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Articles by Thomas T. Liu in JoVE

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Analysis and Design of Perfusion-based Event-related FMRI Experiments

Perfusion-based functional magnetic resonance imaging (fMRI) using arterial spin labeling (ASL) methods has the potential to provide better localization of the functional signal to the sites of neural activity compared to blood oxygenation level-dependent (BOLD) contrast fMRI. At present, experiments using ASL have been limited to simple block and periodic single-trial designs. We present here an adaptation of the general linear model to perfusion-based fMRI that enables the design and analysis of more complicated designs, such as random and semirandom event-related designs. Formulas for the least-squares estimate of the perfusion response and the F statistic for the detection of a response are derived. Exact expressions and useful approximations for detection power and estimation efficiency are presented, and it is shown that the trade-off between power and efficiency for perfusion experiments is similar to that previously observed for BOLD experiments. The least-squares estimate is compared with an estimate formed from the running subtraction of tag and control images. The running subtraction estimate is shown to be approximately equal to a temporally low-pass-filtered version of the least-squares estimate. Numerical simulations and results from ASL experiments are used to support the theoretical findings.

Increased Diffusion Sensitivity with Hyperechos

It is shown that the introduction of a 180 degrees refocusing pulse into a standard diffusion weighted stimulated echo sequence is equivalent to the simplest hyperecho sequence with identical diffusion weighting but equal or greater signal-to-noise (SNR) and thus equal or greater diffusion contrast. For high b-value imaging, the hyperecho sequence thus possesses the high diffusion contrast in the presence of small T(1)/T(2) ratios characteristic of stimulated echo sequences but with less than the 50% loss in SNR that is associated with the stimulated echo. For low b-value imaging, the hyperecho signal converges to that of the standard spin echo. The advantages of the two-pulse diffusion weighted hyperecho sequence are demonstrated theoretically. Experimental results are shown in the application to high angular resolution diffusion encoding (HARD) in normal human brain.

Discrepancies Between BOLD and Flow Dynamics in Primary and Supplementary Motor Areas: Application of the Balloon Model to the Interpretation of BOLD Transients

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.

Efficiency, Power, and Entropy in Event-related FMRI with Multiple Trial Types. Part I: Theory

Experimental designs for functional magnetic resonance imaging (fMRI) experiments can be characterized by their estimation efficiency, which is a measure of the variance in the estimate of the hemodynamic response function (HRF), and their detection power, which is a measure of the variance in the estimate of the amplitude of functional activity. Previous studies have shown that there exists a fundamental trade-off between efficiency and power for experiments with a single trial type of interest. This paper extends the prior work by presenting a theoretical model for the relation between detection power and estimation efficiency in experiments with multiple trial types. It is shown that the trade-off between efficiency and power present in multiple-trial-type experiments is identical in form to that observed for single-trial-type experiments. Departures from the predicted trade-off due to the inclusion of basis function expansions and the assumption of correlated noise are examined. Finally, conditional entropy is introduced as measure for the randomness of a design, and an empirical relation between entropy and estimation efficiency is presented.

Efficiency, Power, and Entropy in Event-related FMRI with Multiple Trial Types. Part II: Design of Experiments

The performance of an experimental design for functional magnetic resonance imaging (fMRI) can be characterized by its estimation efficiency, which is the ability to make an estimate of the hemodynamic response, its detection power, which is the ability to detect an activation, and its conditional entropy, which is a measure of the randomness of the design. In Liu and Frank [Neuroimage 21 (2004) 387-400], it is shown that there is a fundamental theoretical trade-off between estimation efficiency and detection power for experiments with multiple trial types and that there is an empirical relation between estimation efficiency and conditional entropy. This paper provides an intuitive interpretation of the theoretical results and examines the practical implications of these results for the optimal design of fMRI experiments with multiple trial types. The properties of block designs, permuted block designs, m-sequence designs, clustered m-sequence designs, and mixed designs are explored. It is shown that these designs nearly achieve the theoretically predicted performance and can be used in practice to obtain advantageous trade-offs among efficiency, power, and entropy.

Trend Detection Via Temporal Difference Model Predicts Inferior Prefrontal Cortex Activation During Acquisition of Advantageous Action Selection

The process of accurately predicting which actions are associated with advantageous versus disadvantageous outcomes is an important function of daily life. An integral part of this process is being able to detect when the association between an action and an outcome changes. This investigation examined the hypothesis that the inferior prefrontal cortex is critical for the detection of trends and that a trend process derived from the temporal difference model accomplishes this detection. Nineteen normal right-handed volunteers completed 120 4-s trials of a Rock Paper Scissors (RPS) task during functional magnetic resonance imaging. Subjects acquired the selection of advantageous actions during the RPS task. Activations in the medial frontal gyrus (BA 10), left ventrolateral frontal gyrus (BA 11/47), and left pallidum were significantly higher during trials in which subjects acquired the advantageous action. The time course of individually derived trend detection functions was found to be time-locked to the hemodynamic changes in the inferior frontal gyrus. These findings are consistent with the hypothesis that the inferior prefrontal cortex computes a trend from previously experienced action-outcome sequences based on a value function derived from the temporal difference model.

