Faculty Collaboration Database

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. Hum Brain Mapp 2012 Feb;33(2):288-306

Date

02/10/2011

Pubmed ID

21305669

Pubmed Central ID

PMC4001883

DOI

10.1002/hbm.21217

Scopus ID

2-s2.0-84855939756 (requires institutional sign-in at Scopus site)   9 Citations

Abstract

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.

Author List

Hahn AD, Nencka AS, Rowe DB

Author

Andrew S. Nencka PhD Director, Associate Professor in the Radiology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Algorithms
Artifacts
Brain Mapping
Computer Simulation
Humans
Image Processing, Computer-Assisted
Magnetic Fields
Magnetic Resonance Imaging
Models, Statistical
Motion
Regression Analysis