Fluctuations In Blood Oxygen Level-dependent Signal Research Articles

Measuring vascular reactivity with resting-state blood oxygenation level-dependent (BOLD) signal fluctuations: A potential alternative to the breath-holding challenge?

Measurement of the ability of blood vessels to dilate and constrict, known as vascular reactivity, is often performed with breath-holding tasks that transiently raise arterial blood carbon dioxide (PaCO2) levels. However, following the proper commands for a breath-holding experiment may be difficult or impossible for many patients. In this study, we evaluated two approaches for obtaining vascular reactivity information using blood oxygenation level-dependent signal fluctuations obtained from resting-state functional magnetic resonance imaging data: physiological fluctuation regression and coefficient of variation of the resting-state functional magnetic resonance imaging signal. We studied a cohort of 28 older adults (69 ± 7 years) and found that six of them (21%) could not perform the breath-holding protocol, based on an objective comparison with an idealized respiratory waveform. In the subjects that could comply, we found a strong linear correlation between data extracted from spontaneous resting-state functional magnetic resonance imaging signal fluctuations and the blood oxygenation level-dependent percentage signal change during breath-holding challenge (R2 = 0.57 and 0.61 for resting-state physiological fluctuation regression and resting-state coefficient of variation methods, respectively). This technique may eliminate the need for subject cooperation, thus allowing the evaluation of vascular reactivity in a wider range of clinical and research conditions in which it may otherwise be impractical.

Multiscale network activity in resting state fMRI.

The brain is inherently multiscalar in both space and time. We argue that this multiscalar nature is reflected in the blood oxygenation level dependent (BOLD) fluctuations used to map functional connectivity. We present evidence that global fluctuations in activity, quasiperiodic spatiotemporal patterns, and aperiodic time-varying activity coexist within the BOLD signal. These processes can be separated using careful analysis and appear to reflect electrical activity on similar scales, suggesting that the BOLD signal fluctuations can provide novel insight into the functional architecture of the brain.

Salience Network Functional Connectivity Predicts Placebo Effects in Major Depression

BackgroundRecent neuroimaging studies have demonstrated resting-state functional connectivity (rsFC) abnormalities among intrinsic brain networks in major depressive disorder (MDD); however, their role as predictors of treatment response has not yet been explored. Here, we investigate whether network-based rsFC predicts antidepressant and placebo effects in MDD. MethodsWe performed a randomized controlled trial of two week-long, identical placebos (described either as having active fast-acting, antidepressant effects or as inactive) followed by a 10-week open-label antidepressant medication treatment. Twenty-nine participants underwent an rsFC functional magnetic resonance imaging scan at the completion of each placebo condition. Networks were isolated from resting-state blood oxygen level-dependent signal fluctuations using independent component analysis. Baseline and placebo-induced changes in rsFC within the default mode, salience, and executive networks were examined for associations with placebo and antidepressant treatment response. ResultsIncreased baseline rsFC in the rostral anterior cingulate within the salience network, a region classically implicated in the formation of placebo analgesia and the prediction of treatment response in MDD, was associated with greater response to 1 week of active placebo and 10 weeks of antidepressant treatment. Machine learning further demonstrated that increased salience network rsFC, mainly within the rostral anterior cingulate, significantly predicts individual responses to placebo administration. ConclusionsThese data demonstrate that baseline rsFC within the salience network is linked to clinical placebo responses. This information could be employed to identify patients who would benefit from lower doses of antidepressant medication or nonpharmacologic approaches or to develop biomarkers of placebo effects in clinical trials.

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.

Vascular coupling in resting-state fMRI: evidence from multiple modalities.

