Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Nonparametric permutation tests for functional neuroimaging: a primer with examples.

Thomas E Nichols1, Andrew P Holmes

  • 1Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Human Brain Mapping
|December 18, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

FEMA-Long: Modeling unstructured covariances for discovery of time-dependent effects in large-scale longitudinal datasets.

PLoS genetics·2026
Same author

Leveraging STRAW +10 criteria to evaluate menopause stage effects on sleep quality.

Climacteric : the journal of the International Menopause Society·2026
Same author

Widespread use of invalid statistical tests in biomedical machine learning.

bioRxiv : the preprint server for biology·2026
Same author

Scalable Bayesian Image-on-Scalar Regression for Population-Scale Neuroimaging Data Analysis.

Journal of the American Statistical Association·2026
Same author

A titin truncating variant linked to atrial fibrillation increases atrial profibrotic signalling and cholinergic sensitivity.

Cardiovascular research·2026
Same author

Convergent and divergent brain-cognition development in early adolescence.

Nature communications·2026
Same journal

Injury Severity Influences Long-Term Cognitive Control in Pediatric "Mild" Traumatic Brain Injury.

Human brain mapping·2026
Same journal

Early Adulthood Signatures of Motherhood in Brain Aging.

Human brain mapping·2026
Same journal

Neural Markers of Interocular Grouping During Binocular Rivalry With MEG.

Human brain mapping·2026
Same journal

Neural Correlates of Explicit Outcome Expectation Effects: An Activation Likelihood Estimation Meta-Analysis.

Human brain mapping·2026
Same journal

Benchmarking fMRI Denoising Pipelines.

Human brain mapping·2026
Same journal

Modeled Long-Term Effects of Psilocybin on Dynamic Activity and Effective Connectivity of Fronto-Striatal-Thalamic Circuits.

Human brain mapping·2026
See all related articles

Nonparametric permutation testing offers a flexible statistical analysis for neuroimaging, effectively handling multiple comparisons. This method can validate parametric approaches, especially in low-degree-of-freedom analyses.

Area of Science:

  • Neuroimaging
  • Statistics
  • Computational Neuroscience

Background:

  • Nonparametric permutation testing is a flexible statistical method for functional neuroimaging data analysis.
  • It addresses the multiple comparisons problem inherent in voxel-by-voxel hypothesis testing.
  • Existing methods like Statistical Parametric Mapping (SPM) with random field theory are common but may have limitations.

Purpose of the Study:

  • To provide an accessible explication of nonparametric permutation testing for functional neuroimaging.
  • To introduce freely distributed MATLAB software for implementing these techniques.
  • To demonstrate the application and advantages of permutation testing in neuroimaging.

Main Methods:

  • Nonparametric permutation testing applied to functional neuroimaging data.

Related Experiment Videos

  • Accounting for multiple comparisons using permutation-based extensions.
  • Utilizing a locally pooled variance estimate for analyses with low degrees of freedom.
  • Comparison with Statistical Parametric Mapping (SPM) and random field theory.

    • Main Results:

    • Permutation testing provides valid statistical analysis with minimal assumptions.
    • It yields results comparable to parametric approaches like SPM under ideal conditions.
    • The nonparametric approach can outperform SPM in low-degree-of-freedom scenarios (e.g., single-subject PET/SPECT, population fMRI).
    • The method serves to verify the validity of computationally cheaper parametric methods.

    Conclusions:

    • Nonparametric permutation testing is a powerful and flexible tool for functional neuroimaging.
    • Accessible explication and software facilitate practical application of these techniques.
    • Permutation testing offers a valuable alternative and validation method for neuroimaging statistical analysis, particularly in specific experimental designs.