Coupling of Cerebral Blood Flow and Oxygen Consumption During Physiological Activation and Deactivation Measured with FMRI

The physiological basis of the blood oxygenation level dependent (BOLD) signal and its dependence on baseline cerebral blood flow (CBF) were investigated by comparing responses to a visual stimulus after physiological changes of the baseline. Eight human subjects were imaged with 3 and 4 T MRI scanners, and both BOLD signal and CBF were simultaneously measured. Subjects viewed a flickering radial checkerboard in a block design experiment, alternating between eyes open or closed during the off periods. Compared to a baseline state with eyes open in a darkened room, substantial deactivation (average change: 2.9 +/- 0.3% BOLD, 22 +/- 2.1% CBF) in the occipital cortex was observed when the eyes were closed. The absolute response during stimulation (average change: 4.4 +/- 0.4% BOLD, 36.3 +/- 3.1% CBF) was independent of the preceding resting condition. We estimated the fractional change in CBF to be approximately 2.2 +/- 0.15 times greater than the fractional change in metabolic rate of oxygen (CMRO2). The changes in CBF and CMRO2 were consistently linearly coupled during activation and deactivation with CBF changes being between approximately 60% and 150% compared to baseline with eyes open. Relative to an assumed baseline oxygen extraction fraction (OEF) of 40%, the estimated OEF decreased to 33 +/- 1.4% during activation and increased to 46 +/- 1.2% during rest with eyes closed. In conclusion, we found that simply closing the eyes creates a large physiological deactivation in the visual cortex, and provides a robust paradigm for studying baseline effects in fMRI. In addition, we propose a feed-forward model for neurovascular coupling which accounts for the changes in OEF seen following baseline changes, including both the current physiological perturbations as well as previously reported pharmacologically induced changes.

Modeling the Hemodynamic Response to Brain Activation

Neural activity in the brain is accompanied by changes in cerebral blood flow (CBF) and blood oxygenation that are detectable with functional magnetic resonance imaging (fMRI) techniques. In this paper, recent mathematical models of this hemodynamic response are reviewed and integrated. Models are described for: (1) the blood oxygenation level dependent (BOLD) signal as a function of changes in cerebral oxygen extraction fraction (E) and cerebral blood volume (CBV); (2) the balloon model, proposed to describe the transient dynamics of CBV and deoxy-hemoglobin (Hb) and how they affect the BOLD signal; (3) neurovascular coupling, relating the responses in CBF and cerebral metabolic rate of oxygen (CMRO(2)) to the neural activity response; and (4) a simple model for the temporal nonlinearity of the neural response itself. These models are integrated into a mathematical framework describing the steps linking a stimulus to the measured BOLD and CBF responses. Experimental results examining transient features of the BOLD response (post-stimulus undershoot and initial dip), nonlinearities of the hemodynamic response, and the role of the physiologic baseline state in altering the BOLD signal are discussed in the context of the proposed models. Quantitative modeling of the hemodynamic response, when combined with experimental data measuring both the BOLD and CBF responses, makes possible a more specific and quantitative assessment of brain physiology than is possible with standard BOLD imaging alone. This approach has the potential to enhance numerous studies of brain function in development, health, and disease.

Caffeine Alters the Temporal Dynamics of the Visual BOLD Response

The blood oxygenation level-dependent (BOLD) responses to visual stimuli, using both a 1-s long single trial stimulus and a 20-s long block stimulus, were measured in a 4-T magnetic field both before and immediately after a 200-mg caffeine dose. In addition, resting levels of cerebral blood flow (CBF) were measured using arterial spin labeling. For the single trial stimulus, the caffeine dose significantly (p<0.05) reduced the time to peak (TTP), the time after the peak at which the response returned to 50% of the peak amplitude (TA50), and the amplitude of the poststimulus undershoot in all subjects (N=5). Other parameters, such as the full-width half-maximum (FWHM) and the peak amplitude, also showed significant changes in the majority of subjects. For the block stimulus, the TTP, TA50, and the time for the response to reach 50% of the peak amplitude (T50) were significantly reduced. In some subjects, oscillations were observed in the poststimulus portion of the response with median peak periods of 9.1 and 9.5 s for the single trial and block responses, respectively. Resting CBF was reduced by an average of 24%. The reproducibility of the results was verified in one subject who was scanned on 3 different days. The dynamic changes are similar to those previously reported for baseline CBF reductions induced by hypocapnia and hyperoxia.

An Arteriolar Compliance Model of the Cerebral Blood Flow Response to Neural Stimulus

Although functional magnetic resonance imaging (fMRI) is a widely used and powerful tool for studying brain function, the quantitative interpretation of fMRI measurements for basic neuroscience and clinical studies can be complicated by inter-subject and inter-session variability arising from modulation of the baseline vascular state by disease, aging, diet, and pharmacological agents. In particular, recent studies have shown that the temporal dynamics of the cerebral blood flow (CBF) and the blood oxygenation level dependent (BOLD) responses to stimulus are modulated by changes in baseline CBF induced by various vasoactive agents and by decreases in vascular compliance associated with aging. These effects are not readily explained using current models of the CBF and BOLD responses. We present here a second-order nonlinear feedback model of the evoked CBF response in which neural activity modulates the compliance of arteriolar smooth muscle. Within this model framework, the baseline vascular state affects the dynamic response by changing the relative contributions of an active smooth muscle component and a passive connective tissue component to the overall vessel compliance. Baseline dependencies of the BOLD signal are studied by coupling the arteriolar compliance model with a previously described balloon model of the venous compartment. Numerical simulations show that the proposed model describes to first order the observed dependence of CBF and BOLD responses on the baseline vascular state.

A Signal Processing Model for Arterial Spin Labeling Functional MRI

A model of the signal path in arterial spin labeling (ASL)-based functional magnetic resonance imaging (fMRI) is presented. Three subtraction-based methods for forming a perfusion estimate are considered and shown to be specific cases of a generalized estimate consisting of a modulator followed by a low pass filter. The performance of the methods is evaluated using the signal model. Contamination of the perfusion estimate by blood oxygenation level dependent contrast (BOLD) is minimized by using either sinc subtraction or surround subtraction for block design experiments and by using pair-wise subtraction for randomized event-related experiments. The subtraction methods all tend to decorrelate the 1/f type low frequency noise often observed in fMRI experiments. Sinc subtraction provides the flattest noise power spectrum at low frequencies, while pair-wise subtraction yields the narrowest autocorrelation function. The formation of BOLD estimates from the ASL data is also considered and perfusion weighting of the estimates is examined using the signal model.

