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Robust, unbiased general linear model estimation of phMRI signal amplitude in the presence of variation in the temporal response profile
Author(s) -
Pendse Gautam V.,
Schwarz Adam J.,
Baumgartner Richard,
Coimbra Alexandre,
Upadhyay Jaymin,
Borsook David,
Becerra Lino
Publication year - 2010
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.22180
Subject(s) - amplitude , singular value decomposition , signal (programming language) , computer science , mathematics , statistics , algorithm , physics , quantum mechanics , programming language
Purpose: To determine a simple yet robust method to generate parsimonious design matrices that accurately estimate the “pharmacological MRI” (phMRI) response amplitude in the presence of both confounding signals and variability in temporal profile. Variability in the temporal response profile of phMRI time series data is often observed. If not properly accounted for, this variation can result in inaccurate and unevenly biased signal amplitude estimates when modeled within a general linear model (GLM) framework. Materials and Methods: The approach uses a low‐rank singular value decomposition (SVD) approximation to a set of vectors capturing anticipated variations of no interest around the signal model to generate additional regressors for the design matrix. The method is demonstrated for both plateau and bolus type phMRI response profiles in the presence of variation in signal onset and/or shape, and applied to an in vivo blood oxygenation level‐dependent (BOLD) phMRI study of buprenorphine in healthy human subjects. Results: In general, 2–3 additional regressors, capturing >75% of the anticipated variance, resulted in robust and unbiased signal amplitude estimates in the presence of substantial variability. Conclusion: This method provides a simple and flexible means to provide robust phMRI amplitude estimates within a GLM framework. J. Magn. Reson. Imaging 2010;31:1445–1457. © 2010 Wiley‐Liss, Inc.