Resting-state functional magnetic resonance imaging (rs-fMRI) provides a potential to understand intrinsic brain functional connectivity. However, vascular effects in rs-fMRI are still not fully understood. Through multiple modalities, we showed marked vascular signal fluctuations and high-level coupling among arterial pressure, cerebral blood flow (CBF) velocity and brain tissue oxygenation at <0.08 Hz. These similar spectral power distributions were also observed in blood oxygen level-dependent (BOLD) signals obtained from six representative regions of interest (ROIs). After applying brain global, white-matter, cerebrospinal fluid (CSF) mean signal regressions and low-pass filtering (<0.08 Hz), the spectral power of BOLD signal was reduced by 55.6% to 64.9% in all ROIs (P=0.011 to 0.001). The coherence of BOLD signal fluctuations between an ROI pair within a same brain network was reduced by 9.9% to 20.0% (P=0.004 to <0.001), but a larger reduction of 22.5% to 37.3% (P=0.032 to <0.001) for one not in a same network. Global signal regression overall had the largest impact in reducing spectral power (by 52.2% to 61.7%) and coherence, relative to the other three preprocessing steps. Collectively, these findings raise a critical question of whether a large portion of rs-fMRI signals can be attributed to the vascular effects produced from upstream changes in cerebral hemodynamics.

Resting-State Functional Connectivity in Individuals with Down Syndrome and Williams Syndrome Compared with Typically Developing Controls.

The emergence of resting-state functional connectivity (rsFC) analysis, which examines temporal correlations of low-frequency (<0.1 Hz) blood oxygen level-dependent signal fluctuations between brain regions, has dramatically improved our understanding of the functional architecture of the typically developing (TD) human brain. This study examined rsFC in Down syndrome (DS) compared with another neurodevelopmental disorder, Williams syndrome (WS), and TD. Ten subjects with DS, 18 subjects with WS, and 40 subjects with TD each participated in a 3-Tesla MRI scan. We tested for group differences (DS vs. TD, DS vs. WS, and WS vs. TD) in between- and within-network rsFC connectivity for seven functional networks. For the DS group, we also examined associations between rsFC and other cognitive and genetic risk factors. In DS compared with TD, we observed higher levels of between-network connectivity in 6 out 21 network pairs but no differences in within-network connectivity. Participants with WS showed lower levels of within-network connectivity and no significant differences in between-network connectivity relative to DS. Finally, our comparison between WS and TD controls revealed lower within-network connectivity in multiple networks and higher between-network connectivity in one network pair relative to TD controls. While preliminary due to modest sample sizes, our findings suggest a global difference in between-network connectivity in individuals with neurodevelopmental disorders compared with controls and that such a difference is exacerbated across many brain regions in DS. However, this alteration in DS does not appear to extend to within-network connections, and therefore, the altered between-network connectivity must be interpreted within the framework of an intact intra-network pattern of activity. In contrast, WS shows markedly lower levels of within-network connectivity in the default mode network and somatomotor network relative to controls. These findings warrant further investigation using a task-based procedure that may help disentangle the relationship between brain function and cognitive performance across the spectrum of neurodevelopmental disorders.

Default-mode network functional connectivity is closely related to metabolic activity.

Over the last decade, the brain's default‐mode network (DMN) and its function has attracted a lot of attention in the field of neuroscience. However, the exact underlying mechanisms of DMN functional connectivity, or more specifically, the blood‐oxygen level‐dependent (BOLD) signal, are still incompletely understood. In the present study, we combined 2‐deoxy‐2‐[18F]fluoroglucose positron emission tomography (FDG‐PET), proton magnetic resonance spectroscopy (1H‐MRS), and resting‐state functional magnetic resonance imaging (rs‐fMRI) to investigate more directly the association between local glucose consumption, local glutamatergic neurotransmission and DMN functional connectivity during rest. The results of the correlation analyzes using the dorsal posterior cingulate cortex (dPCC) as seed region showed spatial similarities between fluctuations in FDG‐uptake and fluctuations in BOLD signal. More specifically, in both modalities the same DMN areas in the inferior parietal lobe, angular gyrus, precuneus, middle, and medial frontal gyrus were positively correlated with the dPCC. Furthermore, we could demonstrate that local glucose consumption in the medial frontal gyrus, PCC and left angular gyrus was associated with functional connectivity within the DMN. We did not, however, find a relationship between glutamatergic neurotransmission and functional connectivity. In line with very recent findings, our results lend further support for a close association between local metabolic activity and functional connectivity and provide further insights towards a better understanding of the underlying mechanism of the BOLD signal. Hum Brain Mapp 36:2027–2038, 2015. © 2015 Wiley Periodicals, Inc.