Physiological Noise Reduction for Arterial Spin Labeling Functional MRI

Three methods for the reduction of physiological noise in arterial spin labeling (ASL) functional magnetic resonance imaging (fMRI) are presented and compared. The methods are based upon a general linear model of the ASL measurement process and on a previously described retrospective image-based method (RETROICOR) for physiological noise reduction in blood oxygenation level dependent fMRI. In the first method, the contribution of physiological noise to the interleaved control and tag images that comprise the ASL time series are assumed to be equal, while in the second method this assumption is not made. For the third method, it is assumed that physiological noise primarily impacts the perfusion time series obtained from the filtered subtraction of the control and tag images. The methods were evaluated using studies of functional activity in the visual cortex and the hippocampal region. The first and second methods significantly improved statistical performance in both brain regions, whereas the third method did not provide a significant gain. The second method provided significantly better performance than the first method in the hippocampal region, whereas the differences between methods were less pronounced in visual cortex. The improved performance of the second method in the hippocampal region appears to reflect the relatively greater effect of cardiac fluctuations in this brain region. The proposed methods should be particularly useful for ASL studies of cognitive processes where the intrinsic signal to noise ratio is typically lower than for studies of primary sensory regions.

Caffeine Reduces the Initial Dip in the Visual BOLD Response at 3 T

Localized changes in oxygen consumption related to increased neural activity can result in a small and transient "initial dip" of the blood oxygenation level-dependent (BOLD) signal used in functional magnetic resonance imaging (fMRI). The initial dip has been of great interest to the fMRI community because it may provide a more accurate and localized measure of neural activity than the conventional BOLD signal increase. Although potentially useful as a technique for human brain mapping, the initial dip is not always detected and has been a source of some controversy. In this study, the BOLD response to a 4-s long visual stimulus was measured with a 3-T MRI system in 5 healthy volunteers both before and immediately after a 200-mg oral caffeine dose. The caffeine dose significantly (P < 0.001) reduced or eliminated the initial dip in all subjects. These findings suggest that caffeine usage may be a key factor in the detection of the initial dip in human fMRI studies.

Velocity-selective Arterial Spin Labeling

In pathologies in which slow or collateral flow conditions may exist, conventional arterial spin labeling (ASL) methods that apply magnetic tags based on the location of arterial spins may not provide robust measures of cerebral blood flow (CBF), as the transit delay for the delivery of blood to target tissues may far exceed the relaxation time of the tag. Here we describe current methods for ASL with velocity-selective (VS) tags (termed VSASL) that do not require spatial selectivity and can thus provide quantitative measures of CBF under slow and collateral flow conditions. The implementation of a robust multislice VSASL technique is described in detail, and data obtained with this technique are compared with those obtained with conventional pulsed ASL (PASL). The technical considerations described here include the design of VS pulses, background suppression, anisotropy with respect to velocity-encoding directions, and CBF quantitation issues.

Bayesian Inference of Hemodynamic Changes in Functional Arterial Spin Labeling Data

The study of brain function using MRI relies on acquisition techniques that are sensitive to different aspects of the hemodynamic response contiguous to areas of neuronal activity. For this purpose different contrasts such as arterial spin labeling (ASL) and blood oxygenation level dependent (BOLD) functional MRI techniques have been developed to investigate cerebral blood flow (CBF) and blood oxygenation, respectively. Analysis of such data typically proceeds by separate, linear modeling of the appropriate CBF or BOLD time courses. In this work an approach is developed that provides simultaneous inference on hemodynamic changes via a nonlinear physiological model of ASL data acquired at multiple echo times. Importantly, this includes a significant contribution by changes in the static magnetization, M, to the ASL signal. Inference is carried out in a Bayesian framework. This is able to extract, from dual-echo ASL data, probabilistic estimates of percentage changes of CBF, R(2) (*), and the static magnetization, M. This approach provides increased sensitivity in inferring CBF changes and reduced contamination in inferring BOLD changes when compared with general linear model approaches on single-echo ASL data. We also consider how the static magnetization, M, might be related to changes in CBV by assuming the same mechanism for water exchange as in vascular space occupancy.

Measurement of Cerebral Perfusion with Arterial Spin Labeling: Part 1. Methods

Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI) method that provides a highly repeatable quantitative measure of cerebral blood flow (CBF). As compared to the more commonly used blood oxygenation level dependent (BOLD) contrast-based methods, ASL techniques measure a more biologically specific correlate of neural activity, with the potential for more accurate estimation of the location and magnitude of neural function. Recent advances in acquisition and analysis methods have improved the somewhat limited sensitivity of ASL to perfusion changes associated with neural activity. In addition, ASL perfusion measures are insensitive to the low-frequency fluctuations commonly observed in BOLD experiments and can make use of imaging sequences that are less sensitive than BOLD contrast to signal loss caused by magnetic susceptibility effects. ASL measures of perfusion can aid in the interpretation of the BOLD signal change and, when combined with BOLD, can measure the change in oxygen utilization accompanying changes in behavioral state. Whether used alone to probe neural activity or in combination with BOLD techniques, ASL methods are contributing to the field's understanding of healthy and disordered brain function.

Measurement of Cerebral Perfusion with Arterial Spin Labeling: Part 2. Applications

Arterial spin labeling (ASL) uses magnetic resonance imaging methods to measure cerebral blood flow (CBF) non-invasively. ASL CBF validly localizes brain function and may be especially useful for studies where the time frame of behavioral change is more than a few minutes, such as in longitudinal and treatment studies. ASL measures of cerebral perfusion are highly accurate in detecting lesion laterality in temporal lobe epilepsy, stenotic-occlusive disease, and brain tumors. Among lesioned patients, ASL CBF has excellent concurrent validity when correlated with CBF measured by Positron Emission Tomography or with dynamic susceptibility-weighted magnetic resonance. ASL CBF can predict tumor grading in vivo and can predict six-month response to the surgical treatment of brain tumors. ASL's capability to selectively and non-invasively tag flow in major vessels may refine the monitoring of treatment of cerebrovascular disease and brain tumors. Conclusions about the utility of ASL are limited by the small sample sizes of the studies currently in the literature and by the uncertainty caused by the effect of brain disease on transit times of the magnetic tag. As the method evolves, ASL techniques will likely become more widely used in clinical research and practice.

