Resting-state Blood Oxygen Level-dependent fMRI Research Articles

A Novel Finding in Cerebral Blood Flow in Patients with Sickle Cell Disease Using Bold Functional MRI

Background: Sickle cell disease (SCD) is an inherited blood disorder which is associated with acute and chronic pain, as well as other vascular complications such as arterial steno-occlusion, stroke, and silent cerebral infarction. Alterations of cerebral blood flow have been found to be associated with different painful stages in SCD, thus cerebral blood flow might be correlated with the disease severity determined by varied pain conditions in SCD. Blood oxygen level dependent (BOLD) imaging is a blood-related contrast technology in functional magnetic resonance imaging (fMRI). We have previously demonstrated the feasibility of using low frequency oscillation (LFO) in BOLD fMRI to track the hemodynamic features of the blood flow with maximum cross-correlation coefficient (MCCC) and the Delay Time (i.e., blood arrival time at different brain regions) (Tong et al., JCBFM. 2017). Positive MCCC value was found between the LFO BOLD signals extracted from the global mean (GMean, averaged signal across the whole brain) and the superior sagittal sinus (SSS) in our previous findings (Tong et al., JCBFM. 2018). In this study, we aim to use LFO BOLD signals to explore the cerebral hemodynamic features with MCCCs and their associations with hematological and disease severity related outcomes in patients with SCD. Methods: Ten subjects with SCD aged 14-43 years old (5 HbSS, 3 HbSC, 1 HbSB+, 1 HbB0) and 10 age- and sex-matched controls from a publicly available dataset Human Connectome Project (HCP) (Essen et al., Neuroimage, 2013) were included for data analysis. T1-weighted and resting-state BOLD fMRI (repetition time (TR)=1.05 sec) were collected using a 3T SIEMENS (Prisma) scanner. A BOLD fMRI dataset with TR of 0.72 sec from healthy subjects was used as control. All the BOLD fMRI data were preprocessed using FSL to correct the motion artifact. The SSS region was identified in the T1-weighted image using FSL. The corresponding SSS mask was then applied in the BOLD fMRI image to extract the BOLD fMRI signals in the SSS region. The GMean BOLD signal was averaged across the whole brain. BOLD fMRI Signals were demeaned and band-pass filtered (0.01-0.1 Hz) to acquire the LFO signals. Cross-correlation between the SSS-LFO signal and GMean-LFO signal was performed to calculate the MCCC and their corresponding Delay Time. Correlations between the MCCCs of the two LFO signals (from SSS and GMean) and each hematological index were further performed. Results: Consistent with the healthy control in our previous findings, half of the patients (3 HbSC, 1 HbSB+, and 1 HbSS) presented positive MCCC values. However, interestingly, negative MCCC values were found from another half of the patients (4 HbSS and 1 HbB0, Figure 1, p < 0.05 for all subjects). Notably, all patients with HbSC presented positive MCCC values that are similar to controls whereas 4 out 5 patients with HbSS (80%) were found to have negative MCCC values. More importantly, higher percentages of HbS and lower total Hgb (HbS(%): r=-0.73, p=0.03; Hgb(GM/dL): r=0.69, p=0.03) were found to be significantly associated with the negative MCCC values. Conclusions: We found a never-before-seen negative MCCC signature between the BOLD fMRI signals in the SSS and the GMean in a subset of patients with SCD compared with healthy controls. This might indicate a significant change in cerebral blood flow in a subset of patients with SS disease compared with SC and controls. Importantly, we further observed that this never-before-seen negative MCCC signature is highly associated with the percentage of the HbS and total Hgb that are known to be correlated with disease severity. This might be due to the microvascular shunting (Juttukonda et al., JCBFM, 2019) that exists in patients who have high percentage of HbS. This study is the first to associate BOLD fMRI derived hemodynamic metrics with disease severity related outcomes in SCD. This never-before-seen anti-correlation MCCC signature may have tremendous promise as a novel biomarker for SCD severity and differentiate pain characteristics in different sickle cell phenotypes, and further investigation in larger number of subjects is needed to understand variations between SCD phenotypes and its relationship to clinical outcomes. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Cerebral neurovascular alterations in stable chronic obstructive pulmonary disease: a preliminary fMRI study.

