Document Detail


Enhancing the utility of complex-valued functional magnetic resonance imaging detection of neurobiological processes through postacquisition estimation and correction of dynamic B(0) errors and motion.
MedLine Citation:
PMID:  21305669     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Functional magnetic resonance imaging (fMRI) time series analysis is typically performed using only the magnitude portion of the data. The phase information remains unused largely due to its sensitivity to temporal variations in the magnetic field unrelated to the functional response of interest. These phase changes are commonly the result of physiologic processes such as breathing or motion either inside or outside the imaging field of view. As a result, although the functional phase response carries pertinent physiological information concerning the vasculature, one aspect of which is the location of large draining veins, the full hemodynamic phase response is understudied and is poorly understood, especially in comparison with the magnitude response. It is likely that the magnitude and phase contain disjoint information, which could be used in tandem to better characterize functional hemodynamics. In this work, simulated and human fMRI experimental data are used to demonstrate how statistical analysis of complex-valued fMRI time series can be problematic, and how robust analysis using these powerful and flexible complex-valued statistics is possible through postprocessing with correction for dynamic magnetic field fluctuations in conjunction with estimated motion parameters. These techniques require no special pulse sequence modifications and can be applied to any complex-valued echo planar imaging data set. This analysis shows that the phase component appears to contain information complementary to that in the magnitude and that processing and analysis techniques are available to investigate it in a robust and flexible manner.
Authors:
Andrew D Hahn; Andrew S Nencka; Daniel B Rowe
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2011-02-08
Journal Detail:
Title:  Human brain mapping     Volume:  33     ISSN:  1097-0193     ISO Abbreviation:  Hum Brain Mapp     Publication Date:  2012 Feb 
Date Detail:
Created Date:  2012-01-13     Completed Date:  2012-03-27     Revised Date:  2014-05-19    
Medline Journal Info:
Nlm Unique ID:  9419065     Medline TA:  Hum Brain Mapp     Country:  United States    
Other Details:
Languages:  eng     Pagination:  288-306     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 Wiley Periodicals, Inc.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Artifacts
Brain Mapping / methods*
Computer Simulation
Humans
Image Processing, Computer-Assisted / methods*
Magnetic Fields
Magnetic Resonance Imaging / methods*
Models, Statistical
Motion
Regression Analysis
Grant Support
ID/Acronym/Agency:
EB000215/EB/NIBIB NIH HHS; EB007827/EB/NIBIB NIH HHS; R01 EB000215/EB/NIBIB NIH HHS; R01 EB007827/EB/NIBIB NIH HHS
Comments/Corrections

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