Characterizing the modulation of resting-state fMRI metrics by baseline physiology.

The blood-oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal is commonly used to assess functional connectivity across brain regions, particularly in the resting state (rs-fMRI). However, the BOLD fMRI signal is not merely a representation of neural activity, but a combination of neural activity and vascular response. These aspects of the BOLD signal are easily influenced by systemic physiology, potentially biasing BOLD-based functional connectivity measurements. In this work, we focus on the following physiological modulators of the BOLD signal: cerebral blood flow (CBF), venous blood oxygenation, and cerebrovascular reactivity (CVR). We use simulations and experiments to examine the relationship between the physiological parameters and rs-fMRI functional connectivity measurements in three resting-state networks: default mode network, somatosensory network and visual network. By using the general linear model, we demonstrate that physiological modulators significantly impact functional connectivity measurements in these regions, but in a manner that depends on the interplay between signal- and noise-driven correlations. Moreover, we find that the physiological effects vary by brain region and depend on the range of physiological conditions probed; the associations are more complex than previously reported. The results confirm that it is important to account for the effect of physiological modulators when comparing resting-state fMRI metrics. We note that such modulatory effects may be amplified by disease conditions, which will warrant future investigations.

The Effect of Low-Frequency Physiological Correction on the Reproducibility and Specificity of Resting-State fMRI Metrics: Functional Connectivity, ALFF, and ReHo.

The resting-state fMRI (rs-fMRI) signal is affected by a variety of low-frequency physiological phenomena, including variations in cardiac-rate (CRV), respiratory-volume (RVT), and end-tidal CO2 (PETCO2). While these effects have become better understood in recent years, the impact that their correction has on the quality of rs-fMRI measurements has yet to be clarified. The objective of this paper is to investigate the effect of correcting for CRV, RVT and PETCO2 on the rs-fMRI measurements. Nine healthy subjects underwent a test-retest rs-fMRI acquisition using repetition times (TRs) of 2 s (long-TR) and 0.323 s (short-TR), and the data were processed using eight different physiological correction strategies. Subsequently, regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and resting-state connectivity of the motor and default-mode networks are calculated for each strategy. Reproducibility is calculated using intra-class correlation and the Dice Coefficient, while the accuracy of functional-connectivity measures is assessed through network separability, sensitivity and specificity. We found that: (1) the reproducibility of the rs-fMRI measures improved significantly after correction for PETCO2; (2) separability of functional networks increased after PETCO2 correction but was not affected by RVT and CRV correction; (3) the effect of physiological correction does not depend on the data sampling-rate; (4) the effect of physiological processes and correction strategies is network-specific. Our findings highlight limitations in our understanding of rs-fMRI quality measures, and underscore the importance of using multiple quality measures to determine the optimal physiological correction strategy.

Identifying Dysfunctional Cortex: Dissociable Effects of Stroke and Aging on Resting State Dynamics in MEG and fMRI.

Spontaneous signals in neuroimaging data may provide information on cortical health in disease and aging, but the relative sensitivity of different approaches is unknown. In the present study, we compared different but complementary indicators of neural dynamics in resting-state MEG and BOLD fMRI, and their relationship with blood flow. Participants included patients with post-stroke aphasia, age-matched controls, and young adults. The complexity of brain activity at rest was quantified in MEG using spectral analysis and multiscale entropy (MSE) measures, whereas BOLD variability was quantified as the standard deviation (SDBOLD), mean squared successive difference (MSSD), and sample entropy of the BOLD time series. We sought to assess the utility of signal variability and complexity measures as markers of age-related changes in healthy adults and perilesional dysfunction in chronic stroke. The results indicate that reduced BOLD variability is a robust finding in aging, whereas MEG measures are more sensitive to the cortical abnormalities associated with stroke. Furthermore, reduced complexity of MEG signals in perilesional tissue were correlated with hypoperfusion as assessed with arterial spin labeling (ASL), while no such relationship was apparent with BOLD variability. These findings suggest that MEG signal complexity offers a sensitive index of neural dysfunction in perilesional tissue in chronic stroke, and that these effects are clearly distinguishable from those associated with healthy aging.

Spin-Echo Resting-State Functional Connectivity in High-Susceptibility Regions: Accuracy, Reliability, and the Impact of Physiological Noise.

Gradient-echo (GE) echo-planar imaging (EPI) is the method of choice in blood-oxygenation level-dependent (BOLD) functional MRI (fMRI) studies, as it demonstrates substantially higher BOLD sensitivity than its spin-echo (SE) counterpart. However, it is also well known that the GE-EPI signal is prone to signal dropouts and shifts due to susceptibility effects near air-tissue interfaces. SE-EPI, in contrast, is minimally affected by these artifacts. In this study, we quantify, for the first time, the sensitivity and specificity of SE and GE EPI for resting-state fMRI functional connectivity (fcMRI) mapping, using the 1000-brain fcMRI atlas (Yeo et al., 2011 ) as the pseudoground truth. Moreover, we assess the influence of physiological processes on resting-state BOLD measured using both regular and ultrafast GE and SE acquisitions. Our work demonstrates that SE-EPI and GE-EPI are associated with similar sensitivities, specificities, and intersubject reproducibility in fcMRI for most brain networks, generated using both seed-based analysis and independent component analysis. More importantly, SE-based fcMRI measurements demonstrated significantly higher sensitivity, specificity, and intersubject reproducibility in high-susceptibility regions, spanning the limbic and frontal networks in the 1000-brain atlas. In addition, SE-EPI is significantly less sensitive to prominent sources of physiological noise, including low-frequency respiratory volume and heart rate variations. Our work suggests that SE-EPI should be increasingly adopted in the study of networks spanning susceptibility-affected brain regions, including those that are important to memory, language, and emotion.

