[en] Subject-specific hemodynamic response functions (HRFs) have been recommended to capture
variation in the form of the hemodynamic response between subjects (Aguirre et al., [1998]: Neuroimage
8:360–369). The purpose of this article is to find optimal designs for estimation of subject-specific
parameters for the double gamma HRF. As the double gamma function is a nonlinear function of its
parameters, optimal design theory for nonlinear models is employed in this article. The double gamma
function is linearized by a Taylor approximation and the maximin criterion is used to handle dependency
of the D-optimal design on the expansion point of the Taylor approximation. A realistic range of
double gamma HRF parameters is used for the expansion point of the Taylor approximation. Furthermore,
a genetic algorithm (GA) (Kao et al., [2009]: Neuroimage 44:849–856) is applied to find locally
optimal designs for the different expansion points and the maximin design chosen from the locally
optimal designs is compared to maximin designs obtained by m-sequences, blocked designs, designs
with constant interstimulus interval (ISI) and random event-related designs. The maximin design
obtained by the GA is most efficient. Random event-related designs chosen from several generated
designs and m-sequences have a high efficiency, while blocked designs and designs with a constant ISI
have a low efficiency compared to the maximin GA design.
Disciplines :
Neurosciences & behavior
Author, co-author :
Maus, Bärbel ; Maastricht University > Department of Methodology & Statistics
van Breukelen, Gerard J P; Maastricht University > Department of Methodology and Statistics
Goebel, Rainer; Maastricht University > Department of Cognitive Neuroscience
Berger, Martijn P F; Maastricht University > Department of Methodology and Statistics
Language :
English
Title :
Optimal design for nonlinear estimation of the hemodynamic response function.
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