Cited by 184Functional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and Applications

Cluster success: fMRI inferences for spatial extent have acceptable false-positive rates.

Slotnick, Scott D.·2017·Cognitive Neuroscience

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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Crossref · 10.1080/17588928.2017.1319350

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  • The gPPI analysis used cluster-level FWE correction with an initial cluster-forming threshold of P < 0.001.

    “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).”

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Authors
Slotnick, S. D.
Affiliations
Boston College (US)
Corresponding author
Slotnick, Scott D.
Venue
Cognitive Neuroscience
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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