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

Detecting changes in nonisotropic images.

K J Worsley1, M Andermann, T Koulis

  • 1Department of Mathematics and Statistics, McGill University, Montreal, Québec, Canada. worsley@math.mcgill.ca

Human Brain Mapping
|October 19, 1999
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

Crystallization of ApoA1 and ApoE4 nanolipoprotein particles and initial XFEL-based structural studies.

Crystals·2022
Same author

A voxel-wise assessment of growth differences in infants developing autism spectrum disorder.

NeuroImage. Clinical·2021
Same author

A fixed-target platform for serial femtosecond crystallography in a hydrated environment.

IUCrJ·2020
Same author

Reducing off target viral delivery in ovarian cancer gene therapy using a protease-activated AAV2 vector platform.

Journal of controlled release : official journal of the Controlled Release Society·2019
Same author

On farm factors increasing dark cutting in pasture finished beef cattle.

Meat science·2018
Same author

Indices of repetitive behaviour are correlated with patterns of intrinsic functional connectivity in youth with autism spectrum disorder.

Brain research·2018

Statistical parametric mapping (SPM) using random field theory is invalid for nonisotropic image data. A novel method corrects P values by assuming data can be statistically warped to an isotropic space, ensuring validity without explicit warping.

Area of Science:

  • Neuroimaging analysis
  • Statistical modeling
  • Computational anatomy

Background:

  • Random field theory (RFT) for statistical parametric mapping (SPM) assumes isotropic image noise.
  • Nonisotropic noise, common in projected cortical surface data and anatomical images, violates RFT assumptions.
  • Existing RFT methods are therefore invalid for analyzing complex neuroimaging datasets.

Purpose of the Study:

  • To develop a statistically valid method for P value calculation in nonisotropic neuroimaging data.
  • To address the limitations of random field theory in the presence of nonconstant smoothness.
  • To provide a robust approach for analyzing projected cortical surface data and anatomical images.

Main Methods:

  • Proposed a theoretical framework assuming image data can be statistically warped into an isotropic space.

Related Experiment Videos

  • Developed a method to correct P values for local maxima and suprathreshold cluster sizes under nonisotropic conditions.
  • The method relies on the existence of a statistical warping, not the explicit computation of the warping itself.

    • Main Results:

    • The proposed method provides corrected P values that are valid even when the underlying image data is nonisotropic.
    • This approach circumvents the need to explicitly compute the statistical warping, simplifying application.
    • Ensures the reliability of statistical inference in neuroimaging studies with complex data structures.

    Conclusions:

    • The theoretical framework enables valid statistical inference for nonisotropic neuroimaging data, overcoming RFT limitations.
    • This method is applicable to projected cortical surface data, anatomical images, and other nonisotropic datasets.
    • Offers a significant advancement for accurate statistical analysis in neuroimaging research.