Cognitive impairment (CI) is very common in patients with chronic obstructive pulmonary disease (COPD). Cerebral structural and functional abnormalities have been reported in cognitively impaired patients with COPD, and the neurovascular coupling changes are rarely investigated. To address this issue, arterial spin labeling (ASL) and resting-state blood oxygenation level dependent (BOLD) fMRI techniques were used to determine whether any neurovascular changes in COPD patients. Forty-five stable COPD patients and forty gender- and age-matched healthy controls were recruited. Furthermore, resting-state BOLD fMRI and ASL were acquired to calculate degree centrality (DC) and cerebral blood flow (CBF) respectively. The CBF-DC coupling and CBF/DC ratio were compared between the two groups. COPD patients showed abnormal CBF, DC and CBF/DC ratio in several regions. Moreover, lower CBF/DC ratio in the left lingual gyrus negatively correlated with naming scores, lower CBF/DC ratio in medial frontal cortex/temporal gyrus positively correlated with the Montreal Cognitive Assessment (MoCA), visuospatial/executive and delayed recall scores. These findings may provide new potential insights into neuropathogenesis of cognition decline in stable COPD patients.

BOLD asynchrony elucidates tumor burden in IDH-mutated gliomas.

Gliomas comprise the most common type of primary brain tumor, are highly invasive, and often fatal. IDH-mutated gliomas are particularly challenging to image and there is currently no clinically accepted method for identifying the extent of tumor burden in these neoplasms. This uncertainty poses a challenge to clinicians who must balance the need to treat the tumor while sparing healthy brain from iatrogenic damage. The purpose of this study was to investigate the feasibility of using resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to detect glioma-related asynchrony in vascular dynamics for distinguishing tumor from healthy brain. Twenty-four stereotactically localized biopsies were obtained during open surgical resection from ten treatment-naïve patients with IDH-mutated gliomas who received standard-of-care preoperative imaging as well as echo-planar resting-state BOLD fMRI. Signal intensity for BOLD asynchrony and standard-of-care imaging was compared to cell counts of total cellularity (H&E), tumor density (IDH1 & Sox2), cellular proliferation (Ki67), and neuronal density (NeuN), for each corresponding sample. BOLD asynchrony was directly related to total cellularity (H&E, P = 4 × 10-5), tumor density (IDH1, P = 4 × 10-5; Sox2, P = 3 × 10-5), cellular proliferation (Ki67, P = .002), and inversely related to neuronal density (NeuN, P = 1 × 10-4). Asynchrony in vascular dynamics, as measured by resting-state BOLD fMRI, correlates with tumor burden and provides a radiographic delineation of tumor boundaries in IDH-mutated gliomas.

Asynchrony in Peritumoral Resting-State Blood Oxygen Level-Dependent fMRI Predicts Meningioma Grade and Invasion.

Meningioma grade is determined by histologic analysis, with detectable brain invasion resulting in a diagnosis of grade II or III tumor. However, tissue undersampling is a common problem, and invasive parts of the tumor can be missed, resulting in the incorrect assignment of a lower grade. Radiographic biomarkers may be able to improve the diagnosis of grade and identify targets for biopsy. Prior work in patients with gliomas has shown that the resting-state blood oxygen level-dependent fMRI signal within these tumors is not synchronous with normal brain. We hypothesized that blood oxygen level-dependent asynchrony, a functional marker of vascular dysregulation, could predict meningioma grade. We identified 25 patients with grade I and 11 patients with grade II or III meningiomas. Blood oxygen level-dependent time-series were extracted from the tumor and the radiographically normal control hemisphere and were included as predictors in a multiple linear regression to generate a blood oxygen level-dependent asynchrony map, in which negative values signify synchronous and positive values signify asynchronous activity relative to healthy brain. Masks of blood oxygen level-dependent asynchrony were created for each patient, and the fraction of the mask that extended beyond the contrast-enhancing tumor was computed. The spatial extent of blood oxygen level-dependent asynchrony was greater in high (grades II and III) than in low (I) grade tumors (P < 0.001) and could discriminate grade with high accuracy (area under the curve = 0.88). Blood oxygen level-dependent asynchrony radiographically discriminates meningioma grade and may provide targets for biopsy collection to aid in histologic diagnosis.

Comparing Coordinated Networks Across the Brainstem and Spinal Cord in the Resting State and Altered Cognitive State.