A Primer on Functional Magnetic Resonance Imaging

In this manuscript, basic principles of functional magnetic resonance imaging (fMRI) are reviewed. In the first section, two intrinsic mechanisms of magnetic resonance image contrast related to the longitudinal and transverse components of relaxing spins and their relaxation rates, T(1) and T(2), are described. In the second section, the biophysical mechanisms that alter the apparent transverse relaxation time, T(2*), in blood oxygenation level dependent (BOLD) studies and the creation of BOLD activation maps are discussed. The physiological complexity of the BOLD signal is emphasized. In the third section, arterial spin labeling (ASL) measures of cerebral blood flow are presented. Arterial spin labeling inverts or saturates the magnetization of flowing spins to measure the rate of delivery of blood to capillaries. In the fourth section, calibrated fMRI, which uses BOLD and ASL to infer alterations of oxygen utilization during behavioral activation, is reviewed. The discussion concludes with challenges confronting studies of individual cases.

A Component Based Noise Correction Method (CompCor) for BOLD and Perfusion Based FMRI

A component based method (CompCor) for the reduction of noise in both blood oxygenation level-dependent (BOLD) and perfusion-based functional magnetic resonance imaging (fMRI) data is presented. In the proposed method, significant principal components are derived from noise regions-of-interest (ROI) in which the time series data are unlikely to be modulated by neural activity. These components are then included as nuisance parameters within general linear models for BOLD and perfusion-based fMRI time series data. Two approaches for the determination of the noise ROI are considered. The first method uses high-resolution anatomical data to define a region of interest composed primarily of white matter and cerebrospinal fluid, while the second method defines a region based upon the temporal standard deviation of the time series data. With the application of CompCor, the temporal standard deviation of resting-state perfusion and BOLD data in gray matter regions was significantly reduced as compared to either no correction or the application of a previously described retrospective image based correction scheme (RETROICOR). For both functional perfusion and BOLD data, the application of CompCor significantly increased the number of activated voxels as compared to no correction. In addition, for functional BOLD data, there were significantly more activated voxels detected with CompCor as compared to RETROICOR. In comparison to RETROICOR, CompCor has the advantage of not requiring external monitoring of physiological fluctuations.

Cerebral Blood Flow and BOLD Responses to a Memory Encoding Task: a Comparison Between Healthy Young and Elderly Adults

Functional magnetic resonance imaging (fMRI) studies of the medial temporal lobe have primarily made use of the blood oxygenation level dependent (BOLD) response to neural activity. The interpretation of the BOLD signal as a measure of medial temporal lobe function can be complicated, however, by changes in the cerebrovascular system that can occur with both normal aging and age-related diseases, such as Alzheimer's disease. Quantitative measures of the functional cerebral blood flow (CBF) response offer a useful complement to BOLD measures and have been shown to aid in the interpretation of fMRI studies. Despite these potential advantages, the application of ASL to fMRI studies of cognitive tasks and at-risk populations has been limited. In this study, we demonstrate the application of ASL fMRI to obtain measures of the CBF and BOLD responses to the encoding of natural scenes in healthy young (mean 25 years) and elderly (mean 74 years) adults. The percent CBF increase in the medial temporal lobe was significantly higher in the older adults, whereas the CBF levels during baseline and task conditions and during a separate resting-state scan were significantly lower in the older group. The older adults also showed slightly higher values for the BOLD response amplitude and the absolute change in CBF, but the age group differences were not significant. The percent CBF and BOLD responses are consistent with an age-related increase in the cerebral metabolic rate of oxygen metabolism (CMRO(2)) response to memory encoding.

Noninvasive Measurement of the Cerebral Blood Flow Response in Human Lateral Geniculate Nucleus with Arterial Spin Labeling FMRI

To date, functional magnetic resonance imaging (fMRI) studies of the lateral geniculate nucleus (LGN) have primarily focused on measures of the blood oxygenation level dependent (BOLD) signal. Arterial spin labeling (ASL) is an MRI method that can provide direct measures of functional cerebral blood flow (CBF) changes. Because CBF is a well-defined physiological quantity that contributes to BOLD contrast, CBF measures can be used to improve the quantitative interpretation of fMRI studies. However, due in part to the low intrinsic signal-to-noise ratio of the ASL method, measures of functional CBF changes in the LGN are challenging and have not previously been reported. In this study, we demonstrate the feasibility of using ASL fMRI to measure the CBF response of the LGN to visual stimulation on a 3 T MRI system. The use of background suppression and physiological noise reduction techniques allowed reliable detection of LGN activation in all five subjects studied. The measured percent CBF response during activation ranged from 40 to 100%, assuming no interaction between the left and right LGN.

Imaging Periodic Currents Using Alternating Balanced Steady-state Free Precession

Existing functional brain MR imaging methods detect neuronal activity only indirectly via a surrogate signal such as deoxyhemoglobin concentration in the vascular bed of cerebral parenchyma. It has been recently proposed that neuronal currents may be measurable directly using MRI (ncMRI). However, limited success has been reported in neuronal current detection studies that used standard gradient or spin echo pulse sequences. The balanced steady-state free precession (bSSFP) pulse sequence is unique in that it can afford the highest known SNR efficiency and is exquisitely sensitive to perturbations in free precession phase. It is reported herein that when a spin phase-perturbing periodic current is locked to an RF pulse train, phase perturbations are accumulated across multiple RF excitations and the spin magnetization reaches an alternating balanced steady state (ABSS) that effectively amplifies the phase perturbations due to the current. The alternation of the ABSS signal therefore is highly sensitive to weak periodic currents. Current phantom experiments employing ABSS imaging resulted in detection of magnetic field variations as small as 0.15nT in scans lasting for 36 sec, which is more sensitive than using gradient-recalled echo imaging.

