Fluctuations In Blood Oxygen Level-dependent Signal Research Articles

Comparison between end-tidal CO 2 and respiration volume per time for detecting BOLD signal fluctuations during paced hyperventilation

Respiratory motion and capnometry monitoring were performed during blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) of the brain while a series of paced hyperventilation tasks were performed that caused significant hypocapnia. Respiration volume per time (RVT) and end-tidal carbon dioxide (ETCO 2) were determined and compared for their ability to explain BOLD contrast changes in the data. A 35% decrease in ETCO 2 was observed along with corresponding changes in RVT. A best-fit ETCO 2 response function, with an average initial peak delay time of 12 s, was empirically determined. ETCO 2 data convolved with this response function was more strongly and prevalently correlated to BOLD signal changes than RVT data convolved with the corresponding respiration response function. The results suggest that ETCO 2 better models BOLD signal fluctuations in fMRI experiments with significant transient hypocapnia. This is due to hysteresis in the ETCO 2 response when moving from hypocapnia to normocapnia, compared to moving from normocapnia to hypocapnia.

Interictal Functional Connectivity of Human Epileptic Networks Assessed by Intracerebral EEG and BOLD Signal Fluctuations

In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal derived from resting state functional magnetic resonance imaging (fMRI) reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG) and resting-state functional MRI (fMRI) in 5 patients suffering from intractable temporal lobe epilepsy (TLE). Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions) during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband) and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal). This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional connectivity measured by iEEG and BOLD signals give complementary but sometimes inconsistent information in TLE.

Abnormal small-world architecture of top–down control networks in obsessive–compulsive disorder

Obsessive-compulsive disorder (OCD) is a common neuropsychiatric disorder that is characterized by recurrent intrusive thoughts, ideas or images and repetitive ritualistic behaviours. Although focal structural and functional abnormalities in specific brain regions have been widely studied in populations with OCD, changes in the functional relations among them remain poorly understood. This study examined OCD-related alterations in functional connectivity patterns in the brain's top-down control network. We applied resting-state functional magnetic resonance imaging to investigate the correlation patterns of intrinsic or spontaneous blood oxygen level-dependent signal fluctuations in 18 patients with OCD and 16 healthy controls. The brain control networks were first constructed by thresholding temporal correlation matrices of 39 brain regions associated with top-down control and then analyzed using graph theory-based approaches. Compared with healthy controls, the patients with OCD showed decreased functional connectivity in the posterior temporal regions and increased connectivity in various control regions such as the cingulate, precuneus, thalamus and cerebellum. Furthermore, the brain's control networks in the healthy controls showed small-world architecture (high clustering coefficients and short path lengths), suggesting an optimal balance between modularized and distributed information processing. In contrast, the patients with OCD showed significantly higher local clustering, implying abnormal functional organization in the control network. Further analysis revealed that the changes in network properties occurred in regions of increased functional connectivity strength in patients with OCD. The patient group in the present study was heterogeneous in terms of symptom clusters, and most of the patients with OCD were medicated. Our preliminary results suggest that the organizational patterns of intrinsic brain activity in the control networks are altered in patients with OCD and thus provide empirical evidence for aberrant functional connectivity in the large-scale brain systems in people with this disorder.

Automated real-time behavioral and physiological data acquisition and display integrated with stimulus presentation for fMRI

Functional magnetic resonance imaging (fMRI) is based on correlating blood oxygen-level dependent (BOLD) signal fluctuations in the brain with other time-varying signals. Although the most common reference for correlation is the timing of a behavioral task performed during the scan, many other behavioral and physiological variables can also influence fMRI signals. Variations in cardiac and respiratory functions in particular are known to contribute significant BOLD signal fluctuations. Variables such as skin conduction, eye movements, and other measures that may be relevant to task performance can also be correlated with BOLD signals and can therefore be used in image analysis to differentiate multiple components in complex brain activity signals. Combining real-time recording and data management of multiple behavioral and physiological signals in a way that can be routinely used with any task stimulus paradigm is a non-trivial software design problem. Here we discuss software methods that allow users control of paradigm-specific audio–visual or other task stimuli combined with automated simultaneous recording of multi-channel behavioral and physiological response variables, all synchronized with sub-millisecond temporal accuracy. We also discuss the implementation and importance of real-time display feedback to ensure data quality of all recorded variables. Finally, we discuss standards and formats for storage of temporal covariate data and its integration into fMRI image analysis. These neuroinformatics methods have been adopted for behavioral task control at all sites in the Functional Biomedical Informatics Research Network (FBIRN) multi-center fMRI study.