Resting-state (RS) functional magnetic resonance imaging (fMRI) has been used to investigate networks of activity within the brain, as well as the brainstem (BS) and spinal cord (SC). While previous research has shown coordinated resting state networks (RSNs) in the BS/SC, their function is still unclear. The aim of this study was to investigate the function of RSNs across these regions, by examining how these networks change when participants are experiencing different cognitive states (RS, listening to an audio presentation, or watching a video). RS blood oxygenation-level dependent fMRI data were obtained from the human cervical SC and BS in 20 healthy participants (14 women, 6 men), at 3 tesla, with T2-weighted single-shot fast spin-echo imaging. Functional connectivity was investigated within the entire three-dimensional region by means of temporal correlations between anatomical regions and by structural equation modeling (SEM). Both correlational analyses and SEM showed extensive connectivity within and across BS and SC regions, and 37% to 40% of significant connections were consistent across study conditions. However, significant differences in connectivity between specific regions of the BS and SC were also identified which depended on the study conditions. The results indicate that connectivity across the RS SC/BS is influenced by a person's cognitive/emotional state. The known anatomical functions of the regions involved support the conclusion that this RS network may play a role in the integration of homeostatic autonomic functions.

Investigation of Resting-State BOLD Networks in the Human Brainstem and Spinal Cord

Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to investigate networks within the cortex and has also provided some insight into the networks present in the brainstem (BS) and spinal cord (SC). The purpose of this study was to investigate resting-state blood oxygenation-level dependent (BOLD) fluctuations in the BS/SC and to identify resting-state networks (RSNs) across these regions. Resting-state BOLD fMRI data were obtained from the entire BS and cervical SC in 16 healthy participants, at 3 T, with T2-weighted single-shot fast spin-echo imaging. Data were spatially normalized and processed to remove physiological noise. Cluster-cluster functional connectivity was investigated across the entire 3D region by means of temporal correlations, and structural equation modeling (SEM) was used to investigate RSNs. Extensive connectivity was observed within and across BS and SC regions, with connections spanning up to 120 mm, although shorter connections were more prevalent. SEM results revealed extensive brainstem-cord connectivity that included specific anatomical regions within the brainstem. The results indicate the presence of a complex resting-state network which is highly interconnected in the spinal cord. Known anatomical connections between cortical and BS regions support the conclusion that the observed resting-state BOLD fluctuations in the BS/SC may be related to autonomic regulation. Future studies are required to further investigate these resting-state BOLD networks.

Altered functional connectivity between sub-regions in the thalamus and cortex in schizophrenia patients measured by resting state BOLD fMRI at 7T

The thalamus is a small brain structure that relays neuronal signals between subcortical and cortical regions. Abnormal thalamocortical connectivity in schizophrenia has been reported in previous studies using blood-oxygenation-level-dependent (BOLD) functional MRI (fMRI) performed at 3T. However, anatomically the thalamus is not a single entity, but is subdivided into multiple distinct nuclei with different connections to various cortical regions. We sought to determine the potential benefit of using the enhanced sensitivity of BOLD fMRI at ultra-high magnetic field (7T) in exploring thalamo-cortical connectivity in schizophrenia based on subregions in the thalamus. Seeds placed in thalamic subregions of 14 patients and 14 matched controls were used to calculate whole-brain functional connectivity. Our results demonstrate impaired thalamic connectivity to the prefrontal cortex and the cerebellum, but enhanced thalamic connectivity to the motor/sensory cortex in schizophrenia. This altered functional connectivity significantly correlated with disease duration in the patients. Remarkably, comparable effect sizes observed in previous 3T studies were detected in the current 7T study with a heterogeneous and much smaller cohort, providing evidence that ultra-high field fMRI may be a powerful tool for measuring functional connectivity abnormalities in schizophrenia. Further investigation with a larger cohort is merited to validate the current findings.

Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI

Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition.

Local Glioma Cells Are Associated with Vascular Dysregulation.

Malignant glioma is a highly infiltrative malignancy that causes variable disruptions to the structure and function of the cerebrovasculature. While many of these structural disruptions have known correlative histopathologic alterations, the mechanisms underlying vascular dysfunction identified by resting-state blood oxygen level-dependent imaging are not yet known. The purpose of this study was to characterize the alterations that correlate with a blood oxygen level-dependent biomarker of vascular dysregulation. Thirty-two stereotactically localized biopsies were obtained from contrast-enhancing (n = 16) and nonenhancing (n = 16) regions during open surgical resection of malignant glioma in 17 patients. Preoperative resting-state blood oxygen level-dependent fMRI was used to evaluate the relationships between radiographic and histopathologic characteristics. Signal intensity for a blood oxygen level-dependent biomarker was compared with scores of tumor infiltration and microvascular proliferation as well as total cell and neuronal density. Biopsies corresponded to a range of blood oxygen level-dependent signals, ranging from relatively normal (z = -4.79) to markedly abnormal (z = 8.84). Total cell density was directly related to blood oxygen level-dependent signal abnormality (P = .013, R2 = 0.19), while the neuronal labeling index was inversely related to blood oxygen level-dependent signal abnormality (P = .016, R2 = 0.21). The blood oxygen level-dependent signal abnormality was also related to tumor infiltration (P = .014) and microvascular proliferation (P = .045). The relationship between local, neoplastic characteristics and a blood oxygen level-dependent biomarker of vascular function suggests that local effects of glioma cell infiltration contribute to vascular dysregulation.