SNR and Functional Sensitivity of BOLD and Perfusion-based FMRI Using Arterial Spin Labeling with Spiral SENSE at 3 T

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies using parallel imaging to reduce the readout window have reported a loss in temporal signal-to-noise ratio (SNR) that is less than would be expected given a purely thermal noise model. In this study, the impact of parallel imaging on the noise components and functional sensitivity of both BOLD and perfusion-based fMRI data was investigated. Dual-echo arterial spin labeling data were acquired on five subjects using sensitivity encoding (SENSE), at reduction factors (R) of 1, 2 and 3. Direct recording of cardiac and respiratory activity during data acquisition enabled the retrospective removal of physiological noise. The temporal SNR of the perfusion time series closely followed the thermal noise prediction of a radicalR loss in SNR as the readout window was shortened, with temporal SNR values (relative to the R=1 data) of 0.72 and 0.56 for the R=2 and R=3 data, respectively, after accounting for physiological noise. However, the BOLD temporal SNR decreased more slowly than predicted even after accounting for physiological noise, with relative temporal SNR values of 0.80 and 0.63 for the R=2 and R=3 data, respectively. Spectral analysis revealed that the BOLD trends were dominated by low-frequency fluctuations, which were not dominant in the perfusion data due to signal processing differences. The functional sensitivity, assessed using mean F values over activated regions of interest (ROIs), followed the temporal SNR trends for the BOLD data. However, results for the perfusion data were more dependent on the threshold used for ROI selection, most likely due to the inherently low SNR of functional perfusion data.

Caffeine-induced Uncoupling of Cerebral Blood Flow and Oxygen Metabolism: a Calibrated BOLD FMRI Study

Although functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) signal changes is a sensitive tool for mapping brain activation, quantitative studies of the physiological effects of pharmacological agents using fMRI alone are difficult to interpret due to the complexities inherent in the BOLD response. Hypercapnia-calibrated BOLD methodology is potentially a more powerful physiological probe of brain function, providing measures of the changes in cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO(2)). In this study, we implemented a quantitative R(2)* approach for assessing the BOLD response to improve the stability of repeated measurements, in combination with the calibrated BOLD method, to examine the CBF and CMRO(2) responses to caffeine ingestion. Ten regular caffeine consumers were imaged before and after a 200-mg caffeine dose. A dual-echo arterial spin labeling technique was used to measure CBF and BOLD responses to visual stimulation, caffeine consumption and mild hypercapnia. For a region of interest defined by CBF activation to the visual stimulus, the results were: hypercapnia increased CBF (+46.6%, +/-11.3, mean and standard error), visual stimulation increased both CBF (+47.9%, +/-2.9) and CMRO(2) (+20.7%, +/-1.4), and caffeine decreased CBF (-34.5%, +/-2.6) with a non-significant change in CMRO(2) (+5.2%, +/-6.4). The coupling between CBF and CMRO(2) was significantly different in response to visual stimulation compared to caffeine consumption. A calibrated BOLD methodology using R(2) * is a promising approach for evaluating CBF and CMRO(2) changes in response to pharmacological interventions.

Calibrated FMRI in the Medial Temporal Lobe During a Memory-encoding Task

Prior measures of the blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF) responses to a memory-encoding task within the medial temporal lobe have suggested that the coupling between functional changes in CBF and changes in the cerebral metabolic rate of oxygen (CMRO(2)) may be tighter in the medial temporal lobe as compared to the primary sensory areas. In this study, we used a calibrated functional magnetic resonance imaging (fMRI) approach to directly estimate memory-encoding-related changes in CMRO(2) and to assess the coupling between CBF and CMRO(2) in the medial temporal lobe. The CBF-CMRO(2) coupling ratio was estimated using a linear fit to the flow and metabolism changes observed across subjects. In addition, we examined the effect of region-of-interest (ROI) selection on the estimates. In response to the memory-encoding task, CMRO(2) increased by 23.1+/-8.8% to 25.3+/-5.7% (depending upon ROI), with an estimated CBF-CMRO(2) coupling ratio of 1.66+/-0.07 to 1.75+/-0.16. There was not a significant effect of ROI selection on either the CMRO(2) or coupling ratio estimates. The observed coupling ratios were significantly lower than the values (2 to 4.5) that have been reported in previous calibrated fMRI studies of the visual and motor cortices. In addition, the estimated coupling ratio was found to be less sensitive to the calibration procedure for functional responses in the medial temporal lobe as compared to the primary sensory areas.

Caffeine Reduces the Activation Extent and Contrast-to-noise Ratio of the Functional Cerebral Blood Flow Response but Not the BOLD Response

Measures of the spatial extent of functional activation are important for a number of functional magnetic resonance imaging (fMRI) applications, such as pre-surgical planning and longitudinal tracking of changes in brain activation with disease progression and drug treatment. The interpretation of the data from these applications can be complicated by inter-subject or inter-session variability in the measured fMRI signals. Prior studies have shown that modulation of baseline cerebral blood flow (CBF) can directly alter the functional CBF and blood oxygenation level dependent (BOLD) responses, suggesting that the spatial extents of functional activation maps based on these signals may also depend on baseline CBF. In this study, we used a caffeine dose (200 mg) to decrease baseline CBF and found significant (p<0.05) reductions in both the CBF activation extent and contrast-to-noise ratio (CNR) but no significant changes in the BOLD activation extent and CNR. In contrast, caffeine significantly changed the temporal dynamics of the BOLD response but not the CBF response. The decreases in the CBF activation extent and CNR were consistent with a significant caffeine-induced decrease in the absolute CBF change accompanied by no significant change in the residual noise. Measures of baseline CBF also accounted for a significant portion of the inter-subject variability in the CBF activation map area and CNR. Factors that can modulate baseline CBF, such as age, medication, and disease, should therefore be carefully considered in the interpretation of studies that use functional CBF activation maps.

