Investigation of Low Frequency Drift in fMRI Signal

Low frequency drift (0.0-0.015 Hz) has often been reported in time series fMRI data. This drift has often been attributed to physiological noise or subject motion, but no studies have been done to test this assumption. Time series T*2-weighted volumes were acquired on two clinical 1.5 T MRI systems using spiral and EPI readout gradients from cadavers, a normal volunteer, and nonhomogeneous and homogeneous phantoms. The data were tested for significant differences (P = 0.001) from Gaussian noise in the frequency range 0.0-0.015 Hz. The percentage of voxels that were significant in data from the cadaver, normal volunteer, nonhomogeneous and homogeneous phantoms were 13.7-49.0%, 22.1-61.9%, 46.4-68.0%, and 1.10%, respectively. Low frequency drift was more pronounced in regions with high spatial intensity gradients. Significant drifting was present in data acquired from cadavers and nonhomogeneous phantoms and all pulse sequences tested, implying that scanner instabilities and not motion or physiological noise may be the major cause of the drift.

[1]  D. G. Watts,et al.  Spectral analysis and its applications , 1968 .

[2]  H L Kundel,et al.  Nuclear magnetic resonance characteristics of fresh and fixed tissue: the effect of elapsed time. , 1983, Radiology.

[3]  E P du Boulay,et al.  Histopathology of multiple sclerosis lesions detected by magnetic resonance imaging in unfixed postmortem central nervous system tissue. , 1991, Brain : a journal of neurology.

[4]  E C Wong,et al.  Processing strategies for time‐course data sets in functional mri of the human brain , 1993, Magnetic resonance in medicine.

[5]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited , 1995, NeuroImage.

[6]  B. Biswal,et al.  Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.

[7]  X Hu,et al.  Retrospective estimation and correction of physiological fluctuation in functional MRI , 1995, Magnetic resonance in medicine.

[8]  P. Jezzard,et al.  Correction for geometric distortion in echo planar images from B0 field variations , 1995, Magnetic resonance in medicine.

[9]  Peter van Gelderen,et al.  Fast 3D functional magnetic resonance imaging at 1.5 T with spiral acquisition , 1996, Magnetic resonance in medicine.

[10]  J. Pekar,et al.  Whole-brain functional mapping with isotropic MR imaging. , 1996, Radiology.

[11]  E. Bullmore,et al.  Statistical methods of estimation and inference for functional MR image analysis , 1996, Magnetic resonance in medicine.

[12]  D A Finelli,et al.  Magnetization transfer effects on T1-weighted three-dimensional gradient-echo MR images of a phantom simulating enhancing brain lesions. , 1997, AJNR. American journal of neuroradiology.

[13]  J. Saunders,et al.  k‐space detection and correction of physiological artifacts in fMRI , 1997, Magnetic resonance in medicine.

[14]  B. Biswal,et al.  Hypercapnia Reversibly Suppresses Low-Frequency Fluctuations in the Human Motor Cortex during Rest Using Echo–Planar MRI , 1997, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[15]  Karl J. Friston,et al.  Human Brain Function , 1997 .

[16]  M H Buonocore,et al.  Noise suppression digital filter for functional magnetic resonance imaging based on image reference data , 1997, Magnetic resonance in medicine.

[17]  Geraint Rees,et al.  Functional Imaging with magnetic resonce , 1997 .

[18]  J. H. Duyn,et al.  Multislice Imaging of Quantitative Cerebral Perfusion with Pulsed Arterial Spin-Labeling , 1998, NeuroImage.

[19]  Peter van Gelderen,et al.  A comparison of fast MR scan techniques for cerebral activation studies at 1.5 Tesla , 1998, Magnetic resonance in medicine.

[20]  Urs E. Ruttimann,et al.  Quantitation of Regional Cerebral Blood Flow Increases in Prefrontal Cortex during a Working Memory Task: A Steady-State Arterial Spin-Tagging Study , 1998, NeuroImage.