On the Stability of BOLD fMRI Correlations.

Measurement of correlations between brain regions (functional connectivity) using blood oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the functional organization of the brain. Recently, dynamic functional connectivity has emerged as a major topic in the resting-state BOLD fMRI literature. Here, using simulations and multiple sets of empirical observations, we confirm that imposed task states can alter the correlation structure of BOLD activity. However, we find that observations of "dynamic" BOLD correlations during the resting state are largely explained by sampling variability. Beyond sampling variability, the largest part of observed "dynamics" during rest is attributable to head motion. An additional component of dynamic variability during rest is attributable to fluctuating sleep state. Thus, aside from the preceding explanatory factors, a single correlation structure-as opposed to a sequence of distinct correlation structures-may adequately describe the resting state as measured by BOLD fMRI. These results suggest that resting-state BOLD correlations do not primarily reflect moment-to-moment changes in cognitive content. Rather, resting-state BOLD correlations may predominantly reflect processes concerned with the maintenance of the long-term stability of the brain's functional organization.

Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults

In conventional neuroimaging, cerebrovascular reactivity (CVR) is quantified primarily using the blood-oxygenation level-dependent (BOLD) functional MRI (fMRI) signal, specifically, as the BOLD response to intravascular carbon dioxide (CO2) modulations, in units of [%ΔBOLD/mmHg]. While this method has achieved wide appeal and clinical translation, the tolerability of CO2-related tasks amongst patients and the elderly remains a challenge in more routine and large-scale applications. In this work, we propose an improved method to quantify CVR by exploiting intrinsic fluctuations in CO2 and corresponding changes in the resting-state BOLD signal (rs-qCVR). Our rs-qCVR approach requires simultaneous monitoring of PETCO2, cardiac pulsation and respiratory volume. In 16 healthy adults, we compare our quantitative CVR estimation technique to the prospective CO2-targeting based CVR quantification approach (qCVR, the “standard”). We also compare our rs-CVR to non-quantitative alternatives including the resting-state fluctuation amplitude (RSFA), amplitude of low-frequency fluctuation (ALFF) and global-signal regression. When all subjects were pooled, only RSFA and ALFF were significantly associated with qCVR. However, for characterizing regional CVR variations within each subject, only the PETCO2-based rs-qCVR measure is strongly associated with standard qCVR in 100% of the subjects (p≤0.1). In contrast, for the more qualitative CVR measures, significant within-subject association with qCVR was only achieved in 50–70% of the subjects. Our work establishes the feasibility of extracting quantitative CVR maps using rs-fMRI, opening the possibility of mapping functional connectivity and qCVR simultaneously.

Glioblastoma Induces Vascular Dysregulation in Nonenhancing Peritumoral Regions in Humans.

Glioblastoma is an invasive primary brain malignancy that typically infiltrates the surrounding tissue with malignant cells. It disrupts cerebral blood flow through a variety of biomechanical and biochemical mechanisms. Thus, neuroimaging focused on identifying regions of vascular dysregulation may reveal a marker of tumor spread. The purpose of this study was to use blood oxygenation level-dependent (BOLD) functional MRI (fMRI) to compare the temporal dynamics of the enhancing portion of a tumor with those of brain regions without apparent tumors. Patients with pathologically proven glioblastoma underwent preoperative resting-state BOLD fMRI, T1-weighted contrast-enhanced MRI, and FLAIR MRI. The contralesional control hemisphere, contrast-enhancing tumor, and peritu-moral edema were segmented by use of structural images and were used to extract the time series of these respective regions. The parameter estimates (beta values) for the two regressors and resulting z-statistic images were used as a metric to compare the similarity of the tumor dynamics to those of other brain regions. The time course of the contrast-enhancing tumor was significantly different from that of the rest of the brain (p < 0.05). Similarly, the control signal intensity was significantly different from the tumor signal intensity (p < 0.05). Notably, the temporal dynamics in the peritumoral edema, which did not contain enhancing tumor, were most similar to the those of enhancing tumor than to those of control regions. The findings show that the disruption in vascular regulation induced by a glioblastoma can be detected with BOLD fMRI and that the spatial distribution of these disruptions is localized to the immediate vicinity of the tumor and peritumoral edema.