Optimal Phase Difference Reconstruction: Comparison of Two Methods

The present study compares the performance of the weighted mean (WM) and sensitivity encoding (SENSE) methods for reconstructing phase difference images over a large range of signal-to-noise ratio (SNR). It is found that the WM algorithm is suboptimal, compared to the SENSE method at low SNR. Numerical simulations, phantom and in vivo results are presented.

Inter-subject Variability in Hypercapnic Normalization of the BOLD FMRI Response

In the application of hypercapnic normalization to functional magnetic resonance imaging (fMRI) studies, the blood oxygenation level dependent (BOLD) response to a functional stimulus is typically divided by the BOLD response to a hypercapnic challenge. While some prior studies have shown that hypercapnic normalization can reduce inter-subject BOLD variability, other studies have found an increase in inter-subject variability. In this study we used measures of baseline cerebral blood flow (CBF) and the functional BOLD and CBF responses to both visual stimuli and hypercapnia to assess the effect of hypercapnic normalization on inter-subject variability. We found that the functional and hypercapnic BOLD and CBF responses all exhibited a significant inverse dependence on baseline CBF. In contrast, the maximum BOLD response was independent of baseline CBF and was not a major source of inter-subject BOLD variability. Division of the functional BOLD response by the hypercapnic BOLD response increased inter-subject variability in the normalized responses as compared to the original responses, reflecting the presence of a systematic bias term that was inversely dependent on the hypercapnic BOLD response. This systematic bias resulted from a positive intercept term in the linear relationship between the functional and hypercapnic BOLD responses. This positive intercept term reflected a steeper inverse dependence of the hypercapnic CBF response on baseline CBF, as compared to the functional CBF response. In contrast to the results obtained with normalization based on division, normalized responses obtained by using the hypercapnic BOLD response as a covariate were unaffected by the systematic bias and exhibited reduced inter-subject variability. The findings of this study indicate that the positive intercept in the linear relationship between functional and hypercapnic BOLD responses should be carefully considered in the hypercapnic normalization of BOLD fMRI data.

Caffeine Reduces Resting-state BOLD Functional Connectivity in the Motor Cortex

In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects (N=9). We found that caffeine significantly (p<0.05) reduced measures of resting-state BOLD connectivity in the motor cortex. Baseline cerebral blood flow and spectral energy in the low-frequency BOLD fluctuations were also significantly decreased by caffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

Cerebral Perfusion and Oxygenation Differences in Alzheimer's Disease Risk

Functional MRI has demonstrated differences in response to memory performance based on risk for Alzheimer's disease (AD). The current study compared blood oxygen level dependent (BOLD) functional MRI response with arterial spin labeling (ASL) perfusion response during an associative encoding task and resting perfusion signal in different risk groups for AD. Thirteen individuals with a positive family history of AD and at least one copy of the apolipoprotien E epsilon4 (APOE4) gene (high risk) were compared to ten individuals without these risk factors (low risk). In the medial temporal lobes (MTLs) the high risk group had an elevated level of resting perfusion, and demonstrated decreased fractional BOLD and perfusion responses to the encoding task. However, there was no difference in the absolute cerebral blood flow during the task. These data demonstrate that individuals with increased risk for Alzheimer's disease have elevated MTL resting cerebral blood flow, which significantly influences apparent differences in BOLD activations. BOLD activations should be interpreted with caution, and do not necessarily reflect differences in neuronal activation.

Differential Age Effects on Cerebral Blood Flow and BOLD Response to Encoding: Associations with Cognition and Stroke Risk

Changes in the cerebrovascular system due to age or disease can significantly alter the blood-oxygenation-level-dependent (BOLD) signal and complicate its interpretation. The simultaneous acquisition of arterial spin labeling (ASL) and BOLD data represents a useful technique to more fully characterize the neurovascular underpinnings of functional brain response to cognition. We conducted a functional magnetic resonance imaging (FMRI) study of episodic memory encoding to investigate whether age is related to cerebral blood flow (CBF) and BOLD response in the medial temporal lobe (MTL). Results demonstrated a significant reduction in resting-state CBF in older compared to young adults. Conversely, older adults showed significantly increased CBF but not BOLD response in the MTL during picture encoding relative to young adults. Correlations between CBF response and cognition were demonstrated whereas associations with BOLD were not observed. Stroke risk was associated with both CBF and BOLD response. Results suggest that aging effects on CBF and BOLD responses to encoding are dissociable and that cerebrovascular alterations contribute to findings of age-related differences.

Caffeine Increases the Linearity of the Visual BOLD Response

Although the blood oxygenation level dependent (BOLD) signal used in most functional magnetic resonance imaging (fMRI) studies has been shown to exhibit nonlinear characteristics, most analyses assume that the BOLD signal responds in a linear fashion to stimulus. This assumption of linearity can lead to errors in the estimation of the BOLD response, especially for rapid event-related fMRI studies. In this study, we used a rapid event-related design and Volterra kernel analysis to assess the effect of a 200 mg oral dose of caffeine on the linearity of the visual BOLD response. The caffeine dose significantly (p<0.02) increased the linearity of the BOLD response in a sample of 11 healthy volunteers studied on a 3 T MRI system. In addition, the agreement between nonlinear and linear estimates of the hemodynamic response function was significantly increased (p=0.013) with the caffeine dose. These findings indicate that differences in caffeine usage should be considered as a potential source of bias in the analysis of rapid event-related fMRI studies.