Intrinsic functional architecture predicts electrically evoked responses in the human brain

Intrinsic functional architecture predicts electrically evoked responses in the human brain

Functional connectivity of the superior human temporal sulcus in the brain resting state at 3T

The superior temporal sulcus (STS) constitutes a polymodal associative area providing higher-order visual representation of other's action and emotion, necessary for imitation, empathizing, and mentalizing. In monkeys, STS is connected with the cerebellum, which is also involved in motor, emotional, and cognitive functions. However, in humans, very few data are available concerning the functional connectivity of polymodal STS in general and its functional links with the cerebellum, in particular. This study was therefore designed to investigate the intrinsically connected network of STS during the brain resting state with possible involvement of the cerebellum. Data from 14 right-handed healthy volunteers were acquired at rest and analyzed by region of interest (ROI)-based functional connectivity. Blood-oxygen-level-dependent (BOLD) signal fluctuations of separate six ROIs located in the right and left posterior, medial, and anterior STS were successively used to identify significant temporal correlations with BOLD signal fluctuations of other brain regions. Low-frequency BOLD signals of the right and left posterior, medial, and lateral STS share a common bilateral circuit encompassing the ventrolateral prefrontal, premotor/motor, insular, parietal temporal, occipital, and cerebellar cortices (lobules VI/VIIA), thalamus, and striatum. The STS-centered network (1) is intrinsically connected during the brain resting, (2) encompasses the whole caudalmost two thirds of STS, (3) may partly represent the whole STS structural connectivity, and includes the motor and cognitive neocerebellum (lobules VI/VIIA).

Development of a Large-Scale Functional Brain Network during Human Non-Rapid Eye Movement Sleep

Graph theoretical analysis of functional magnetic resonance imaging (fMRI) time series has revealed a small-world organization of slow-frequency blood oxygen level-dependent (BOLD) signal fluctuations during wakeful resting. In this study, we used graph theoretical measures to explore how physiological changes during sleep are reflected in functional connectivity and small-world network properties of a large-scale, low-frequency functional brain network. Twenty-five young and healthy participants fell asleep during a 26.7 min fMRI scan with simultaneous polysomnography. A maximum overlap discrete wavelet transformation was applied to fMRI time series extracted from 90 cortical and subcortical regions in normalized space after residualization of the raw signal against unspecific sources of signal fluctuations; functional connectivity analysis focused on the slow-frequency BOLD signal fluctuations between 0.03 and 0.06 Hz. We observed that in the transition from wakefulness to light sleep, thalamocortical connectivity was sharply reduced, whereas corticocortical connectivity increased; corticocortical connectivity subsequently broke down in slow-wave sleep. Local clustering values were closest to random values in light sleep, whereas slow-wave sleep was characterized by the highest clustering ratio (gamma). Our findings support the hypothesis that changes in consciousness in the descent to sleep are subserved by reduced thalamocortical connectivity at sleep onset and a breakdown of general connectivity in slow-wave sleep, with both processes limiting the capacity of the brain to integrate information across functional modules.

Alcohol increases spontaneous BOLD signal fluctuations in the visual network

Brain activity during resting wakefulness is characterized by slow (< 0.1 Hz) fluctuations of blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals that are topographically organized in discrete functional connectivity networks (resting-state networks, RSNs). The present study aimed at revealing possible network-specific alcohol-induced changes in resting-state fMRI (RS-fMRI) signals. RS-fMRI was carried out on eight healthy subjects in four consecutive 6-min sessions, one before and three after a 0.7 g/kg dose of ethyl alcohol. Control experiments were carried out in different days without alcohol administration. Independent component analysis (ICA) was performed on all experimental and control scans to extract individual and group-level RSN maps in a dynamic network analysis. Alcohol administration significantly increased the overall strength of the visual network ICA component, reaching the peak at 90 min. Within the visual network, the alcohol-induced increase was more pronounced in the primary regions of the occipital cortex and less pronounced in the secondary regions of the occipito-temporal cortex. Other major RSN components, such as the default-mode, the fronto-parietal, the sensori-motor, the self-referential and the auditory components, did not exhibit alcohol-induced changes during the same time window. Alcohol-induced effects on the resting-state functional connectivity of the visual network observed in the present study demonstrate that the visual system is a selective and primary target of acute alcohol administration. The strong enhancement of spontaneous BOLD fluctuations in the primary visual cortex in an acute alcoholic state may impair the normal activation response to visual stimuli and affect visual perception.

Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA

Functional magnetic resonance imaging (fMRI) based on the so-called blood oxygen level-dependent (BOLD) contrast is a powerful tool for studying brain function not only locally but also on the large scale. Most studies assume a simple relationship between neural and BOLD activity, in spite of the fact that it is important to elucidate how the “when” and “what” components of neural activity are correlated to the “where” of fMRI data. Here we conducted simultaneous recordings of neural and BOLD signal fluctuations in primary visual (V1) cortex of anesthetized monkeys. We explored the neurovascular relationship during periods of spontaneous activity by using temporal kernel canonical correlation analysis (tkCCA). tkCCA is a multivariate method that can take into account any features in the signals that univariate analysis cannot. The method detects filters in voxel space (for fMRI data) and in frequency–time space (for neural data) that maximize the neurovascular correlation without any assumption of a hemodynamic response function (HRF). Our results showed a positive neurovascular coupling with a lag of 4–5 s and a larger contribution from local field potentials (LFPs) in the γ range than from low-frequency LFPs or spiking activity. The method also detected a higher correlation around the recording site in the concurrent spatial map, even though the pattern covered most of the occipital part of V1. These results are consistent with those of previous studies and represent the first multivariate analysis of intracranial electrophysiology and high-resolution fMRI.

