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      Cerebral circulation time derived from fMRI signals in large blood vessels

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          Abstract

          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. 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. Prospective. 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. Echo planar imaging (EPI) sequence at 3T. The sLFO fMRI signals from the ICAs and the SSSs were extracted from the resting state fMRI data. The maximum cross-correlation coef ficients and their corresponding delay times were calculated. The gender and age differences of delay times were assessed statistically. T -tests were conducted to measure the gender differences. The Kruskal–Wallis test was used to detect age differences. 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% signi ficance level. The delay times were not signi ficantly different between genders ( P = 0.9846, P = 0.2288 for the left and right ICA, respectively). Signi ficantly shorter delay times (4.3 sec) were found in the children than in the adults ( P < 0.01). We have shown that meaningful perfusion information (ie, CCT) can be derived from the sLFO fMRI signals of the large blood vessels. 1 1

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          What does fMRI tell us about neuronal activity?

          In recent years, cognitive neuroscientists have taken great advantage of functional magnetic resonance imaging (fMRI) as a non-invasive method of measuring neuronal activity in the human brain. But what exactly does fMRI tell us? We know that its signals arise from changes in local haemodynamics that, in turn, result from alterations in neuronal activity, but exactly how neuronal activity, haemodynamics and fMRI signals are related is unclear. It has been assumed that the fMRI signal is proportional to the local average neuronal activity, but many factors can influence the relationship between the two. A clearer understanding of how neuronal activity influences the fMRI signal is needed if we are correctly to interpret functional imaging data.
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            Direct, intraoperative observation of ~0.1 Hz hemodynamic oscillations in awake human cortex: implications for fMRI.

            An almost sinusoidal, large amplitude ~0.1 Hz oscillation in cortical hemodynamics has been repeatedly observed in species ranging from mice to humans. However, the occurrence of 'slow sinusoidal hemodynamic oscillations' (SSHOs) in human functional magnetic resonance imaging (fMRI) studies is rarely noted or considered. As a result, little investigation into the cause of SSHOs has been undertaken, and their potential to confound fMRI analysis, as well as their possible value as a functional biomarker has been largely overlooked. Here, we report direct observation of large-amplitude, sinusoidal ~0.1 Hz hemodynamic oscillations in the cortex of an awake human undergoing surgical resection of a brain tumor. Intraoperative multispectral optical intrinsic signal imaging (MS-OISI) revealed that SSHOs were spatially localized to distinct regions of the cortex, exhibited wave-like propagation, and involved oscillations in the diameter of specific pial arterioles, indicating that the effect was not the result of systemic blood pressure oscillations. fMRI data collected from the same subject 4 days prior to surgery demonstrates that ~0.1 Hz oscillations in the BOLD signal can be detected around the same region. Intraoperative optical imaging data from a patient undergoing epilepsy surgery, in whom sinusoidal oscillations were not observed, is shown for comparison. This direct observation of the '0.1 Hz wave' in the awake human brain, using both intraoperative imaging and pre-operative fMRI, confirms that SSHOs occur in the human brain, and can be detected by fMRI. We discuss the possible physiological basis of this oscillation and its potential link to brain pathologies, highlighting its relevance to resting-state fMRI and its potential as a novel target for functional diagnosis and delineation of neurological disease. © 2013. Published by Elsevier Inc. All rights reserved.
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              Tracking cerebral blood flow in BOLD fMRI using recursively generated regressors.

              BOLD functional MRI (fMRI) data are dominated by low frequency signals, many of them of unclear origin. We have recently shown that some portions of the low frequency oscillations found in BOLD fMRI are systemic signals closely related to the blood circulation (Tong et al. [2013]: NeuroImage 76:202-215). They are commonly treated as physiological noise in fMRI studies. In this study, we propose and test a novel data-driven analytical method that uses these systemic low frequency oscillations in the BOLD signal as a tracer to follow cerebral blood flow dynamically. Our findings demonstrate that: (1) systemic oscillations pervade the BOLD signal; (2) the temporal traces evolve as the blood propagates though the brain; and, (3) they can be effectively extracted via a recursive procedure and used to derive the cerebral circulation map. Moreover, this method is independent from functional analyses, and thus allows simultaneous and independent assessment of information about cerebral blood flow to be conducted in parallel with the functional studies. In this study, the method was applied to data from the resting state scans, acquired using a multiband EPI sequence (fMRI scan with much shorter TRs), of seven healthy participants. Dynamic maps with consistent features resembling cerebral blood circulation were derived, confirming the robustness and repeatability of the method. Copyright © 2014 Wiley Periodicals, Inc.
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                Author and article information

                Journal
                Journal of Magnetic Resonance Imaging
                J Magn Reson Imaging
                Wiley
                1053-1807
                1522-2586
                April 29 2019
                April 29 2019
                Affiliations
                [1 ]Weldon School of Biomedical Engineering, Purdue University West Lafayette Indiana USA
                [2 ]Institute of Electrical Engineering, Yanshan University Yanshan China
                [3 ]Indiana University School of MedicineDepartment of Neurosurgery and Goodman Campbell Brain and Spine Indianapolis Indiana USA
                Article
                10.1002/jmri.26765
                7171696
                31034667
                b50d55d9-9ded-4fe9-a7bd-66f3ce0a4847
                © 2019

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