A novel method of combining blood oxygenation and blood flow sensitive magnetic resonance imaging techniques to measure the cerebral blood flow and oxygen metabolism responses to an unknown neural stimulus

Developmental patterns of CBF and BOLD responses to visual stimulus

To investigate the developmental changes of cerebral blood flow (CBF) and hemodynamic responses to changing neural activity, we used the arterial spin label (ASL) technique to measure resting CBF and simultaneous CBF / blood-oxygen-level dependent (BOLD) signal changes during visual stimulation in 97 typically developing children and young adults (age 13.35 [6.02, 25.25] (median [min, max]) years old at the first time point). The longitudinal study protocol included three MRIs (2.7 ± 0.06 obtained), one year apart, for each participant. Mixed-effect linear and non-linear statistical models were used to analyze age effects on CBF and BOLD signals. Resting CBF decreased exponentially with age (p = 0.0001) throughout the brain, and developmental trajectories differed across brain lobes. The absolute CBF increase in visual cortex during stimulation was constant over the age range, but the fractional CBF change increased with age (p = 0.0001) and the fractional BOLD signal increased with age (p = 0.0001) correspondingly. These findings suggest that the apparent neural hemodynamic coupling in visual cortex does not change after age six years, but age-related BOLD signal changes continue through adolescence primarily due to the changes with age in resting CBF.

Direct imaging of functional networks

In blood-oxygenation-level-dependent functional magnetic resonance imaging (fMRI), current methods typically acquire ∼ 500,000 imaging voxels at each time point, and then use computer algorithms to reduce this data to the coefficients of a few hundred parcels or networks. This suggests that the amount of relevant information present in the fMRI signal is relatively small, and presents an opportunity to greatly improve the speed and signal to noise ratio (SNR) of the fMRI process. In this work, a theoretical framework is presented for calculating the coefficients of functional networks directly from highly undersampled fMRI data. Using predefined functional parcellations or networks and a compact k-space trajectory that samples data at optimal spatial scales, the problem of estimating network coefficients is reformulated to allow for direct least squares estimation, without Fourier encoding. By simulation, this approach is shown to allow for acceleration of the imaging process under ideal circumstances by nearly three orders of magnitude.

Understanding the dynamic relationship between cerebral blood flow and the BOLD signal: Implications for quantitative functional MRI

Calibrated BOLD imaging, in which traditional measurements of the BOLD signal are combined with measurements of cerebral blood flow (CBF) within a BOLD biophysical model to estimate changes in oxygen metabolism (CMRO2), has been a valuable tool for untangling the physiological processes associated with neural stimulus-induced BOLD activation. However, to date this technique has largely been applied to the study of essentially steady-state physiological changes (baseline to activation) associated with block-design stimuli, and it is unclear whether this approach may be directly extended to the study of more dynamic, naturalistic experimental designs. In this study we tested an assumption underlying this technique whose validity is critical to the application of calibrated BOLD to the study of more dynamic stimuli, that information about fluctuations in venous cerebral blood volume (CBVv) can be captured indirectly by measuring fluctuations in CBF, making the independent measurement of CBVv unnecessary. To accomplish this, simultaneous arterial spin labeling and BOLD imaging were used to measure the CBF and BOLD responses to flickering checkerboards with contrasts that oscillated continuously with frequencies of ~0.02-0.16Hz. The measurements were then fit to a dynamic physiological model of the BOLD response in order to explore the range of consistent CMRO2 and CBVv responses. We found that the BOLD and CBF responses were most consistent with relatively tight dynamic coupling between CBF and CMRO2 and a CBVv response that was an order of magnitude slower than either CBF or CMRO2. This finding suggests that the assumption of tight flow-volume coupling may not be strictly valid, complicating the extension of calibrated BOLD to more naturalistic experimental designs.

Effects of background suppression on the sensitivity of dual-echo arterial spin labeling MRI for BOLD and CBF signal changes

Dual-echo arterial spin labeling (DE-ASL) enables the simultaneous acquisition of BOLD and CBF fMRI data and is often used for calibrated BOLD and cerebrovascular CO2 reactivity measurements. DE-ASL, like all ASL techniques, suffers from a low intrinsic CBF SNR, which can be improved by suppressing the background signal via the inclusion of additional inversion pulses. However, until now this approach has been considered to be undesirable for DE-ASL, because the BOLD signal is extracted from the background signal and attenuating the background signal could decrease the sensitivity of DE-ASL scans for BOLD changes. In this study, the effect of background suppression on the sensitivity of DE-ASL MRI for BOLD and CBF signal changes with a visual stimulation paradigm was studied. Results showed that with an average background suppression level of 70% the BOLD sensitivity of DE-ASL MRI decreases slightly (15%), while the CBF sensitivity of the scans increased by almost a factor-of-two (81%). These findings support the conclusion that the gains in CBF sensitivity of DE-ASL MRI due to background suppression outweigh the slight decrease in sensitivity of these scans for BOLD changes, and thus that background suppression is highly recommended for DE-ASL.