Evaluating rehabilitation interventions in Parkinson's disease with functional MRI: a promising neuroprotective strategy.

Evaluating rehabilitation interventions in Parkinson's disease with functional MRI: a promising neuroprotective strategy.

Resting state functional connectivity in the human spinal cord.

Functional magnetic resonance imaging using blood oxygenation level dependent (BOLD) contrast is well established as one of the most powerful methods for mapping human brain function. Numerous studies have measured how low-frequency BOLD signal fluctuations from the brain are correlated between voxels in a resting state, and have exploited these signals to infer functional connectivity within specific neural circuits. However, to date there have been no previous substantiated reports of resting state correlations in the spinal cord. In a cohort of healthy volunteers, we observed robust functional connectivity between left and right ventral (motor) horns, and between left and right dorsal (sensory) horns. Our results demonstrate that low-frequency BOLD fluctuations are inherent in the spinal cord as well as the brain, and by analogy to cortical circuits, we hypothesize that these correlations may offer insight into the execution and maintenance of sensory and motor functions both locally and within the cerebrum.DOI: http://dx.doi.org/10.7554/eLife.02812.001.

A functional dissociation between language and multiple-demand systems revealed in patterns of BOLD signal fluctuations.

What is the relationship between language and other high-level cognitive functions? Neuroimaging studies have begun to illuminate this question, revealing that some brain regions are quite selectively engaged during language processing, whereas other "multiple-demand" (MD) regions are broadly engaged by diverse cognitive tasks. Nonetheless, the functional dissociation between the language and MD systems remains controversial. Here, we tackle this question with a synergistic combination of functional MRI methods: we first define candidate language-specific and MD regions in each subject individually (using functional localizers) and then measure blood oxygen level-dependent signal fluctuations in these regions during two naturalistic conditions ("rest" and story-comprehension). In both conditions, signal fluctuations strongly correlate among language regions as well as among MD regions, but correlations across systems are weak or negative. Moreover, data-driven clustering analyses based on these inter-region correlations consistently recover two clusters corresponding to the language and MD systems. Thus although each system forms an internally integrated whole, the two systems dissociate sharply from each other. This independent recruitment of the language and MD systems during cognitive processing is consistent with the hypothesis that these two systems support distinct cognitive functions.

Local activity determines functional connectivity in the resting human brain: a simultaneous FDG-PET/fMRI study.

Over the last decade, synchronized resting-state fluctuations of blood oxygenation level-dependent (BOLD) signals between remote brain areas [so-called BOLD resting-state functional connectivity (rs-FC)] have gained enormous relevance in systems and clinical neuroscience. However, the neural underpinnings of rs-FC are still incompletely understood. Using simultaneous positron emission tomography/magnetic resonance imaging we here directly investigated the relationship between rs-FC and local neuronal activity in humans. Computational models suggest a mechanistic link between the dynamics of local neuronal activity and the functional coupling among distributed brain regions. Therefore, we hypothesized that the local activity (LA) of a region at rest determines its rs-FC. To test this hypothesis, we simultaneously measured both LA (glucose metabolism) and rs-FC (via synchronized BOLD fluctuations) during conditions of eyes closed or eyes open. During eyes open, LA increased in the visual system, and the salience network (i.e., cingulate and insular cortices) and the pattern of elevated LA coincided almost exactly with the spatial pattern of increased rs-FC. Specifically, the voxelwise regional profile of LA in these areas strongly correlated with the regional pattern of rs-FC among the same regions (e.g., LA in primary visual cortex accounts for ∼ 50%, and LA in anterior cingulate accounts for ∼ 20% of rs-FC with the visual system). These data provide the first direct evidence in humans that local neuronal activity determines BOLD FC at rest. Beyond its relevance for the neuronal basis of coherent BOLD signal fluctuations, our procedure may translate into clinical research particularly to investigate potentially aberrant links between local dynamics and remote functional coupling in patients with neuropsychiatric disorders.