An Arterial Spin Labeling Investigation of Cerebral Blood Flow Deficits in Chronic Stroke Survivors

Although the acute stroke literature indicates that cerebral blood flow (CBF) may commonly be disordered in stroke survivors, limited research has investigated whether CBF remains aberrant in the chronic phase of stroke. A directed study of CBF in stroke is needed because reduced CBF (hypoperfusion) may occur in neural regions that appear anatomically intact and may impact cognitive functioning in stroke survivors. Hypoperfusion in neurologically-involved individuals may also affect BOLD signal in FMRI studies, complicating its interpretation with this population. The current study measured CBF in three chronic stroke survivors with ischemic infarcts (greater than 1 year post-stroke) to localize regions of hypoperfusion, and most critically, examine the CBF inflow curve using a methodology that has never, to our knowledge, been reported in the chronic stroke literature. CBF data acquired with a Pulsed Arterial Spin Labeling (PASL) flow-sensitive alternating inversion recovery (FAIR) technique indicated both delayed CBF inflow curve and hypoperfusion in the stroke survivors as compared to younger and elderly control participants. Among the stroke survivors, we observed regional hypoperfusion in apparently anatomically intact neural regions that are involved in cognitive functioning. These results may have profound implications for the study of behavioral deficits in chronic stroke, and particularly for studies using neuroimaging methods that rely on CBF to draw conclusions about underlying neural activity.

Multiphase Pseudocontinuous Arterial Spin Labeling (MP-PCASL) for Robust Quantification of Cerebral Blood Flow

Pseudocontinuous arterial spin labeling (PCASL) has been demonstrated to provide the sensitivity of the continuous arterial spin labeling method while overcoming many of the limitations of that method. Because the specification of the phases in the radiofrequency pulse train in PCASL defines the tag and control conditions of the flowing arterial blood, its tagging efficiency is sensitive to factors, such as off-resonance fields, that induce phase mismatches between the radiofrequency pulses and the flowing spins. As a result, the quantitative estimation of cerebral blood flow with PCASL can exhibit a significant amount of error when these factors are not taken into account. In this paper, the sources of the tagging efficiency loss are characterized and a novel PCASL method that utilizes multiple phase offsets is proposed to reduce the tagging efficiency loss in PCASL. Simulations are performed to evaluate the feasibility and the performance of the proposed method. Quantitative estimates of cerebral blood flow obtained with multiple phase offset PCASL are compared to estimates obtained with conventional PCASL and pulsed arterial spin labeling. Our results show that multiple phase offset PCASL provides robust cerebral blood flow quantification while retaining much of the sensitivity advantage of PCASL.

Cortical Depth-specific Microvascular Dilation Underlies Laminar Differences in Blood Oxygenation Level-dependent Functional MRI Signal

Changes in neuronal activity are accompanied by the release of vasoactive mediators that cause microscopic dilation and constriction of the cerebral microvasculature and are manifested in macroscopic blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signals. We used two-photon microscopy to measure the diameters of single arterioles and capillaries at different depths within the rat primary somatosensory cortex. These measurements were compared with cortical depth-resolved fMRI signal changes. Our microscopic results demonstrate a spatial gradient of dilation onset and peak times consistent with "upstream" propagation of vasodilation toward the cortical surface along the diving arterioles and "downstream" propagation into local capillary beds. The observed BOLD response exhibited the fastest onset in deep layers, and the "initial dip" was most pronounced in layer I. The present results indicate that both the onset of the BOLD response and the initial dip depend on cortical depth and can be explained, at least in part, by the spatial gradient of delays in microvascular dilation, the fastest response being in the deep layers and the most delayed response in the capillary bed of layer I.

Alcohol Effects on Cerebral Blood Flow in Subjects with Low and High Responses to Alcohol

Although there are multiple indications that alcohol can alter many physiological brain functions, including cerebral blood flow (CBF), studies of the latter have generally used small- or modest-sized samples. Few investigations have yet evaluated how CBF changes after alcohol relate to subsets of subjects with elevated alcoholism risks, such as those with lower levels of response (LR) to alcohol. This study used arterial spin labeling (ASL) after alcohol administration to evaluate a large sample of healthy young men and women with low and high alcohol responses, and, thus, varying risks for alcohol use disorders (AUD).

Accurate Reconstruction of Temporal Correlation for Neuronal Sources Using the Enhanced Dual-core MEG Beamformer

Beamformer spatial filters are commonly used to explore the active neuronal sources underlying magnetoencephalography (MEG) recordings at low signal-to-noise ratio (SNR). Conventional beamformer techniques are successful in localizing uncorrelated neuronal sources under poor SNR conditions. However, the spatial and temporal features from conventional beamformer reconstructions suffer when sources are correlated, which is a common and important property of real neuronal networks. Dual-beamformer techniques, originally developed by Brookes et al. to deal with this limitation, successfully localize highly-correlated sources and determine their orientations and weightings, but their performance degrades at low correlations. They also lack the capability to produce individual time courses and therefore cannot quantify source correlation. In this paper, we present an enhanced formulation of our earlier dual-core beamformer (DCBF) approach that reconstructs individual source time courses and their correlations. Through computer simulations, we show that the enhanced DCBF (eDCBF) consistently and accurately models dual-source activity regardless of the correlation strength. Simulations also show that a multi-core extension of eDCBF effectively handles the presence of additional correlated sources. In a human auditory task, we further demonstrate that eDCBF accurately reconstructs left and right auditory temporal responses and their correlations. Spatial resolution and source localization strategies corresponding to different measures within the eDCBF framework are also discussed. In summary, eDCBF accurately reconstructs source spatio-temporal behavior, providing a means for characterizing complex neuronal networks and their communication.

