Unified univariate and multivariate random field theory
Abstract
We report new random field theory P values for peaks of canonical correlation SPMs for detecting multiple contrasts in a linear model for multivariate image data. This completes results for all types of univariate and multivariate image data analysis. All other known univariate and multivariate random field theory results are now special cases, so these new results present a true unification of all currently known results. As an illustration, we use these results in a deformation-based morphometry (DBM) analysis to look for regions of the brain where vector deformations of nonmissile trauma patients are related to several verbal memory scores, to detect regions of changes in anatomical effective connectivity between the trauma patients and a group of age- and sex-matched controls, and to look for anatomical connectivity in cortical thickness.
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Random field theory was used to correct the resulting t parametric maps for multiple comparisons (one-sided).
“Random field theory46 was used to correct the resulting t parametric maps for multiple comparisons (one-sided).”
From Cerebrospinal fluid p-tau231 as an early indicator of emerging pathology in Alzheimer's disease (2022) · cites this paper as [46]
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References 22 · Cited by 370
- Authors
- Worsley, K. J., Taylor, J. E., Tomaiuolo, F., & Lerch, J.
- Affiliations
- Montreal Neurological Institute and Hospital (CA)
- Stanford University (US)
- Fondazione Santa Lucia (IT)
- Corresponding author
- Worsley, Keith J.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2004-01
- Volume
- 23
- Pages
- S189-S195
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2145714441
- Cited by
- 370
- References
- 22
- Citations by year
- 2026: 6 · 2025: 5 · 2024: 13 · 2023: 18 · 2022: 20 · 2021: 26 · 2020: 20 · 2019: 40 · 2018: 23 · 2017: 9 · 2016: 16 · 2015: 24 · 2014: 13 · 2013: 35 · 2012: 16
- FWCI
- 3.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- random field theory, p-values, canonical correlation analysis, multivariate image analysis, deformation-based morphometry, brain deformation, verbal memory, structural connectivity, cortical thickness, trauma patients
- MeSH terms
- Adult, Algorithms, Analysis of Variance, Brain, Brain Injuries, Cerebral Cortex, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Models, Statistical, Linear Models
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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