Document Detail

Optimizing preprocessing and analysis pipelines for single-subject fMRI. I. Standard temporal motion and physiological noise correction methods.
MedLine Citation:
PMID:  21455942     Owner:  NLM     Status:  MEDLINE    
Subject-specific artifacts caused by head motion and physiological noise are major confounds in BOLD fMRI analyses. However, there is little consensus on the optimal choice of data preprocessing steps to minimize these effects. To evaluate the effects of various preprocessing strategies, we present a framework which comprises a combination of (1) nonparametric testing including reproducibility and prediction metrics of the data-driven NPAIRS framework (Strother et al. [2002]: NeuroImage 15:747-771), and (2) intersubject comparison of SPM effects, using DISTATIS (a three-way version of metric multidimensional scaling (Abdi et al. [2009]: NeuroImage 45:89-95). It is shown that the quality of brain activation maps may be significantly limited by sub-optimal choices of data preprocessing steps (or "pipeline") in a clinical task-design, an fMRI adaptation of the widely used Trail-Making Test. The relative importance of motion correction, physiological noise correction, motion parameter regression, and temporal detrending were examined for fMRI data acquired in young, healthy adults. Analysis performance and the quality of activation maps were evaluated based on Penalized Discriminant Analysis (PDA). The relative importance of different preprocessing steps was assessed by (1) a nonparametric Friedman rank test for fixed sets of preprocessing steps, applied to all subjects; and (2) evaluating pipelines chosen specifically for each subject. Results demonstrate that preprocessing choices have significant, but subject-dependant effects, and that individually-optimized pipelines may significantly improve the reproducibility of fMRI results over fixed pipelines. This was demonstrated by the detection of a significant interaction with motion parameter regression and physiological noise correction, even though the range of subject head motion was small across the group (≪ 1 voxel). Optimizing pipelines on an individual-subject basis also revealed brain activation patterns either weak or absent under fixed pipelines, which has implications for the overall interpretation of fMRI data, and the relative importance of preprocessing methods.
Nathan W Churchill; Anita Oder; Hervé Abdi; Fred Tam; Wayne Lee; Christopher Thomas; Jon E Ween; Simon J Graham; Stephen C Strother
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-03-31
Journal Detail:
Title:  Human brain mapping     Volume:  33     ISSN:  1097-0193     ISO Abbreviation:  Hum Brain Mapp     Publication Date:  2012 Mar 
Date Detail:
Created Date:  2012-02-09     Completed Date:  2012-05-23     Revised Date:  2013-05-20    
Medline Journal Info:
Nlm Unique ID:  9419065     Medline TA:  Hum Brain Mapp     Country:  United States    
Other Details:
Languages:  eng     Pagination:  609-27     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 Wiley Periodicals, Inc.
Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Image Processing, Computer-Assisted / methods*
Magnetic Resonance Imaging / methods*
Models, Statistical
Reproducibility of Results
Grant Support
84447-1//Canadian Institutes of Health Research; MOP84483//Canadian Institutes of Health Research

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Previous Document:  Comparison of the neural correlates of retrieval success in tests of cued recall and recognition mem...
Next Document:  Hippocampal morphology in lithium and non-lithium-treated bipolar I disorder patients, non-bipolar c...