On Multiple Alternating Steady States Induced by Periodic Spin Phase Perturbation Waveforms

Direct measurement of neural currents by means of MRI can potentially open a high temporal resolution (10-100 ms) window applicable for monitoring dynamics of neuronal activity without loss of the high spatial resolution afforded by MRI. Previously, we have shown that the alternating balanced steady state imaging affords high sensitivity to weak periodic currents owing to its amplification of periodic spin phase perturbations. This technique, however, requires precise synchronization of such perturbations to the radiofrequency pulses. Herein, we extend alternating balanced steady state imaging to multiple balanced alternating steady states for estimation of neural current waveforms. Simulations and phantom experiments show that the off-resonance profile of the multiple alternating steady state signal carries information about the frequency content of driving waveforms. In addition, the method is less sensitive than alternating balanced steady state to precise waveform timing relative to radiofrequency pulses. Thus, multiple alternating steady state technique is potentially applicable to MR imaging of the waveforms of periodic neuronal activity. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc.

The Development of Event-related FMRI Designs

The diversity of experimental designs that can be used with functional magnetic resonance imaging (fMRI) has played a key role in its widespread application to studies of human cognition. This flexibility is possible because the fMRI response to external stimuli is remarkably well approximated as the response of a linear time variant system. The experimental demonstration of this property provided the foundation for the development of event-related designs, in which the fMRI response is modeled as the linear summation of the hemodynamic response to discrete events. Building upon prior work from the fields of engineering, neuroscience, and statistics, researchers in the field have created a rich collection of event-related designs and developed a rigorous theoretical framework for characterizing and optimizing the performance of designs. Ongoing challenges include the optimization of designs in the presence of experimental constraints and the development of more time-efficient optimization algorithms.

Pseudocontinuous Arterial Spin Labeling with Optimized Tagging Efficiency

The adiabatic inversion of blood in pseudocontinuous arterial spin labeling (PCASL) is highly sensitive to off-resonance effects and gradient imperfections and this sensitivity can lead to tagging efficiency loss and unpredictable variations in cerebral blood flow estimates. This efficiency loss is caused by a phase tracking error between the RF pulses and the flowing spins. This article introduces a new method, referred to as Optimized PCASL (OptPCASL), that minimizes the phase tracking error by applying an additional compensation RF phase term and in-plane gradients to the PCASL pulse train. The optimal RF phase and gradient amplitudes are determined using a prescan procedure, which consists of a series of short scans interleaved with automated postprocessing routines integrated to the scanner console. The prescan procedure is shown to minimize the phase tracking error in a robust and time efficient manner. As an example of its application, the use of OptPCASL for the improved detection of functional activation in the visual cortex is demonstrated and temporal signal-to-noise ratio (SNR), image SNR, and baseline cerebral blood flow measures are compared to those acquired from conventional PCASL. Magn Reson Med, 2011. © 2011 Wiley Periodicals, Inc.

Function Biomedical Informatics Research Network Recommendations for Prospective Multicenter Functional MRI Studies

This report provides practical recommendations for the design and execution of multicenter functional MRI (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The study was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multisite aspects include: (i) establishing and verifying scan parameters including scanner types and magnetic fields, (ii) establishing and monitoring of a scanner quality program, (iii) developing task paradigms and scan session documentation, (iv) establishing clinical and scanner training to ensure consistency over time, (v) developing means for uploading, storing, and monitoring of imaging and other data, (vi) the use of a traveling fMRI expert, and (vii) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery. J. Magn. Reson. Imaging 2012;. © 2012 Wiley Periodicals, Inc.

A Geometric View of Global Signal Confounds in Resting-state Functional MRI

Resting-state functional magnetic resonance imaging (fMRI) is proving to be an effective tool for mapping the long-range functional connections of the brain in both health and disease. One of the primary measures of connectivity is the correlation between the blood oxygenation level dependent (BOLD) time series observed in different brain regions. The computation of the correlation is often dominated by the presence of a strong global component that can introduce significant variability across functional connectivity maps acquired from different experimental scans or subjects. To address this issue, a variety of global signal correction methods have been proposed, but there is currently a lack of a clear consensus on the best approach to use. Furthermore, there has been concern that some global signal correction methods, such as global signal regression, may produce significant negative bias in the correlation values. In this paper we introduce a framework for visualizing the signal structure of resting-state fMRI data and characterizing the properties of the global signal. Using this framework, we demonstrate that a portion of the global signal can be viewed as an additive confound that increases with the mean BOLD amplitude. An approach for minimizing the contribution of this additive confound is presented, and an initial comparison with existing global signal correction methods is provided.

Caffeine Increases the Temporal Variability of Resting-state BOLD Connectivity in the Motor Cortex

Correlations between spontaneous fluctuations in the blood oxygenation level dependent (BOLD) signal measured with functional MRI are finding increasing use as measures of functional connectivity in the brain, where differences can potentially predict cognitive performance and diagnose disease. Caffeine, which is a widely consumed neural stimulant and vasoactive agent, has been found to decrease the amplitude and correlation of resting-state BOLD fluctuations, and hence is an important factor to consider in functional connectivity studies. However, because the BOLD signal is sensitive to neural and vascular factors, the physiological mechanisms by which caffeine alters spontaneous BOLD fluctuations remain unclear. Resting-state functional connectivity has traditionally been assessed using stationary measures, such as the correlation coefficient between BOLD signals measured across the length of a scan. However, recent work has shown that the correlation of resting-state networks can vary considerably over time, with periods as short as 10 s. In this study, we used a sliding window correlation analysis to assess temporal variations in resting-state functional connectivity of the motor cortex before and after caffeine ingestion. We found that the temporal variability of BOLD correlation was significantly higher following a caffeine dose, with transient periods of strong correlation alternating with periods of low or negative correlation. This phenomenon was primarily due to increased variability in the phase difference between BOLD time courses in the left and right motor cortices. These results indicate that caffeine may cause underlying spontaneous neural fluctuations to go in and out of coherence more frequently, and emphasizes the need to consider non-stationary measures when studying changes in functional connectivity.

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