Campus Units
Statistics
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
12-2013
Journal or Book Title
Stat
Volume
2
Issue
1
First Page
303
Last Page
316
DOI
10.1002/sta4.34
Abstract
It is well known that Gaussian modelling of functional magnetic resonance imaging (fMRI) magnitude time-course data, which are truly Rice distributed, constitutes an approximation, especially at low signal-to-noise ratios (SNRs). Based on this fact, previous work has argued that Rice-based activation tests show superior performance over their Gaussian-based counterparts at low SNRs and should be preferred in spite of the attendant additional computational and estimation burden. Here, we revisit these past studies and, after identifying and removing their underlying limiting assumptions and approximations, provide a more comprehensive comparison. Our experimental evaluations using Receiver Operating Characteristic (ROC) curve methodology show that tests derived using Ricean modelling are substantially superior over the Gaussian-based activation tests only for SNRs below 0.6, that is, SNR values far lower than those encountered in fMRI as currently practiced
Copyright Owner
John Wiley & Sons, Ltd.
Copyright Date
2013
Language
en
File Format
application/pdf
Recommended Citation
Adrian, Daniel W.; Maitra, Ranjan; and Rowe, Daniel B., "Ricean over Gaussian modelling in magnitude fMRI analysis—added complexity with negligible practical benefits" (2013). Statistics Publications. 77.
https://lib.dr.iastate.edu/stat_las_pubs/77
Comments
This is the peer reviewed version of the following article: Stat 2 (2013): 303, doi: 10.1002/sta4.34, which has been published in final form at http://dx.doi.org/10.1002/sta4.34. This article may be used for non-commerical purposes in accordance with Wiley Terms and Conditions for self-archiving