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Are fMRI event-related response constant in time? A model selection answer

Donnet, Sophie; Lavielle, Marc; Poline, Jean-Baptiste (2006), Are fMRI event-related response constant in time? A model selection answer, NeuroImage, 31, 3, p. 1169 – 1176. 10.1016/j.neuroimage.2005.08.068

Type
Article accepté pour publication ou publié
Date
2006
Journal name
NeuroImage
Volume
31
Number
3
Publisher
Elsevier
Pages
1169 – 1176
Publication identifier
10.1016/j.neuroimage.2005.08.068
Metadata
Show full item record
Author(s)
Donnet, Sophie cc

Lavielle, Marc

Poline, Jean-Baptiste
Abstract (EN)
An accurate estimation of the hemodynamic response function (HRF) in functional magnetic resonance imaging (fMRI) is crucial for a precise spatial and temporal estimate of the underlying neuronal processes. Recent works have proposed non-parametric estimation of the HRF under the hypotheses of linearity and stationarity in time. Biological literature suggests, however, that response magnitude may vary with attention or ongoing activity. We therefore test a more flexible model that allows for the variation of the magnitude of the HRF with time in a maximum likelihood framework. Under this model, the magnitude of the HRF evoked by a single event may vary across occurrences of the same type of event. This model is tested against a simpler model with a fixed magnitude using information theory. We develop a standard EM algorithm to identify the event magnitudes and the HRF. We test this hypothesis on a series of 32 regions (4 ROIS on eight subjects) of interest and find that the more flexible model is better than the usual model in most cases. The important implications for the analysis of fMRI time series for event-related neuroimaging experiments are discussed.
Subjects / Keywords
fMRI data; EM algorithm; maximum likelihood; model selection

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