Self-gated 3D stack-of-spirals UTE pulmonary imaging at 0.55T.

PURPOSE: To develop an isotropic high-resolution stack-of-spirals UTE sequence for pulmonary imaging at 0.55 Tesla by leveraging a combination of robust respiratory-binning, trajectory correction, and concomitant-field corrections. METHODS: A stack-of-spirals golden-angle UTE sequence was used to continuously acquire data for 15.5 minutes. The data was binned to a stable respiratory phase based on superoinferior readout self-navigator signals. Corrections for trajectory errors and concomitant field artifacts, along with image reconstruction with conjugate gradient SENSE, were performed inline within the Gadgetron framework. Finally, data were retrospectively reconstructed to simulate scan times of 5, 8.5, and 12 minutes. Image quality was assessed using signal-to-noise, image sharpness, and qualitative reader scores. The technique was evaluated in healthy volunteers, patients with coronavirus disease 2019 infection, and patients with lung nodules. RESULTS: The technique provided diagnostic quality images with parenchymal lung SNR of 3.18 ± 0.0.60, 4.57 ± 0.87, 5.45 ± 1.02, and 5.89 ± 1.28 for scan times of 5, 8.5, 12, and 15.5 minutes, respectively. The respiratory binning technique resulted in significantly sharper images (p < 0.001) as measured with relative maximum derivative at the diaphragm. Concomitant field corrections visibly improved sharpness of anatomical structures away from iso-center. The image quality was maintained with a slight loss in SNR for simulated scan times down to 8.5 minutes. Inline image reconstruction and artifact correction were achieved in <5 minutes. CONCLUSION: The proposed pulmonary imaging technique combined efficient stack-of-spirals imaging with robust respiratory binning, concomitant field correction, and trajectory correction to generate diagnostic quality images with 1.75 mm isotropic resolution in 8.5 minutes on a high-performance 0.55 Tesla system.

Oxygen-enhanced functional lung imaging using a contemporary 0.55 T MRI system.

The purpose of this study was to evaluate oxygen-enhanced pulmonary imaging at 0.55 T with 3D stack-of-spirals ultrashort-TE (UTE) acquisition. Oxygen-enhanced pulmonary MRI offers the measurement of regional lung ventilation and perfusion using inhaled oxygen as a contrast agent. Low-field MRI systems equipped with contemporary hardware can provide high-quality structural lung imaging by virtue of the prolonged T2 *. Fortuitously, the T1 relaxivity of oxygen increases at lower field strengths, which is expected to improve the sensitivity of oxygen-enhanced lung MRI. We implemented a breath-held T1 -weighted 3D stack-of-spirals UTE acquisition with a 7 ms spiral-out readout. Measurement repeatability was assessed using five repetitions of oxygen-enhanced lung imaging in healthy volunteers (n = 7). The signal intensity at both normoxia and hyperoxia was strongly dependent on lung tissue density modulated by breath-hold volume during the five repetitions. A voxel-wise correction for lung tissue density improved the repeatability of percent signal enhancement maps (coefficient of variation = 34 ± 16%). Percent signal enhancement maps were compared in 15 healthy volunteers and 10 patients with lymphangioleiomyomatosis (LAM), a rare cystic disease known to reduce pulmonary function. We measured a mean percent signal enhancement of 9.0 ± 3.5% at 0.55 T in healthy volunteers, and reduced signal enhancement in patients with LAM (5.4 ± 4.8%, p = 0.02). The heterogeneity, estimated by the percent of lung volume exhibiting low enhancement, was significantly increased in patients with LAM compared with healthy volunteers (11.1 ± 6.0% versus 30.5 ± 13.1%, p = 0.01), illustrating the capability to measure regional functional deficits.

Simultaneous multislice rapid magnetic resonance elastography of the liver.