Spontaneous BOLD Signal Fluctuations in Young Healthy Subjects and Elderly Patients with Chronic Kidney Disease

Spontaneous fluctuations in blood oxygenation level-dependent (BOLD) images are the basis of resting-state fMRI and frequently used for functional connectivity studies. However, there may be intrinsic information in the amplitudes of these fluctuations. We investigated the possibility of using the amplitude of spontaneous BOLD signal fluctuations as a biomarker for cerebral vasomotor reactivity.We compared the coefficient of variation (CV) of the time series (defined as the temporal standard deviation of the time series divided by the mean signal intensity) in two populations: 1) Ten young healthy adults and 2) Ten hypertensive elderly subjects with chronic kidney disease (CKD).We found a statistically significant increase (P<0.01) in the CV values for the CKD patients compared with the young healthy adults in both gray matter (GM) and white matter (WM). The difference was independent of the exact segmentation method, became more significant after correcting for physiological signals using RETROICOR, and mainly arose from very low frequency components of the BOLD signal fluctuation (f<0.025 Hz). Furthermore, there was a strong relationship between WM and GM signal fluctuation CV's (R2 = 0.87) in individuals, with a ratio of about 1∶3.These results suggest that amplitude of the spontaneous BOLD signal fluctuations may be used to assess the cerebrovascular reactivity mechanisms and provide valuable information about variations with age and different disease states.

Lag structure in resting-state fMRI

The discovery that spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals contain information about the functional organization of the brain has caused a paradigm shift in neuroimaging. It is now well established that intrinsic brain activity is organized into spatially segregated resting-state networks (RSNs). Less is known regarding how spatially segregated networks are integrated by the propagation of intrinsic activity over time. To explore this question, we examined the latency structure of spontaneous fluctuations in the fMRI BOLD signal. Our data reveal that intrinsic activity propagates through and across networks on a timescale of ∼1 s. Variations in the latency structure of this activity resulting from sensory state manipulation (eyes open vs. closed), antecedent motor task (button press) performance, and time of day (morning vs. evening) suggest that BOLD signal lags reflect neuronal processes rather than hemodynamic delay. Our results emphasize the importance of the temporal structure of the brain's spontaneous activity.

Advantages and Disadvantages of Resting State Functional Connectivity Magnetic Resonance Imaging for Clinical Applications

Functional Magnetic Resonance Imaging (fMRI) is a powerful non-invasive technique for imaging BOLD (Blood Oxygenation Level Dependent) signal changes that is due to changes in brain hemodynamics responses associated to local neuronal activity to identify activated brain regions [1,2]. This technique allows researchers in laboratory environment to investigate the BOLD signals to determine the activated brain reigns for different stimuli or the processing of various cognitive tasks [3,4]. Furthermore, fMRI can be used in clinical applications to determine the brain abnormalities in population of subjects with neurological disease. Our knowledge about brain functions comes from task-state studies in the presence of external stimuli that the neural activity and subject responses are measured for analysis. However, the brain is very active in resting-state without any stimuli. Recent findings that have been proven very valuable in the clinical area of fMRI applications, involves investigation of brain fluctuations at resting condition and their results demonstrate that spontaneous modulation of the BOLD does not produce randomly. Spontaneous modulations in BOLD signal are structured in spatial patterns that make correlated networks between various brain regions. The analysis of brain fluctuations in BOLD signal usually involves spatial patterns of correlated activity across regions of interests that are known as resting state connectivity networks. After data acquisition and preprocessing [5], there are two important data analysis techniques for studying the resting state functional connectivity: seed-based correlations approaches that are based on calculating the correlation between extracted regions of interests to identify spatial pattern of spontaneous activity and ICA (Independent Component Analyses)-based approaches that use all brain voxels activity to separate brain functional networks that are correlated with spontaneous component of BOLD signal (to account for non-neural noise with considering maximally independent spontaneous BOLD fluctuations) [4,6-8]. Functional connectivity approaches are divided into resting state and task state studies [4,9,10].

