The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Nonstationary cluster-size inference with random field and permutation methods
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Citations
Cites
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
Nonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256
Self-citationFunctional neuroanatomy of emotion: A meta-analysis of emotion activation studies in PET and fMRI
Phan, K. L., Wager, T., Taylor, S. F., & Liberzon, I. (2002) · NeuroImage · doi:10.1006/nimg.2002.1087 · Cited by 3,502
Self-citationForman, S. D., Cohen, J. D., Fitzgerald, M., Eddy, W. F., Mintun, M. A., & Noll, D. C. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910330508 · Cited by 3,202
Detecting activations in PET and fMRI: levels of inference and power
Friston, K. J., Holmes, A., Poline, J.-B., Price, C. J., & Frith, C. D. (1996) · NeuroImage · doi:10.1006/nimg.1996.0074 · Cited by 1,148 · cited 2×
“(1994), have been widely used in such investigations because of increased sensitivity to spatially extended signals, compared to voxel-intensity tests (Friston et al., 1996; Poline et al., 1997).”
Background
Cited by
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
Self-citationPermutation inference for the general linear model
Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.060 · Cited by 3,563
Self-citationCluster-extent based thresholding in fMRI analyses: Pitfalls and recommendations
Woo, C.-W., Krishnan, A., & Wager, T. D. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.058 · Cited by 1,253
Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data
Hagler, D. J., Saygin, A. P., & Sereno, M. I. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.07.036 · Cited by 752
Quantifying and exploring camouflaging in men and women with autism
Lai, M.-C., Lombardo, M. V., Ruigrok, A. N., Chakrabarti, B., Auyeung, B., Szatmari, P., Happé, F., Baron-Cohen, S., & MRC AIMS Consortium (2017) · Autism · doi:10.1177/1362361316671012 · Cited by 705
Metadata
- Authors
- Hayasaka, S., Phan, K. L., Liberzon, I., Worsley, K. J., & Nichols, T. E.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2004-06
- Volume
- 22
- Issue
- 2
- Pages
- 676-687
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1988193785
- Cited by
- 661
- References
- 5
- FWCI
- 3.36
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Nonstationary cluster-size inference with random field and permutation methods. https://app.cochat.ai/papers/10.1016/j.neuroimage.2004.01.041
- The paper
- Hayasaka, S., Phan, K. L., Liberzon, I., Worsley, K. J., & Nichols, T. E. (2004). Nonstationary cluster-size inference with random field and permutation methods. NeuroImage. https://doi.org/10.1016/j.neuroimage.2004.01.041
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