To design and validate a rapid Simultaneous Multi-slice (SMS) Magnetic Resonance Elastography technique (MRE), which combines SMS acquisition, in-plane undersampling and an existing rapid Magnetic Resonance Elastography (MREr) scheme to allow accelerated data acquisition in healthy volunteers and comparison against MREr. SMS-MREr sequence was developed by incorporating SMS acquisition scheme into an existing MREr sequence that accelerates MRE acquisition by acquiring data during opposite phases of mechanical vibrations. The MREr sequence accelerated MRE acquisition by acquiring data during opposite phases of mechanical vibrations. Liver MRE was performed on 23 healthy subjects using MREr and SMS-MREr sequences, and mean stiffness values were obtained for manually drawn regions of interest. Linear correlation and agreement between MREr- and SMS-MREr-based stiffness values were investigated. SMS-MREr reduced the scan time by half relative to MREr, and allowed acquisition of four-slice MRE data in a single 17-second breath-hold. Visual comparison suggested agreement between MREr and SMS-MREr elastograms. A Pearson's correlation of 0.93 was observed between stiffness values derived from MREr and SMS-MREr. Bland-Altman analysis demonstrated good agreement, with -0.08 kPa mean bias and narrow limits of agreement (95% CI: 0.23 to -0.39 kPa) between stiffness values obtained using MREr and SMS-MREr. SMS can be combined with other fast MRE approaches to achieve further acceleration. This pushes the limit on the acceleration that can be achieved in MRE acquisition, and makes it possible to conduct liver MRE exams in a single breath-hold.

Opportunities in Interventional and Diagnostic Imaging by Using High-Performance Low-Field-Strength MRI.

Background Commercial low-field-strength MRI systems are generally not equipped with state-of-the-art MRI hardware, and are not suitable for demanding imaging techniques. An MRI system was developed that combines low field strength (0.55 T) with high-performance imaging technology. Purpose To evaluate applications of a high-performance low-field-strength MRI system, specifically MRI-guided cardiovascular catheterizations with metallic devices, diagnostic imaging in high-susceptibility regions, and efficient image acquisition strategies. Materials and Methods A commercial 1.5-T MRI system was modified to operate at 0.55 T while maintaining high-performance hardware, shielded gradients (45 mT/m; 200 T/m/sec), and advanced imaging methods. MRI was performed between January 2018 and April 2019. T1, T2, and T2* were measured at 0.55 T; relaxivity of exogenous contrast agents was measured; and clinical applications advantageous at low field were evaluated. Results There were 83 0.55-T MRI examinations performed in study participants (45 women; mean age, 34 years ± 13). On average, T1 was 32% shorter, T2 was 26% longer, and T2* was 40% longer at 0.55 T compared with 1.5 T. Nine metallic interventional devices were found to be intrinsically safe at 0.55 T (<1°C heating) and MRI-guided right heart catheterization was performed in seven study participants with commercial metallic guidewires. Compared with 1.5 T, reduced image distortion was shown in lungs, upper airway, cranial sinuses, and intestines because of improved field homogeneity. Oxygen inhalation generated lung signal enhancement of 19% ± 11 (standard deviation) at 0.55 T compared with 7.6% ± 6.3 at 1.5 T (P = .02; five participants) because of the increased T1 relaxivity of oxygen (4.7e-4 mmHg-1sec-1). Efficient spiral image acquisitions were amenable to low field strength and generated increased signal-to-noise ratio compared with Cartesian acquisitions (P < .02). Representative imaging of the brain, spine, abdomen, and heart generated good image quality with this system. Conclusion This initial study suggests that high-performance low-field-strength MRI offers advantages for MRI-guided catheterizations with metal devices, MRI in high-susceptibility regions, and efficient imaging. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Grist in this issue.

Detection of neural light-scattering activity in vivo: optical transmittance studies in the rat brain.

Optical studies of ex vivo brain slices where blood is absent show that neural activity is accompanied by significant intrinsic optical signals (IOS) related to activity-dependent scattering changes in neural tissue. However, the neural scattering signals have been largely ignored in vivo in widely-used IOS methods where absorption contrast from hemoglobin was employed. Changes in scattering were observed on a time scale of seconds in previous brain slice IOS studies, similar to the time scale for the hemodynamic response. Therefore, potential crosstalk between the scattering and absorption changes may not be ignored if they have comparable contributions to IOS. In vivo, the IOS changes linked to neural scattering have been elusive. To isolate neural scattering signals in vivo, we employed 2 implantable optodes for small-separation (2 mm) transmission measurements of local brain tissue in anesthetized rats. This unique geometry enables us to separate neuronal activity-related changes in neural tissue scattering from changes in blood absorption based upon the direction of the signal change. The changes in IOS scattering and absorption in response to up-states of spontaneous neuronal activity in cortical or subcortical structures have strong correlation to local field potentials, but significantly different response latencies. We conclude that activity-dependent neural tissue scattering in vivo may be an additional source of contrast for functional brain studies that provides complementary information to other optical or MR-based systems that are sensitive to hemodynamic contrast.

