Previous studies have found that aperiodic, systemic low-frequency oscillations (sLFOs) are present in blood-oxygen-level-dependent (BOLD) data. These signals are in the same low frequency band as the "resting state" signal; however, they are distinct signals which represent non-neuronal, physiological oscillations. The same sLFOs are found in the periphery (i.e. finger tips) as changes in oxy/deoxy-hemoglobin concentration using concurrent near-infrared spectroscopy. Together, this evidence points toward an extra-cerebral origin of these sLFOs. If this is the case, it is expected that these sLFO signals would be found in the carotid arteries with time delays that precede the signals found in the brain. To test this hypothesis, we employed the publicly available MyConnectome dataset (a two-year longitudinal study of a single subject) to extract the sLFOs in the internal carotid arteries (ICAs) with the help of the T1/T2-weighted images. Significant, but negative, correlations were found between the LFO BOLD signals from the ICAs and (1) the global signal (GS), (2) the superior sagittal sinus, and (3) the jugulars. We found the consistent time delays between the sLFO signals from ICAs, GS and veins which coincide with the blood transit time through the cerebral vascular tree.

It is commonly believed that cerebrospinal fluid (CSF) movement is facilitated by blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF movement was recently found during non-rapid eye movement (NREM) sleep via functional MRI. This finding raises other fundamental questions: 1) the explanation of coupling between hemodynamic oscillations and CSF movement from fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF movement. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF movement through the lens of fMRI. Time delays between CSF movement and global hemodynamics were calculated. The observed delays between hemodynamics and CSF movement match those predicted by the model. Moreover, by conducting separate fMRI scans of the brain and neck, we confirmed the low frequency CSF movement at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF movement is facilitated by changes in cerebral blood volume mainly in the low frequency range, even when the individual is awake.

Elevated carbon dioxide (CO2) in breathing air is widely used as a vasoactive stimulus to assess cerebrovascular functions under hypercapnia (i.e., “stress test” for the brain). Blood-oxygen-level-dependent (BOLD) is a contrast mechanism used in functional magnetic resonance imaging (fMRI). BOLD is used to study CO2-induced cerebrovascular reactivity (CVR), which is defined as the voxel-wise percentage BOLD signal change per mmHg change in the arterial partial pressure of CO2 (PaCO2). Besides the CVR, two additional important parameters reflecting the cerebrovascular functions are the arrival time of arterial CO2 at each voxel, and the waveform of the local BOLD signal. In this study, we developed a novel analytical method to accurately calculate the arrival time of elevated CO2 at each voxel using the systemic low frequency oscillations (sLFO: 0.01-0.1 Hz) extracted from the CO2 challenge data. In addition, 26 candidate hemodynamic response functions (HRF) were used to quantitatively describe the temporal brain reactions to a CO2 stimulus. We demonstrated that our approach improved the traditional method by allowing us to accurately map three perfusion-related parameters: the relative arrival time of blood, the hemodynamic response function, and CVR during a CO2 challenge.

Background The systemic low‐frequency oscillation (sLFO) functional (f)MRI signals extracted from the internal carotid artery (ICA) and the superior sagittal sinus (SSS) are found to have valuable physiological information. Purpose 1) To further develop and validate a method utilizing these signals to measure the delay times from the ICAs and the SSS. 2) To establish the delay time as an effective perfusion biomarker that associates with cerebral circulation time (CCT). 3) To explore within subject variations, and the effects of gender and age on the delay times. Study Type Prospective. Subjects In all, 100 healthy adults (Human Connectome Project [HCP], age range 22–36 years, 54 females and 46 males), 56 healthy children (Adolescent Brain Cognitive Development project) were included. Field Strength/Sequence Echo planar imaging (EPI) sequence at 3T. Assessment The sLFO fMRI signals from the ICAs and the SSSs were extracted from the resting state fMRI data. The maximum cross‐correlation coefficients and their corresponding delay times were calculated. The gender and age differences of delay times were assessed statistically. Statistical Tests T‐tests were conducted to measure the gender differences. The Kruskal–Wallis test was used to detect age differences. Results Consistent and robust results were found from 80% of the 400 HCP scans included. Negative correlations (–0.67) between the ICA and the SSS signals were found with the ICA signal leading the SSS signal by ∼5 sec. Within subject variation was 2.23 sec at the 5% significance level. The delay times were not significantly different between genders (P = 0.9846, P = 0.2288 for the left and right ICA, respectively). Significantly shorter delay times (4.3 sec) were found in the children than in the adults (P < 0.01). Data Conclusion We have shown that meaningful perfusion information (ie, CCT) can be derived from the sLFO fMRI signals of the large blood vessels. Level of Evidence: 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:1504–1513.

Cerebral spinal fluid (CSF) plays an important role in the clearance of metabolic waste products from the brain, yet the driving forces of CSF flow are not fully understood. It is commonly believed that CSF flow is facilitated by the blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF flow was found recently during non-rapid eye movement sleep (NREM) sleep via functional MRI. However, questions remain regarding 1) the explanation of coupling between hemodynamic oscillations and CSF flow using fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF flow. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF flow through the lens of fMRI. We found that the observed delays between these two signals match those predicted by the model. Moreover, by conducting separated fMRI scans of the brain and neck, we confirmed the low frequency CSF flow at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF flow is facilitated by hemodynamic oscillations mainly in the low frequency range, even when the individual is awake.