IngentaConnect The Evaluation of Preprocessing Choices in Single-Subject BOLD fM...

Authors: LaConte S.^{1, 5, 2}; Anderson J.^{5, 3}; Muley S.^{5, 3}; Ashe J.³; Frutiger S.^{5, 3}; Rehm K.^{6, 4}; Hansen L.K.⁶; Yacoub E.^{2, 4}; Hu X.^{1, 2, 4}; Rottenberg D.^{5, 3, 4}; Strother S.^{1, 5, 3, 4}

Source: NeuroImage, Volume 18, Number 1, January 2003 , pp. 10-27(18)

Publisher: Academic Press

Abstract:

This work proposes an alternative to simulation-based receiver operating characteristic (ROC) analysis for assessment of fMRI data analysis methodologies. Specifically, we apply the rapidly developing nonparametric prediction, activation, influence, and reproducibility resampling (NPAIRS) framework to obtain cross-validation-based model performance estimates of prediction accuracy and global reproducibility for various degrees of model complexity. We rely on the concept of an analysis chain meta-model in which all parameters of the preprocessing steps along with the final statistical model are treated as estimated model parameters. Our ROC analog, then, consists of plotting prediction vs. reproducibility results as curves of model complexity for competing meta-models. Two theoretical underpinnings are crucial to utilizing this new validation technique. First, we explore the relationship between global signal-to-noise and our reproducibility estimates as derived previously. Second, we submit our model complexity curves in the prediction versus reproducibility space as reflecting classic bias-variance tradeoffs. Among the particular analysis chains considered, we found little impact in performance metrics with alignment, some benefit with temporal detrending, and greatest improvement with spatial smoothing. © 2002 Elsevier Science (USA)

Language: English

Document Type: Research article

DOI: 10.1006/nimg.2002.1300

Affiliations: 1: Biomedical Engineering 2: Biomedical Engineering, Center for Magnetic Resonance Research 3: Biomedical Engineering, Center for Magnetic Resonance Research, Neurology Department 4: Biomedical Engineering, Center for Magnetic Resonance Research, Neurology Department, Radiology Department, University of Minnesota, Minneapolis, Minnesota, 55455 5: PET Imaging Center, Minneapolis, Minnesota, 55417 6: Department of Mathematical Modeling, Technical University of Denmark, Lyngby, Denmark

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The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics