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ABSTRACT: Lack of tissue contrast and existing inhomogeneous bias fields from multi-channel coils have the potential to degrade the output of registration algorithms; and consequently degrade group analysis and any attempt to accurately localize brain function. Non-invasive ways to improve tissue contrast in fMRI images include the use of low flip angles (FAs) well below the Ernst angle and longer repetition times (TR). Techniques to correct intensity inhomogeneity are also available in most mainstream fMRI data analysis packages; but are not used as part of the pre-processing pipeline in many studies. In this work, we use a combination of real data and simulations to show that simple-to-implement acquisition/pre-processing techniques can significantly improve the outcome of both functional-to-functional and anatomical-to-functional image registrations. We also emphasize the need of tissue contrast on EPI images to be able to appropriately evaluate the quality of the alignment. In particular, we show that the use of low FAs (e.g., θ≤40°), when physiological noise considerations permit such an approach, significantly improves accuracy, consistency and stability of registration for data acquired at relatively short TRs (TR≤2s). Moreover, we also show that the application of bias correction techniques significantly improves alignment both for array-coil data (known to contain high intensity inhomogeneity) as well as birdcage-coil data. Finally, improvements in alignment derived from the use of the first infinite-TR volumes (ITVs) as targets for registration are also demonstrated. For the purpose of quantitatively evaluating the different scenarios, two novel metrics were developed: Mean Voxel Distance (MVD) to evaluate registration consistency, and Deviation of Mean Voxel Distance (dMVD) to evaluate registration stability across successive alignment attempts.
NeuroImage 11/2012; · 5.89 Impact Factor
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ABSTRACT: A central challenge in the fMRI based study of functional connectivity is distinguishing neuronally related signal fluctuations from the effects of motion, physiology, and other nuisance sources. Conventional techniques for removing nuisance effects include modeling of noise time courses based on external measurements followed by temporal filtering. These techniques have limited effectiveness. Previous studies have shown using multi-echo fMRI that neuronally related fluctuations are Blood Oxygen Level Dependent (BOLD) signals that can be characterized in terms of changes in R(2)* and initial signal intensity (S(0)) based on the analysis of echo-time (TE) dependence. We hypothesized that if TE-dependence could be used to differentiate BOLD and non-BOLD signals, non-BOLD signal could be removed to denoise data without conventional noise modeling. To test this hypothesis, whole brain multi-echo data were acquired at 3 TEs and decomposed with Independent Components Analysis (ICA) after spatially concatenating data across space and TE. Components were analyzed for the degree to which their signal changes fit models for R(2)* and S(0) change, and summary scores were developed to characterize each component as BOLD-like or not BOLD-like. These scores clearly differentiated BOLD-like "functional network" components from non BOLD-like components related to motion, pulsatility, and other nuisance effects. Using non BOLD-like component time courses as noise regressors dramatically improved seed-based correlation mapping by reducing the effects of high and low frequency non-BOLD fluctuations. A comparison with seed-based correlation mapping using conventional noise regressors demonstrated the superiority of the proposed technique for both individual and group level seed-based connectivity analysis, especially in mapping subcortical-cortical connectivity. The differentiation of BOLD and non-BOLD components based on TE-dependence was highly robust, which allowed for the identification of BOLD-like components and the removal of non BOLD-like components to be implemented as a fully automated procedure.
NeuroImage 12/2011; 60(3):1759-70. · 5.89 Impact Factor
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ABSTRACT: A confound for functional magnetic resonance imaging (fMRI), especially for auditory studies, is the presence of imaging acoustic noise generated mainly as a byproduct of rapid gradient switching during volume acquisition and, to a lesser extent, the radiofrequency transmit. This work utilized a novel pulse sequence to present actual imaging acoustic noise for characterization of the induced hemodynamic responses and assessment of linearity in the primary auditory cortex with respect to noise duration. Results show that responses to brief duration (46 ms) imaging acoustic noise is highly nonlinear while responses to longer duration (>1 s) imaging acoustic noise becomes approximately linear, with the right primary auditory cortex exhibiting a higher degree of nonlinearity than the left for the investigated noise durations. This study also assessed the spatial extent of activation induced by imaging acoustic noise, showing that the use of modeled responses (specific to imaging acoustic noise) as the reference waveform revealed additional activations in the auditory cortex not observed with a canonical gamma variate reference waveform, suggesting an improvement in detection sensitivity for imaging acoustic noise-induced activity. Longer duration (1.5 s) imaging acoustic noise was observed to induce activity that expanded outwards from Heschl's gyrus to cover the superior temporal gyrus as well as parts of the middle temporal gyrus and insula, potentially affecting higher level acoustic processing.
NeuroImage 11/2009; 49(4):3027-38. · 5.89 Impact Factor
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ABSTRACT: To assess and model signal fluctuations induced by non-T(1)-related confounds in variable repetition time (TR) functional magnetic resonance imaging (fMRI) and to develop a compensation procedure to correct for the non-T(1)-related artifacts.
Radiofrequency disabled volume gradient sequences were effected at variable offsets between actual image acquisitions, enabling perturbation of the measurement system without perturbing longitudinal magnetization, allowing the study of non-T(1)-related confounds that may arise in variable TR experiments. Three imaging sessions utilizing a daily quality assurance (DQA) phantom were conducted to assess the signal fluctuations, which were then modeled as a second-order system. A modified projection procedure was implemented to correct for signal fluctuations arising from non-T(1)-related confounds, and statistical analysis was performed to assess the significance of the artifacts with and without compensation.
Assessment using phantom data reveals that the signal fluctuations induced by non-T(1)-related confounds was consistent in shape across the phantom and well-modeled by a second-order system. The phantom exhibited significant spurious detections (at P < 0.01) almost uniformly across the central slices of the phantom.
Second-order system modeling and compensation of non-T(1)-related confounds achieves significant reduction of spurious detection of fMRI activity in a phantom.
Journal of Magnetic Resonance Imaging 05/2009; 29(5):1234-9. · 2.70 Impact Factor
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ABSTRACT: The blood-oxygen-level-dependent (BOLD) signal measured in the brain with functional magnetic resonance imaging (fMRI) during an activation experiment often exhibits pronounced transients at the beginning and end of the stimulus. Such transients could be a reflection of transients in the underlying neural activity, or they could result from transients in cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2), or cerebral blood volume (CBV). These transients were investigated using an arterial spin labeling (ASL) method that allows simultaneous measurements of BOLD and CBF responses. Responses to a finger-tapping task (40-s stimulus, 80-s rest) were measured in primary motor area (M1) and supplementary motor area (SMA) in five healthy volunteers. In SMA, the average BOLD response was pronounced near the beginning and end of the stimulus, while in M1, the BOLD response was nearly flat. However, CBF responses in the two regions were rather similar, and did not exhibit the same transient features as the BOLD response in SMA. Because this suggests a hemodynamic rather than a neural origin for the transients of the BOLD response in SMA, we used a generalization of the balloon model to test the degree of hemodynamic transients required to produce the measured curves. Both data sets could be approximated with modest differences in the shapes of the CMRO2 and CBV responses. This study illustrates the utility and the limitations of using theoretical models combined with ASL techniques to understand the dynamics of the BOLD response.
NeuroImage 02/2004; 21(1):144-53. · 5.89 Impact Factor
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ABSTRACT: We present here a method for improving SNR in CSF-attenuated imaging relative to the standard technique of using an inversion pulse and imaging at the null point of CSF. In this new method the inversion pulse is replaced with a 90x–180y–90x preparation sequence that provides T1 and T2 selectivity. This allows the tissue magnetization to recover more rapidly, allows for the use of shorter TR values, and reduces T1 weighting. Magn Reson Med 45:529–532, 2001. © 2001 Wiley-Liss, Inc.
Magnetic Resonance in Medicine 02/2001; 45(3):529 - 532. · 2.96 Impact Factor
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ABSTRACT: A modified pulsed arterial spin labeling (ASL) technique is introduced here that has both higher temporal resolution and higher SNR per unit time than existing ASL techniques. In this technique, the time TI between the application of the tag and image acquisition is longer than the repetition time TR, allowing for the use of greatly reduced TR values without a significant decrease in the amplitude of the ASL signal. This improves both the temporal resolution and the sensitivity of ASL for functional brain mapping. Magn Reson Med 44:511–515, 2000. © 2000 Wiley-Liss, Inc.
Magnetic Resonance in Medicine 09/2000; 44(4):511 - 515. · 2.96 Impact Factor
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ABSTRACT: Perfusion and blood oxygenation level-dependent (BOLD) signals were simultaneously measured during a finger-tapping task at 3T using QUIPSS II with thin-slice TI1 periodic saturation, a modified pulsed arterial spin labeling technique that provides quantitative measurement of perfusion. Perfusion and BOLD signal changes due to motor activation were obtained and correlated with the T1 values estimated from echo-planar imaging (EPI)-based T1 maps on a voxel-by-voxel basis. The peak perfusion signal occurs in voxels with a T1 of brain parenchyma while the peak BOLD signal occurs in voxels with a T1 characteristic of blood and cerebrospinal fluid. The locations of the peak signals of functional BOLD and perfusion only partially overlap on the order of 40%. Perfusion activation maps will likely represent the sites of neuronal activity better than do BOLD activation maps. Magn Reson Med 44:137–143, 2000. © 2000 Wiley-Liss, Inc.
Magnetic Resonance in Medicine 07/2000; 44(1):137 - 143. · 2.96 Impact Factor
