Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates
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Summary
It is found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%.
- Type
- article
- Published
- 2015-11-05
- Cited by
- 3,350
- References
- 61
- Access
- Open access
- OpenAlex
- https://openalex.org/W2134305330
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4875801
Keywords
Inference, Parametric statistics, Computer science, Permutation (music), Voxel
References
- Organization for Human Brain Mapping（OHBM）2010の報告
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- Multilevel linear modelling for FMRI group analysis using Bayesian inference
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- BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs
- Improved Assessment of Significant Activation in Functional Magnetic Resonance Imaging (fMRI): Use of a Cluster‐Size Threshold
- Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference
- Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging.
- Adjusting the effect of nonstationarity in cluster-based and TFCE inference
- Making big data open: data sharing in neuroimaging
- The secret lives of experiments: Methods reporting in the fMRI literature
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