Resting-state Functional Magnetic Resonance Imaging Correlates of Sevoflurane-induced Unconsciousness.

Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been used to study the effects of anesthetic agents on correlated intrinsic neural activity. Previous studies have focused primarily on intravenous agents. The authors studied the effects of sevoflurane, an inhaled anesthetic. Resting-state BOLD fMRI was acquired from 10 subjects before sedation and from 9 subjects rendered unresponsive by 1.2% sevoflurane. The fMRI data were analyzed taking particular care to minimize the impact of artifact generated by head motion. BOLD correlations were specifically weaker within the default mode network and ventral attention network during sevoflurane-induced unconsciousness, especially between anterior and posterior midline regions. Reduced functional connectivity between these same networks and the thalamus was also spatially localized to the midline frontal regions. The amplitude of BOLD signal fluctuations was substantially reduced across all brain regions. The importance of censoring epochs contaminated by head motion was demonstrated by comparative analyses. Sevoflurane-induced unconsciousness is associated with both globally reduced BOLD signal amplitudes and selectively reduced functional connectivity within cortical networks associated with consciousness (default mode network) and orienting to salient external stimuli (ventral attention network). Scrupulous attention to minimizing the impact of head motion artifact is critical in fMRI studies using anesthetic agents.

Resting spontaneous activity in the default mode network predicts performance decline during prolonged attention workload

After continuous and prolonged cognitive workload, people typically show reduced behavioral performance and increased feelings of fatigue, which are known as “time-on-task (TOT) effects”. Although TOT effects are pervasive in modern life, their underlying neural mechanisms remain elusive. In this study, we induced TOT effects by administering a 20-min continuous psychomotor vigilance test (PVT) to a group of 16 healthy adults and used resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to examine spontaneous brain activity changes associated with fatigue and performance. Behaviorally, subjects displayed robust TOT effects, as reflected by increasingly slower reaction times as the test progressed and higher self-reported mental fatigue ratings after the 20-min PVT. Compared to pre-test measurements, subjects exhibited reduced amplitudes of low-frequency fluctuation (ALFF) in the default mode network (DMN) and increased ALFF in the thalamus after the test. Subjects also exhibited reduced anti-correlations between the posterior cingulate cortex (PCC) and right middle prefrontal cortex after the test. Moreover, pre-test resting ALFF in the PCC and medial prefrontal cortex (MePFC) predicted subjects' subsequent performance decline; individuals with higher ALFF in these regions exhibited more stable reaction times throughout the 20-min PVT. These results support the important role of both task-positive and task-negative networks in mediating TOT effects and suggest that spontaneous activity measured by resting-state BOLD fMRI may be a marker of mental fatigue.

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.

Complexity and synchronicity of resting state blood oxygenation level-dependent (BOLD) functional MRI in normal aging and cognitive decline

To explore the use of approximate entropy (ApEn) as an index of the complexity and the synchronicity of resting state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in normal aging and cognitive decline associated with familial Alzheimer's disease (fAD).Resting state BOLD fMRI data were acquired at 3T from two independent cohorts of subjects consisting of healthy young (age 23 ± 2 years, n = 8) and aged volunteers (age 66 ± 3 years, n = 8), as well as 22 fAD associated subjects (14 mutation carriers, age 41.2 ± 15.8 years; and eight nonmutation carrying family members, age 28.8 ± 5.9 years). Mean ApEn values were compared between the two age groups and correlated with cognitive performance in the fAD group. Cross-ApEn (C-ApEn) was further calculated to assess the asynchrony between precuneus and the rest of the brain.Complexity of brain activity measured by mean ApEn in gray and white matter decreased with normal aging. In the fAD group, cognitive impairment was associated with decreased mean ApEn in gray matter as well as decreased regional ApEn in right precuneus, right lateral parietal regions, left precentral gyrus, and right paracentral gyrus. A pattern of asynchrony between BOLD fMRI series emerged from C-ApEn analysis, with significant regional anti-correlation with cross-correlation coefficient of functional connectivity analysis.ApEn and C-ApEn may be useful for assessing the complexity and synchronicity of brain activity in normal aging and cognitive decline associated with neurodegenerative diseases.