Variability of the coupling of blood flow and oxygen metabolism responses in the brain: a problem for interpreting BOLD studies but potentially a new window on the underlying neural activity

Recent studies from our group and others using quantitative fMRI methods have found that variations of the coupling ratio of blood flow (CBF) and oxygen metabolism (CMRO2) responses to a stimulus have a strong effect on the BOLD response. Across a number of studies an empirical pattern is emerging in the way CBF and CMRO2 changes are coupled to neural activation: if the stimulus is modulated to create a stronger response (e.g., increasing stimulus contrast), CBF is modulated more than CMRO2; on the other hand, if the brain state is altered such that the response to the same stimulus is increased (e.g., modulating attention, adaptation, or excitability), CMRO2 is modulated more than CBF. Because CBF and CMRO2 changes conflict in producing BOLD signal changes, this finding has an important implication for conventional BOLD-fMRI studies: the BOLD response exaggerates the effects of stimulus variation but is only weakly sensitive to modulations of the brain state that alter the response to a standard stimulus. A speculative hypothesis is that variability of the coupling ratio of the CBF and CMRO2 responses reflects different proportions of inhibitory and excitatory evoked activity, potentially providing a new window on neural activity in the human brain.

A New Functional MRI Approach for Investigating Modulations of Brain Oxygen Metabolism

Functional MRI (fMRI) using the blood oxygenation level dependent (BOLD) signal is a common technique in the study of brain function. The BOLD signal is sensitive to the complex interaction of physiological changes including cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral oxygen metabolism (CMRO₂). A primary goal of quantitative fMRI methods is to combine BOLD imaging with other measurements (such as CBF measured with arterial spin labeling) to derive information about CMRO₂. This requires an accurate mathematical model to relate the BOLD signal to the physiological and hemodynamic changes; the most commonly used of these is the Davis model. Here, we propose a new nonlinear model that is straightforward and shows heuristic value in clearly relating the BOLD signal to blood flow, blood volume and the blood flow-oxygen metabolism coupling ratio. The model was tested for accuracy against a more detailed model adapted for magnetic fields of 1.5, 3 and 7T. The mathematical form of the heuristic model suggests a new ratio method for comparing combined BOLD and CBF data from two different stimulus responses to determine whether CBF and CMRO₂ coupling differs. The method does not require a calibration experiment or knowledge of parameter values as long as the exponential parameter describing the CBF-CBV relationship remains constant between stimuli. The method was found to work well for 1.5 and 3T but is prone to systematic error at 7T. If more specific information regarding changes in CMRO₂ is required, then with accuracy similar to that of the Davis model, the heuristic model can be applied to calibrated BOLD data at 1.5T, 3T and 7T. Both models work well over a reasonable range of blood flow and oxygen metabolism changes but are less accurate when applied to a simulated caffeine experiment in which CBF decreases and CMRO₂ increases.

Adaptation of cerebral oxygen metabolism and blood flow and modulation of neurovascular coupling with prolonged stimulation in human visual cortex

Prolonged visual stimulation results in neurophysiologic and hemodynamic adaptation. However, the hemodynamic adaptation appears to be small compared to neural adaptation. It is not clear how the cerebral metabolic rate of oxygen (CMRO2) is affected by adaptation. We measured cerebral blood flow (CBF) and CMRO2 change in responses to peripheral stimulation either continuously, or intermittently (on/off cycles). A linear system's response to the continuous input should be equal to the sum of the original response to the intermittent input and a version of that response shifted by half a cycle. The CMRO2 response showed a large non-linearity consistent with adaptation, the CBF response adapted to a lesser degree, and the blood oxygenation level dependent (BOLD) response was nearly linear. The metabolic response was coupled with a larger flow in the continuous condition than in the intermittent condition. Our results suggest that contrast adaptation improves energy economy of visual processing. However BOLD modulations may not accurately represent the underlying metabolic nonlinearity due to modulation of the coupling of blood flow and oxygen metabolism changes.