Cardiovascular magnetic resonance elastography: A review.

Cardiovascular diseases are the leading cause of death worldwide. These cardiovascular diseases are associated with mechanical changes in the myocardium and aorta. It is known that stiffness is altered in many diseases, including the spectrum of ischemia, diastolic dysfunction, hypertension and hypertrophic cardiomyopathy. In addition, the stiffness of the aortic wall is altered in multiple diseases, including hypertension, coronary artery disease and aortic aneurysm formation. For example, in diastolic dysfunction in which the ejection fraction is preserved, stiffness can potentially be an important biomarker. Similarly, in aortic aneurysms, stiffness can provide valuable information with regard to rupture potential. A number of studies have addressed invasive and non-invasive approaches to test and measure the mechanical properties of the myocardium and aorta. One of the non-invasive approaches is magnetic resonance elastography (MRE). MRE is a phase-contrast magnetic resonance imaging technique that measures tissue stiffness non-invasively. This review article highlights the technical details and application of MRE in the quantification of myocardial and aortic stiffness in different disease states.

Functional Connectivity Alterations in Epilepsy from Resting-State Functional MRI.

The study of functional brain connectivity alterations induced by neurological disorders and their analysis from resting state functional Magnetic Resonance Imaging (rfMRI) is generally considered to be a challenging task. The main challenge lies in determining and interpreting the large-scale connectivity of brain regions when studying neurological disorders such as epilepsy. We tackle this challenging task by studying the cortical region connectivity using a novel approach for clustering the rfMRI time series signals and by identifying discriminant functional connections using a novel difference statistic measure. The proposed approach is then used in conjunction with the difference statistic to conduct automatic classification experiments for epileptic and healthy subjects using the rfMRI data. Our results show that the proposed difference statistic measure has the potential to extract promising discriminant neuroimaging markers. The extracted neuroimaging markers yield 93.08% classification accuracy on unseen data as compared to 80.20% accuracy on the same dataset by a recent state-of-the-art algorithm. The results demonstrate that for epilepsy the proposed approach confirms known functional connectivity alterations between cortical regions, reveals some new connectivity alterations, suggests potential neuroimaging markers, and predicts epilepsy with high accuracy from rfMRI scans.

Comparative analysis of classifiers for developing an adaptive computer-assisted EEG analysis system for diagnosing epilepsy.

Computer-assisted analysis of electroencephalogram (EEG) has a tremendous potential to assist clinicians during the diagnosis of epilepsy. These systems are trained to classify the EEG based on the ground truth provided by the neurologists. So, there should be a mechanism in these systems, using which a system's incorrect markings can be mentioned and the system should improve its classification by learning from them. We have developed a simple mechanism for neurologists to improve classification rate while encountering any false classification. This system is based on taking discrete wavelet transform (DWT) of the signals epochs which are then reduced using principal component analysis, and then they are fed into a classifier. After discussing our approach, we have shown the classification performance of three types of classifiers: support vector machine (SVM), quadratic discriminant analysis, and artificial neural network. We found SVM to be the best working classifier. Our work exhibits the importance and viability of a self-improving and user adapting computer-assisted EEG analysis system for diagnosing epilepsy which processes each channel exclusive to each other, along with the performance comparison of different machine learning techniques in the suggested system.

Microembolism induces anhedonia but no detectable changes in white matter integrity in aged rats.

Microvascular disease leads to alterations of cerebral vasculature including the formation of microembolic (ME) strokes. Though ME are associated with changes in mood and the severity and progression of cognitive decline, the effect of ME strokes on cerebral microstructure and its relationship to behavioral endpoints is unknown. Here, we used adult and aged male rats to test the hypotheses that ME lesions result in subtle changes to white and gray matter integrity as detected by high-throughput diffusion tensor imaging (DTI) and that these structural disruptions correspond to behavioral deficits. Two weeks post-surgery, aged animals showed depressive-like behaviors in the sucrose consumption test in the absence of altered cerebral diffusivity as assessed by ex-vivo DTI. Furthermore, DTI indices did not correlate with the degree of behavioral disruption in aged animals or in a subset of animals with observed tissue cavitation and subtle DTI alterations. Together, data suggest that behavioral deficits are not the result of damage to brain regions or white matter tracts, rather the activity of other systems may underlie functional disruption and recovery.