P.1.i.030 Default mode network functional connectivity in patients with temporal lobe epilepsy and comorbid depressive and anxiety symptoms

Background: The resting-state networks (RSNs) are sets of biological neuronal ensembles, demonstrating a synchronized low frequency BOLD (Blood Oxygenation Level Dependent) signal fluctuations (<0.08−0.1Hz). The Default Mode Network (DMN) is a RSN that is active when an individual is not focused on the outside world and the brain is at wakeful rest. It has been shown that DMN is involved in emotional processing and may play a significant role in the origin of affective symptoms. Affective symptoms (depression and anxiety) are common in temporal lobe epilepsy and DMN functional connectivity (FC) have been found to be altered in patients with this pathology. Aim: To investigate FC in TLE patients with and without comorbid anxiety-depressive symptoms. Materials and Methods: 28 patients with TLE, confirmed by EEG, aged between 18 and 50, without any significant brain alterations and history of other psychiatric disorders were included in this study. Affective symptoms were assessed during comprehensive psychiatric interview. Beck Depression Inventory, Hospital Anxiety Depressive Scale, Hamilton Anxiety Scale and Montgomery-Asberg Depressive Rating Scale were additionally used to quantify symptom severity. All subjects underwent routine MRI procedure and 9-min resting-state fMRI scanning session, during which they were asked to keep their eyes closed. The images were processed and analyzed using SPM8 and ‘GIFT’ toolbox. Independent component analysis was used to isolate DMN. The resulted maps were compared in groups using one-way ANOVA with post-hoc pairwise comparisons. The results were considered as statistically significant according to threshold of p< 0.005 with a 10-voxel cluster size [1]. Results: All patients were divided into three groups: patients with current affective symptoms and left-sided epileptic focus (left-sided ‘affective’ group (LSAG), n = 18), patients with current affective symptoms and right-sided focus (right-sided ‘affective’ group (RSAG), n = 18), and patients without affective symptoms (‘non-affective’ group (NAG), n = 18). In both groups with affective symptoms, a moderate level of depressive and anxiety symptoms was found, with higher ‘anxiety’ score in LSAG and higher ‘depressive’ score and ‘dysphoric’ symptoms in RSAG. ANOVA revealed significant group differences in the left insula, superior parietal and left frontal cortex. Post-hoc analysis identified increased FC in the right precuneus, parahippocampal and frontal cortex in RSAG compared to NAG. Higher FC in LSAG group demonstrated higher FC in the left insular and parietal cortex compared to RSAG. Conclusions: Increased insular and frontal FC, observed in LSAG, may determine more severe anxiety symptoms in this group. The results are consistent with the data from recent studies, indicating higher anxiety level in patients with left-sided epileptic focus localization. Increased FC in the right precuneus, parahippocampal and frontal area in RSAG may explain the presence of depressive symptoms in this groups and their association with impaired self-control and self-awareness. To finalize, TLE can be considered as a good model to investigate mechanisms underlying anxiety and depression not only in epilepsy, but also in many other neurological and psychiatric disorders.

Brain modifications after acute alcohol consumption analyzed by resting state fMRI