The association between cerebrovascular reactivity and resting-state fMRI functional connectivity in healthy adults: The influence of basal carbon dioxide.

Although widely used in resting-state fMRI (fMRI) functional connectivity measurement (fcMRI), the BOLD signal is only an indirect measure of neuronal activity, and is inherently modulated by both neuronal activity and vascular physiology. For instance, cerebrovascular reactivity (CVR) varies widely across individuals irrespective of neuronal function, but the implications for fcMRI are currently unknown. This knowledge gap compromises our ability to correctly interpret fcMRI measurements. In this work, we investigate the relationship between CVR and resting fcMRI measurements in healthy young adults, in both the motor and the executive-control networks. We modulate CVR within each individual by subtly increasing and decreasing resting vascular tension through baseline end-tidal CO2 (PETCO2), and measure fcMRI during these hypercapnic, hypocapnic and normocapnic states. Furthermore, we assess the association between CVR and fcMRI within and across individuals. Within individuals, resting PETCO2 is found to significantly influence both CVR and resting fcMRI values. In addition, we find resting fcMRI to be significantly and positively associated with CVR across the group in both networks. This relationship is potentially mediated by concomitant alterations in BOLD signal fluctuation amplitude. This work clearly demonstrates and quantifies a major vascular modulator of resting fcMRI, one that is also subject and regional dependent. We suggest that individualized correction for CVR effects in fcMRI measurements is essential for fcMRI studies of healthy brains, and can be even more important in studying diseased brains.

Comparing cerebrovascular reactivity measured using BOLD and cerebral blood flow MRI: The effect of basal vascular tension on vasodilatory and vasoconstrictive reactivity.

Cerebrovascular reactivity (CVR) is an important metric of cerebrovascular health. While the BOLD fMRI method in conjunction with carbon-dioxide (CO2) based vascular manipulation has been the most commonly used, the BOLD signal is not a direct measure of vascular changes, and the use of arterial-spin labeling (ASL) cerebral blood flow (CBF) imaging is increasingly advocated. Nonetheless, given the differing dependencies of BOLD and CBF on vascular baseline conditions and the diverse CO2 manipulation types currently used in the literature, knowledge of potential biases introduced by each technique is critical for the interpretation of CVR measurements. In this work, we use simultaneous BOLD-CBF acquisitions during both vasodilatory (hypercapnic) and vasoconstrictive (hypocapnic) stimuli to measure CVR. We further imposed different levels of baseline vascular tension by inducing hypercapnic and hypocapnic baselines, separately from normocapnia by 4mmHg. We saw significant and diverse dependencies on vascular stimulus and baseline condition in both BOLD and CBF CVR measurements: (i) BOLD-based CVR is more sensitive to basal vascular tension than CBF-based CVR; (ii) the use of a combination of vasodilatory and vasoconstrictive stimuli maximizes the sensitivity of CBF-based CVR to vascular tension changes; (iii) the BOLD and CBF vascular response delays are both significantly lengthened at predilated baseline. As vascular tension can often be altered by potential pathology, our findings are important considerations when interpreting CVR measurements in health and disease.

Mapping the end-tidal CO2 response function in the resting-state BOLD fMRI signal: spatial specificity, test-retest reliability and effect of fMRI sampling rate.

The blood oxygenation level dependent (BOLD) signal measures brain function indirectly through physiological processes and hence is susceptible to global physiological changes. Specifically, fluctuations in end-tidal CO2 (PETCO2), in addition to cardiac rate variation (CRV), and respiratory volume per time (RVT) variations, have been known to confound the resting-state fMRI (rs-fMRI) signal. Previous studies addressed the resting-state fMRI response function to CRV and RVT, but no attempt has been made to directly estimate the voxel-wise response function to PETCO2. Moreover, the potential interactions among PETCO2, CRV, and RVT necessitate their simultaneous inclusion in a multi-regression model to estimate the PETCO2 response. In this study, we use such a model to estimate the voxel-wise PETCO2 response functions directly from rs-fMRI data of nine healthy subjects. We also characterized the effect of sampling rate (TR=2seconds vs. 323ms) on the temporal and spatial variability of the PETCO2 response function in addition to that of CRV and RVT. In addition, we assess the test-retest reproducibility of the response functions to PETCO2, CRV and RVT. We found that despite overlaps across their spatial patterns, PETCO2 explains a unique portion of the rs-fMRI signal variance compared to RVT and CRV. We also found the shapes of the estimated responses are very similar between long- and short-TR data, although responses estimated from short-TR data have higher reproducibility.