M., Choi, K. S., Dougherty, D. D., et al. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01161-1 · Cited by 296
Siddiqi, S. H., Trapp, N. T., Hacker, C. D., Laumann, T. O., Kandala, S., Hong, X., Trillo, L., Shahim, P., Leuthardt, E. C., Carter, A. R., et al. (2019) · Journal of Neurotrauma · doi:10.1089/neu.2018.5889 · Cited by 106
Beaty, R. E., Chen, Q., Christensen, A. P., Kenett, Y. N., Silvia, P. J., Benedek, M., & Schacter, D. L. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116499 · Cited by 108
Eklund, A., Knutsson, H., & Nichols, T. E. (2019) · Human Brain Mapping · doi:10.1002/hbm.24350 · Cited by 82
Metadata
- Authors
- Slotnick, S. D.
- Affiliations
- Boston College (US)
- Corresponding author
- Slotnick, Scott D.
- ORCID
- Slotnick, Scott D.
- Venue
- Cognitive Neuroscience
- Publisher
- Informa UK Limited
- Published
- 2017-04-19
- Volume
- 8
- Issue
- 3
- Pages
- 150-155
- ISSN
- 1758-8928 (ISSN-L)
- 1758-8936
- OpenAlex
- W2607103049
- Cited by
- 184
- References
- 5
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 7 · 2023: 13 · 2022: 26 · 2021: 22 · 2020: 19 · 2019: 50 · 2018: 28 · 2017: 1
- FWCI
- 15.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cognitive Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- false positive rate, multiple testing correction, resting-state fMRI, permutation methods, one-sample t-test, two-sample t-test, default mode network, type I error, type II error
- MeSH terms
- Humans, Magnetic Resonance Imaging
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