Wavelet-based estimation of a semiparametric generalized linear model of fMRI time-series.

Full Abstract

This paper addresses the problem of detecting significant changes in fMRI time series that are correlated to a stimulus time course. This paper provides a new approach to estimate the parameters of a semiparametric generalized linear model of fMRI time series. The fMRI signal is described as the sum of two effects:
a smooth trend and the response to the stimulus. The trend belongs to a subspace spanned by large scale wavelets. The wavelet transform provides an approximation to the Karhunen-Loève transform for the long memory noise and we have developed a scale space regression that permits to carry out the regression in the wavelet domain while omitting the scales that are contaminated by the trend. In order to demonstrate that our approach outperforms the state-of-the art detrending technique, we evaluated our method against a smoothing spline approach. Experiments with simulated data and experimental fMRI data, demonstrate that our approach can infer and remove drifts that cannot be adequately represented with splines.

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Author information

Author/s: Meyer, François G (FG);

Affiliation: Department of Electrical Engineering, University of Colorado, Boulder, CO 80302, USA. francois.meyer@colorado.edu

Journal and publication information

Publication Type: Comparative Study; Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies

Journal: IEEE transactions on medical imaging (IEEE Trans Med Imaging), published in United States. (Language: eng)

Reference: 2003-Mar; vol 22 (issue 3) : pp 315-22

Dates: Created 2003/05/22; Completed 2003/09/10; Revised 2006/11/15;

PMID: 12760549, status: MEDLINE (last retrieval date: 11/6/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Acoustic Stimulation - methods
Algorithms
Auditory Perception - physiology
Brain - anatomy & histology; physiology
Brain Mapping - methods
Computer Simulation
Humans
Image Enhancement - methods

Likelihood Functions
Linear Models
Magnetic Resonance Imaging - methods
Models, Biological
Models, Statistical
Signal Processing, Computer-Assisted
Stochastic Processes
Temporal Lobe - anatomy & histology; physiology

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