Resting-state functional magnetic resonance imaging (fMRI) is a recent breakthrough in neuroimaging research able to describe “in vivo” the spontaneous baseline neuronal activity characterized by blood oxygen level dependent (BOLD) signal fluctuations at slow frequency (0.01–0.1Hz) that, in the absence of any task, forms spatially distributed functional connectivity networks, called resting state networks (RSNs). The aim of this study was to investigate, in the young and healthy population, the changing of the RSNs after acute ingestion of an alcohol dose able to determine a blood concentration (0.5g/L) that barely exceeds the legal limits for driving in the majority of European Countries. Fifteen healthy volunteers underwent two fMRI sessions using a 1.5T MR scanner before and after alcohol oral consumption. The main sequence acquired was EPI 2D BOLD, one per each session. To prevent the excessive alcohol consumption the subjects underwent the estimation of blood rate by breath test and after the stabilization of blood alcohol level (BAL) at 0.5g/L the subjects underwent the second fMRI session. Functional data elaboration was carried out using the probabilistic independent component analysis (PICA). Spatial maps so obtained were further organized, with MELODIC multisession temporal concatenation FSL option, in a cluster representing the group of pre-alcohol sessions and the group of post-alcohol sessions, followed by the dual regression approach in order to evaluate the increase or decrease in terms of connectivity in the RSNs between the two sessions at group level.The results we obtained reveal that acute consumption of alcohol reduces in a significant way the BOLD signal fluctuations in the resting brain selectively in the sub-callosal cortex (SCC), in left temporal fusiform cortex (TFC) and left inferior temporal gyrus (ITG), which are cognitive regions known to be part of the reward brain network and the ventral visual system.

The effects of respiratory CO2 fluctuations in the resting-state BOLD signal differ between eyes open and eyes closed

Resting fluctuations in arterial CO2 (a cerebral vasodilator) are believed to be an important source of low-frequency blood oxygenation level dependent (BOLD) signal fluctuations. In this study we focus on the two commonly used resting-states in functional magnetic resonance imaging experiments, eyes open and eyes closed, and quantify the degree to which measured spontaneous fluctuations in the partial pressure of end-tidal CO2 (Petco2) relate to BOLD signal time series. A significantly longer latency of BOLD signal changes following Petco2 fluctuations was found in the eyes closed condition compared to with eyes open, which may reveal different intrinsic vascular response delays in CO2 reactivity or an alteration in the net BOLD signal arising from Petco2 fluctuations and altered neural activity with eyes closed. By allowing a spatially varying time delay for the compensation of this temporal difference, a more spatially consistent CO2 correlation map can be obtained. Finally, Granger-causality analysis demonstrated a “causal” relationship between Petco2 and BOLD. The identified dominant Petco2→BOLD directional coupling supports the notion that Petco2 fluctuations are indeed a cause of resting BOLD variance in the majority of subjects.

Resting state BOLD signal periodicity in low-back pain patient's hippocampus

We report here the case of a low-back pain individual who shows rhythmic fluctuations in hippocampal neural activity. Resting state functional magnetic resonance imaging (fMRI) studies record signal over time without extrinsic stimuli and may be used to assess functional connectivity between regions. Functional connectivity can be evaluated by measuring the correlations in spontaneous fluctuations of blood oxygen level dependent (BOLD) signals from different regions across the brain, providing a systems level evaluation of the integration of individual regions within an intrinsic neural network. This case was detected in a study examining opioid treatment effects on the human brain. During our analysis, we discovered that one participant possessed hippocampal BOLD signal fluctuations with exact periodicity, 0.023Hz, pre-treatment and post-treatment. The resting state BOLD signal pattern is strikingly similar to on/off task design BOLD signal time courses, here mimicking 22s on and 22s off. This frequency fluctuation in the BOLD signal persisted beyond the resting state scan and could be seen in both heat-pain and cold-pain task scans, where the tasks paradigms (20s on and 30s off, and 20s on and 32s off, respectively) were not synced with the BOLD signal fluctuations. Additionally, the BOLD signal fluctuations did not correlate with head motion, heart rate, or respiratory rate. Due to the oddity in the BOLD signal observed in the participant's hippocampus, we asked the participant to return for a third scan, over a year after the first scan. We repeated the same resting state functional scan protocol. The 0.023-Hz BOLD signal periodicity within the hippocampus was still observable. This is the first report we know of where someone exhibits such periodicity in the BOLD signal fluctuations in the resting state. We report here the case of a low-back pain individual who shows rhythmic fluctuations in hippocampal neural activity. Resting state functional magnetic resonance imaging (fMRI) studies record signal over time without extrinsic stimuli and may be used to assess functional connectivity between regions. Functional connectivity can be evaluated by measuring the correlations in spontaneous fluctuations of blood oxygen level dependent (BOLD) signals from different regions across the brain, providing a systems level evaluation of the integration of individual regions within an intrinsic neural network. This case was detected in a study examining opioid treatment effects on the human brain. During our analysis, we discovered that one participant possessed hippocampal BOLD signal fluctuations with exact periodicity, 0.023Hz, pre-treatment and post-treatment. The resting state BOLD signal pattern is strikingly similar to on/off task design BOLD signal time courses, here mimicking 22s on and 22s off. This frequency fluctuation in the BOLD signal persisted beyond the resting state scan and could be seen in both heat-pain and cold-pain task scans, where the tasks paradigms (20s on and 30s off, and 20s on and 32s off, respectively) were not synced with the BOLD signal fluctuations. Additionally, the BOLD signal fluctuations did not correlate with head motion, heart rate, or respiratory rate. Due to the oddity in the BOLD signal observed in the participant's hippocampus, we asked the participant to return for a third scan, over a year after the first scan. We repeated the same resting state functional scan protocol. The 0.023-Hz BOLD signal periodicity within the hippocampus was still observable. This is the first report we know of where someone exhibits such periodicity in the BOLD signal fluctuations in the resting state.

