scholarly journals Vascular origins of low‐frequency oscillations in the cerebrospinal fluid signal in resting‐state fMRI : Interpretation using photoplethysmography

2021 ◽  
Author(s):  
Ahmadreza Attarpour ◽  
James Ward ◽  
J. Jean Chen
2010 ◽  
Vol 117 (1) ◽  
pp. 13-20 ◽  
Author(s):  
Matthew J. Hoptman ◽  
Xi-Nian Zuo ◽  
Pamela D. Butler ◽  
Daniel C. Javitt ◽  
Debra D'Angelo ◽  
...  

2020 ◽  
Author(s):  
Ahmadreza Attarpour ◽  
James Ward ◽  
J. Jean Chen

AbstractSlow and rhythmic spontaneous oscillations of cerebral blood flow are well known to have diagnostic utility, notably frequencies of 0.008-0.03 Hz (B-waves) and 0.05-0.15Hz (Mayer waves or M waves). However, intracranial measurements of these oscillations have been difficult. Oscillations in the cerebrospinal fluid (CSF), which are influenced by the cardiac pulse wave, represent a possible avenue for non-invasively tracking these oscillations using resting-state functional MRI (rs-fMRI), and have been used to correct for vascular oscillations in rs-fMRI functional connectivity calculations. However, the relationship between low-frequency CSF and vascular oscillations is unclear. In this study, we investigate this relationship using fast simultaneous multi-slice rs-fMRI coupled with fingertip photoplethysmography (PPG). We not only extract B-wave and M-wave range spectral power from the PPG signal, but also derive the pulse-intensity ratio (PIR, a surrogate of slow blood-pressure oscillations), the second-derivative of the PPG (SDPPG, a surrogate of arterial stiffness) and heart-rate variability (HRV). The main findings of this study are: (1) signals in different CSF regions (ROIs) are not equivalent in their vascular contributions or in their associations with vascular and tissue rs-fMRI signals; (2) the PPG signal contains the highest signal contribution from the M-wave range, while PIR contains the highest signal contribution from the B-wave range; (3) in the low-frequency range, PIR is more strongly associated with rs-fMRI signal in the CSF than PPG itself, and than HRV and SDPPG; (4) PPG-related vascular oscillations only contribute to < 20% of the CSF signal in rs-fMRI, insufficient support for the assumption that low-frequency CSF signal fluctuations directly reflect vascular oscillations. These findings caution the use of CSF as a monolithic region for extracting physiological nuisance regressors in rs-fMRI applications. They also pave the way for using rs-fMRI in the CSF as a potential tool for tracking cerebrovascular health through, for instance the strong relationship between PIR and the CSF signal.


BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ye Eun Kim ◽  
Min Kyung Kim ◽  
Sang-il Suh ◽  
Ji Hyun Kim

Abstract Background Recent resting-state fMRI studies demonstrated functional dysconnectivity within the central pain matrix in migraineurs. This study aimed to investigate the spatial distribution and amplitude of low-frequency oscillations (LFOs) using fractional amplitude of low-frequency fluctuation (fALFF) analysis in migraine patients without aura, and to examine relationships between regional LFOs and clinical variables. Methods Resting-state fMRI data were obtained and preprocessed in 44 migraine patients without aura and 31 matched controls. fALFF was computed according to the original method, z-transformed for standardization, and compared between migraineurs and controls. Correlation analysis between regional fALFF and clinical variables was performed in migraineurs as well. Results Compared with controls, migraineurs had significant fALFF increases in bilateral ventral posteromedial (VPM) thalamus and brainstem encompassing rostral ventromedial medulla (RVM) and trigeminocervical complex (TCC). Regional fALFF values of bilateral VPM thalamus and brainstem positively correlated with disease duration, but not with migraine attack frequency or Migraine Disability Assessment Scale score. Conclusions We have provided evidence for abnormal LFOs in the brainstem including RVM/TCC and thalamic VPM nucleus in migraine without aura, implicating trigeminothalamic network oscillations in migraine pathophysiology. Our results suggest that enhanced LFO activity may underpin the interictal trigeminothalamic dysrhythmia that could contribute to the impairments of pain transmission and modulation in migraine. Given our finding of increasing fALFF in relation to increasing disease duration, the observed trigeminothalamic dysrhythmia may indicate either an inherent pathology leading to migraine headaches or a consequence of repeated attacks on the brain.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bradley Fitzgerald ◽  
Jinxia Fiona Yao ◽  
Thomas M. Talavage ◽  
Lia M. Hocke ◽  
Blaise deB Frederick ◽  
...  

AbstractA “carpet plot” is a 2-dimensional plot (time vs. voxel) of scaled fMRI voxel intensity values. Low frequency oscillations (LFOs) can be successfully identified from BOLD fMRI and used to study characteristics of neuronal and physiological activity. Here, we evaluate the use of carpet plots paired with a developed slope-detection algorithm as a means to study LFOs in resting state fMRI (rs-fMRI) data with the help of dynamic susceptibility contrast (DSC) MRI data. Carpet plots were constructed by ordering voxels according to signal delay time for each voxel. The slope-detection algorithm was used to identify and calculate propagation times, or “transit times”, of tilted vertical edges across which a sudden signal change was observed. We aim to show that this metric has applications in understanding LFOs in fMRI data, possibly reflecting changes in blood flow speed during the scan, and for evaluating alternative blood-tracking contrast agents such as inhaled CO2. We demonstrate that the propagations of LFOs can be visualized and automatically identified in a carpet plot as tilted lines of sudden intensity change. Resting state carpet plots produce edges with transit times similar to those of DSC carpet plots. Additionally, resting state carpet plots indicate that edge transit times vary at different time points during the scan.


2016 ◽  
Vol 614 ◽  
pp. 105-111 ◽  
Author(s):  
Li Wang ◽  
Qingmei Kong ◽  
Ke Li ◽  
Yunai Su ◽  
Yawei Zeng ◽  
...  

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