Robust data driven model order estimation for independent component analysis of FMRI data with low contrast to noise.

Independent component analysis (ICA) has been successfully utilized for analysis of functional MRI (fMRI) data for task related as well as resting state studies. Although it holds the promise of becoming an unbiased data-driven analysis technique, a few choices have to be made prior to performing ICA, selection of a method for determining the number of independent components (nIC) being one of them. Choice of nIC has been shown to influence the ICA maps, and various approaches (mostly relying on information theoretic criteria) have been proposed and implemented in commonly used ICA analysis packages, such as MELODIC and GIFT. However, there has been no consensus on the optimal method for nIC selection, and many studies utilize arbitrarily chosen values for nIC. Accurate and reliable determination of true nIC is especially important in the setting where the signals of interest contribute only a small fraction of the total variance, i.e. very low contrast-to-noise ratio (CNR), and/or very focal response. In this study, we evaluate the performance of different model order selection criteria and demonstrate that the model order selected based upon bootstrap stability of principal components yields more reliable and accurate estimates of model order. We then demonstrate the utility of this fully data-driven approach to detect weak and focal stimulus-driven responses in real data. Finally, we compare the performance of different multi-run ICA approaches using pseudo-real data.

Mapping of the mouse olfactory system with manganese-enhanced magnetic resonance imaging and diffusion tensor imaging.

As the power of studying mouse genetics and behavior advances, research tools to examine systems level connectivity in the mouse are critically needed. In this study, we compared statistical mapping of the olfactory system in adult mice using manganese-enhanced MRI (MEMRI) and diffusion tensor imaging (DTI) with probabilistic tractography. The primary goal was to determine whether these complementary techniques can determine mouse olfactory bulb (OB) connectivity consistent with known anatomical connections. For MEMRI, 3D T1-weighted images were acquired before and after bilateral nasal administration of MnCl(2) solution. Concomitantly, high-resolution diffusion-tensor images were obtained ex vivo from a second group of mice and processed with a probabilistic tractography algorithm originating in the OB. Incidence maps were created by co-registering and overlaying data from the two scan modalities. The resulting maps clearly show pathways between the OB and amygdala, piriform cortex, caudate putamen, and olfactory cortex in both the DTI and MEMRI techniques that are consistent with the known anatomical connections. These data demonstrate that MEMRI and DTI are complementary, high-resolution neuroimaging tools that can be applied to mouse genetic models of olfactory and limbic system connectivity.

A DTI tractography analysis of infralimbic and prelimbic connectivity in the mouse using high-throughput MRI.

BACKGROUND: High throughput, brain-wide analysis of neural circuit connectivity is needed to understand brain function across species. Combining such tractography techniques with small animal models will allow more rapid integration of systems neuroscience with molecular genetic, behavioral, and cellular approaches. METHODS: We collected DTI and T2 scans on 3 series of 6 fixed mouse brains ex vivo in a 9.4 Tesla magnet. The DTI analysis of ten mouse brains focused on comparing prelimbic (PL) and Infralimbic (IL) probabilistic tractography. To validate the DTI results a preliminary set of 24 additional mice were injected with BDA into the IL and PL. The DTI results and preliminary BDA results were also compared to previously published rat connectivity. RESULTS: We focused our analyses on the connectivity of the mouse prelimbic (PL) vs. infralimbic (IL) cortices. We demonstrated that this DTI analysis is consistent across scanned mice, with prior analyses of rat IL/PL connectivity, and with mouse PL and IL projections using the BDA tracer. CONCLUSIONS: High-throughput ex vivo DTI imaging in the mouse delineated both common and differential connectivity of the IL and PL cortex. The scanning methodology provided a balance of tissue contrast, signal-to-noise ratio, resolution and throughput. Our results are largely consistent with previously published anterograde staining techniques in rats, and the preliminary tracer study of the mouse IL and PL provided here.

Spatiotemporal dynamics of low frequency BOLD fluctuations in rats and humans.