Task-related BOLD responses and resting-state functional connectivity during physiological clamping of end-tidal CO2

Carbon dioxide (CO(2)), a potent vasodilator, is known to have a significant impact on the blood-oxygen level dependent (BOLD) signal. With the growing interest in studying synchronized BOLD fluctuations during the resting state, the extent to which the apparent synchrony is due to variations in the end-tidal pressure of CO(2) (PETCO(2)) is an important consideration. CO(2)-related fluctuations in BOLD signal may also represent a potential confound when studying task-related responses, especially if breathing depth and rate are affected by the task. While previous studies of the above issues have explored retrospective correction of BOLD fluctuations related to arterial PCO(2), here we demonstrate an alternative approach based on physiological clamping of the arterial CO(2) level to a near-constant value. We present data comparing resting-state functional connectivity within the default-mode-network (DMN), as well as task-related BOLD responses, acquired in two conditions in each subject: 1) while subject's PETCO(2) was allowed to vary spontaneously; and 2) while controlling subject's PETCO(2) within a narrow range. Strong task-related responses and areas of maximal signal correlation in the DMN were not significantly altered by suppressing fluctuations in PETCO(2). Controlling PETCO(2) did, however, improve the performance of retrospective physiological noise correction techniques, allowing detection of additional regions of task-related response and resting-state connectivity in highly vascularized regions such as occipital cortex. While these results serve to further rule out systemic physiological fluctuations as a significant source of apparent resting-state network connectivity, they also demonstrate that fluctuations in arterial CO(2) are one of the factors limiting sensitivity in task-based and resting-state fMRI, particularly in regions of high vascular density. This must be considered when comparing subject groups who might exhibit differences in respiratory physiology or breathing patterns.

Altered Thalamocortical Functional Connectivity by Propofol Anesthesia in Rats

Anesthesia, a state of profound central nervous system suppression, involves a sequence of events that is still not well understood. In the present study, we examined the action of propofol (a sedative-hypnotic drug commonly used as anesthetic) on thalamocortical functional connectivity in rats by using functional connectivity magnetic resonance imaging (fcMRI) with a 3.0-tesla MR scanner. Intraperitoneal injections of propofol (80 or 160 mg/kg) were administered to Sprague-Dawley rats. Synchronized low-frequency fluctuations (LFF) of blood oxygen level-dependent (BOLD) signals were found between the thalamic and somatosensory cortices (S1/S2) after administration of 80 mg/kg propofol. However, after application of 160 mg/kg propofol, synchronized LFF of BOLD signals disappeared. These observations indicate that thalamocortical connectivity may play an important role in propofol anesthesia. We also observed that regionally specific long-range correlations of spontaneous low-frequency physiological fluctuations in BOLD signals may be present across somatosensory networks of the brain in the absence of external stimulation. However, our experiment suggests that fcMRI can be used to investigate brain networks that exhibit correlated fluctuations.