Loss of Coherence of Low Frequency Fluctuations of BOLD FMRI in Visual Cortex of Healthy Aged Subjects

Aging effects on blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) have been studied using task induced hemodynamic responses with controversial findings. The present study systematically investigated the normal aging effect in the visual cortex using 3 indices of low frequency fluctuations of resting state BOLD fMRI, i.e., amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo) and functional connectivity (FC). These 3 resting state measurements were compared with task induced BOLD activation in the visual cortex of 2 groups of 10 young and 10 elderly subjects. Our results showed reduced functional connectivity and regional homogeneity of low frequency fluctuations of BOLD fMRI in aged subjects as compared to young subjects. While the mean magnitude of BOLD activation and the mean amplitude of low frequency fluctuations of BOLD fMRI did not vary between the 2 age groups, larger variances were observed in both measures in aged subjects. These data suggest that normal aging may be associated with “loss of coherence” of low frequency fluctuations of resting state BOLD fMRI in the visual cortex, and may affect task induced BOLD response through increased inter- and intra-subject variability.

Correction of low-frequency physiological noise from the resting state BOLD fMRI—Effect on ICA default mode analysis at 1.5 T

Confounding low-frequency fluctuation (LFF) physiological noise is a concern for functional connectivity analyses in blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI). Using estimates of LFF physiological noise derived from measured cardiac and respiration signals, noise can be filtered from the time series thus improving the results of functional connectivity analysis. The ability of spatial independent component analysis (ICA) to separate LFF physiological noise from the default mode network (DMN), which overlap each other spatially and occur at similar frequencies, has remained an open question. We aimed to define the net effect of physiological correction for spatial ICA DMN detection at 1.5 T by statistically testing obtained ICASSO centrotype DMN maps before and after physiological correction. Comparisons with 21 subjects were performed for ICA model orders 20, 30 and 40 and no statistically significant spatial difference was found after physiological correction, although slight DMN reduction in precuneus or sagittal sinus was detected in all dimensionalities. A confounding factor in the analysis is the susceptibility of the ICA decomposition for data changes yielding different DMN splitting between and after physiological correction conditions without comparable true change in the data. This issue is mitigated at higher ICA model orders. The results suggest that subject-level DMN can for some subjects be optimized by physiological correction, but on the group-level this contribution is minor.

Caffeine reduces resting-state BOLD functional connectivity in the motor cortex

In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects ( N = 9). We found that caffeine significantly ( p < 0.05) reduced measures of resting-state BOLD connectivity in the motor cortex. Baseline cerebral blood flow and spectral energy in the low-frequency BOLD fluctuations were also significantly decreased by caffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal

Heart rate fluctuations occur in the low-frequency range (< 0.1 Hz) probed in functional magnetic resonance imaging (fMRI) studies of resting-state functional connectivity and most fMRI block paradigms and may be related to low-frequency blood-oxygenation-level-dependent (BOLD) signal fluctuations. To investigate this hypothesis, temporal correlations between cardiac rate and resting-state fMRI signal timecourses were assessed at 3 T. Resting-state BOLD fMRI and accompanying physiological data were acquired and analyzed using cross-correlation and regression. Time-shifted cardiac rate timecourses were included as regressors in addition to established physiological regressors (RETROICOR (Glover, G.H., Li, T.Q., Ress, D., 2000. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med 44, 162–167) and respiration volume per unit time (Birn, R.M., Diamond, J.B., Smith, M.A., Bandettini, P.A., 2006b. Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. NeuroImage 31, 1536–1548). Significant correlations between the cardiac rate and BOLD signal timecourses were revealed, particularly negative correlations in gray matter at time shifts of 6–12 s and positive correlations at time shifts of 30–42 s (TR = 6 s). Regressors consisting of cardiac rate timecourses shifted by delays of between 0 and 24 s explained an additional 1% of the BOLD signal variance on average over the whole brain across 9 subjects, a similar additional variance to that explained by respiration volume per unit time and RETROICOR regressors, even when used in combination with these other physiological regressors. This suggests that including such time-shifted cardiac rate regressors will be beneficial for explaining physiological noise variance and will thereby improve the statistical power in future task-based and resting-state fMRI studies.