Most studies involving spontaneous fluctuations in the BOLD signal extract connectivity patterns that show relationships between brain areas that are maintained over the length of the scanning session. In this study, however, we examine the spatiotemporal dynamics of the BOLD fluctuations to identify common patterns of propagation within a scan. A novel pattern finding algorithm was developed for detecting repeated spatiotemporal patterns in BOLD fMRI data. The algorithm was applied to high temporal resolution T2*-weighted multislice images obtained from rats and humans in the absence of any task or stimulation. In rats, the primary pattern consisted of waves of high signal intensity, propagating in a lateral to medial direction across the cortex, replicating our previous findings (Majeed et al., 2009a). These waves were observed primarily in sensorimotor cortex, but also extended to visual and parietal association areas. A secondary pattern, confined to subcortical regions consisted of an initial increase and subsequent decrease in signal intensity in the caudate-putamen. In humans, the most common spatiotemporal pattern consisted of an alteration between activation of areas comprising the "default-mode" (e.g., posterior cingulate and anterior medial prefrontal cortices) and the "task-positive" (e.g., superior parietal and premotor cortices) networks. Signal propagation from focal starting points was also observed. The pattern finding algorithm was shown to be reasonably insensitive to the variation in user-defined parameters, and the results were consistent within and between subjects. This novel approach for probing the spontaneous network activity of the brain has implications for the interpretation of conventional functional connectivity studies, and may increase the amount of information that can be obtained from neuroimaging data.

Broadband local field potentials correlate with spontaneous fluctuations in functional magnetic resonance imaging signals in the rat somatosensory cortex under isoflurane anesthesia.

Resting-state functional magnetic resonance imaging (fMRI) is widely used for exploring spontaneous brain activity and large-scale networks; however, the neural processes underlying the observed resting-state fMRI signals are not fully understood. To investigate the neural correlates of spontaneous low-frequency fMRI fluctuations and functional connectivity, we developed a rat model of simultaneous fMRI and multiple-site intracortical neural recordings. This allowed a direct comparison to be made between the spontaneous signals and interhemispheric connectivity measured with the two modalities. Results show that low-frequency blood oxygen level-dependent (BOLD) fluctuations (<0.1 Hz) correlate significantly with slow power modulations (<0.1 Hz) of local field potentials (LFPs) in a broad frequency range (1-100 Hz) under isoflurane anesthesia (1%-1.8%). Peak correlation occurred between neural and hemodynamic activity when the BOLD signal was delayed by ~4 sec relative to the LFP signal. The spatial location and extent of correlation was highly reproducible across studies, with the maximum correlation localized to a small area surrounding the site of microelectrode recording and to the homologous area in the contralateral hemisphere for most rats. Interhemispheric connectivity was calculated using BOLD correlation and band-limited LFP (1-4, 4-8, 8-14, 14-25, 25-40, and 40-100 Hz) coherence. Significant coherence was observed for the slow power changes of all LFP frequency bands as well as in the low-frequency BOLD data. A preliminary investigation of the effect of anesthesia on interhemispheric connectivity indicates that coherence in the high-frequency LFP bands declines with increasing doses of isoflurane, whereas coherence in the low-frequency LFP bands and the BOLD signal increases. These findings suggest that resting-state fMRI signals might be a reflection of broadband LFP power modulation, at least in isoflurane-anesthetized rats.

Functional connectivity in blood oxygenation level-dependent and cerebral blood volume-weighted resting state functional magnetic resonance imaging in the rat brain.

PURPOSE: To directly compare functional connectivity and spatiotemporal dynamics acquired with blood oxygenation level-dependent (BOLD) and cerebral blood volume (CBV)-weighted functional magnetic resonance imaging (fMRI) in anesthetized rats. MATERIALS AND METHODS: A series of BOLD images were acquired in 10 rats followed by CBV-weighted images created by injection of ultrasmall iron oxide particles. Functional connectivity, spectral information, and spatiotemporal dynamics were compared for the BOLD and CBV-weighted resting state scans. RESULTS: BOLD scans exhibited higher cross-correlation values compared to CBV-weighted scans, but the spatial patterns of correlation were similar. The BOLD spectrum contains power evenly distributed throughout the low-frequency range while the CBV power spectrum exhibited a high power peak localized to approximately 0.2 Hz. Both BOLD and CBV resting state scans showed similar propagating waves of activity along the cortex from the SII toward MI; however, these waves were detected more often in BOLD scans than in CBV scans. CONCLUSION: While the power spectrum of the CBV signal is different from that of the BOLD signal, both connectivity maps and spatiotemporal dynamics are similar for the two modalities. Further experiments should address the relationship between spontaneous neural activity, local changes in metabolism, and hemodynamic fluctuations to elucidate the origins of the BOLD and CBV signals.

Simultaneous FMRI and electrophysiology in the rodent brain.

To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in which functional MRI data and in vivo intracortical recording can be performed simultaneously. The combination of MRI and electrical recording is technically challenging because the electrodes used for recording distort the MRI images and the MRI acquisition induces noise in the electrical recording. To minimize the mutual interference of the two modalities, glass microelectrodes were used rather than metal and a noise removal algorithm was implemented for the electrophysiology data. In our studies, two microelectrodes were separately implanted in bilateral primary somatosensory cortices (SI) of the rat and fixed in place. One coronal slice covering the electrode tips was selected for functional MRI. Electrode shafts and fixation positions were not included in the image slice to avoid imaging artifacts. The removed scalp was replaced with toothpaste to reduce susceptibility mismatch and prevent Gibbs ringing artifacts in the images. The artifact structure induced in the electrical recordings by the rapidly-switching magnetic fields during image acquisition was characterized by averaging all cycles of scans for each run. The noise structure during imaging was then subtracted from original recordings. The denoised time courses were then used for further analysis in combination with the fMRI data. As an example, the simultaneous acquisition was used to determine the relationship between spontaneous fMRI BOLD signals and band-limited intracortical electrical activity. Simultaneous fMRI and electrophysiological recording in the rodent will provide a platform for many exciting applications in neuroscience in addition to elucidating the relationship between the fMRI BOLD signal and neuronal activity.

Comparison of alpha-chloralose, medetomidine and isoflurane anesthesia for functional connectivity mapping in the rat.

Functional connectivity measures based upon low-frequency blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) signal fluctuations have become a widely used tool for investigating spontaneous brain activity in humans. Still unknown, however, is the precise relationship between neural activity, the hemodynamic response and fluctuations in the MRI signal. Recent work from several groups had shown that correlated low-frequency fluctuations in the BOLD signal can be detected in the anesthetized rat - a first step toward elucidating this relationship. Building on this preliminary work, through this study, we demonstrate that functional connectivity observed in the rat depends strongly on the type of anesthesia used. Power spectra of spontaneous fluctuations and the cross-correlation-based connectivity maps from rats anesthetized with alpha-chloralose, medetomidine or isoflurane are presented using a high-temporal-resolution imaging sequence that ensures minimal contamination from physiological noise. The results show less localized correlation in rats anesthetized with isoflurane as compared with rats anesthetized with alpha-chloralose or medetomidine. These experiments highlight the utility of using different types of anesthesia to explore the fundamental physiological relationships of the BOLD signal and suggest that the mechanisms contributing to functional connectivity involve a complicated relationship between changes in neural activity, neurovascular coupling and vascular reactivity.

Spatiotemporal dynamics of low frequency fluctuations in BOLD fMRI of the rat.

PURPOSE: To examine spatiotemporal dynamics of low frequency fluctuations in rat cortex. MATERIALS AND METHODS: Gradient-echo echo-planar imaging images were acquired from anesthetized rats (repetition time = 100 ms). Power spectral analysis was performed to detect different frequency peaks. Functional connectivity maps were obtained for the frequency peaks of interest. The images in the filtered time-series were displayed as a movie to study spatiotemporal patterns in the data for frequency bands of interest. RESULTS: High temporal and spectral resolution allowed separation of primary components of physiological noise and visualization of spectral details. Two low frequency peaks with distinct characteristics were observed. Selective visualization of the second low frequency peak revealed waves of activity that typically began in the secondary somatosensory cortex and propagated to the primary motor cortex. CONCLUSION: To date, analysis of these fluctuations has focused on the detection of functional networks assuming steady state conditions. These results suggest that detailed examination of the spatiotemporal dynamics of the low frequency fluctuations may provide more insight into brain function, and add a new perspective to the analysis of resting state fMRI data.