Resting state networks in human cervical spinal cord observed with fMRI

It has been reported that spontaneous fluctuations of blood oxygen level dependent (BOLD) signals can be detected in human brain and constitute resting state networks. It has not been reported whether resting state networks also exist in human spinal cord. In the present study, we investigate spontaneous BOLD signal changes in human cervical spinal cord during resting state. fMRI data were analyzed with independent component analysis and SPM software package. Acceptable reproducibility of spatial maps of BOLD signal changes was found across sessions, with the highest correlation values ranging from 0.18 to 0.44. The dominant frequency of signal changes from independent components with the highest correlation values was approximately the frequency range of the respiratory circle. Activities of spinal motor neurons innervating the scalenes were considered as a major factor in the production of BOLD signal fluctuations were observed in this study. Our findings suggest that BOLD fMRI can be applied to study the features of low-frequency rhythmic activities and corresponding mechanisms in the spinal cord during resting state.

Functional connectivity of the human rostral and caudal cingulate motor areas in the brain resting state at 3T

Three cingulate motor areas have been described in monkeys, the rostral, dorsal, and ventral cingulate motor areas, and would control limbic-related motor activity. However, little anatomical data are available in human about the functional networks these cingulate areas underlie. Therefore, networks anchored in the rostral and caudal cingulate motor areas (rCMA and cCMA, respectively) were studied in human using functional connectivity during the brain resting state. Since the rCMA and cCMA are located just under the pre-supplementary and supplementary motor areas (pre-SMA and SMA), the pre-SMA- and SMA-centered networks were also studied to ensure that these four circuits were correctly dissociated. Data from 14 right-handed healthy volunteers were acquired at rest and analyzed by region of interest (ROI)-based functional connectivity. The blood oxygenation level-dependent (BOLD) signal fluctuations of separate ROIs located in rCMA, cCMA, pre-SMA, and SMA were successively used to identify significant temporal correlations with BOLD signal fluctuations of other brain regions. Low-frequency BOLD signal of the CMA was correlated with signal fluctuations in the prefrontal, cingulate, insular, premotor, motor, medial and inferior parietal cortices, putamen and thalamus, and anticorrelated with the default-mode network. rCMA was more in relation with prefrontal, orbitofrontal, and language-associated cortices than cCMA more related to sensory cortex. These cingulate networks were very similar to the pre-SMA- and SMA-centered networks, although pre-SMA and SMA showed stronger correlation with the prefrontal and inferior parietal cortices and with the cerebellum and the superior parietal cortex, respectively. The human cingulate motor areas constitute an interface between sensorimotor, limbic and executive systems, sharing common cortical, striatal, and thalamic relays with the overlying premotor medial areas.

Contrasting Activity Profile of Two Distributed Cortical Networks as a Function of Attentional Demands

Recent human functional MRI (fMRI) studies have revealed that two widely distributed groups of cortical areas display inverse changes in activity when attentional demands increase, with one group showing higher (task-on) and the second lower (task-off) blood oxygen level-dependent (BOLD) signals. Moreover, task-on and task-off regions also exhibit slow (<0.2 Hz) inversely correlated fluctuations in BOLD signal at rest. However, the neuronal correlates of these reciprocal BOLD signal fluctuations are unknown. Here, we addressed this question using simultaneous recordings of unit activity and local field potentials (LFPs) in the cat homologues of task-on and task-off regions. In all states of vigilance, LFP power was lower in task-off than task-on regions with no difference in firing rates. Both sets of regions displayed slow (0.5-0.15 Hz) cyclical modulations in LFP power in all frequency bands but with large and variable phase differences such that task-on and task-off regions were often anticorrelated. Inversely correlated LFP power fluctuations were state-dependent in that they were much more frequent in waking and paradoxical sleep than in slow-wave sleep. Moreover, consistent with fMRI findings, when attentional demands increased, LFP power in task-on and task-off regions changed in opposite directions, further augmenting and decreasing, respectively. At odds with previous fMRI studies, however, the decreased LFP power in task-off regions was associated with increased firing rates, suggesting that the engagement of task-off regions might not be reduced but in fact enhanced during attention.

Resting-state functional connectivity in animal models: modulations by exsanguination.

We studied the spatiotemporal characteristics of the resting state low frequency fluctuations in functional MRI (fMRI), blood oxygenation level dependent (BOLD) signal in isoflurane-anesthetized rats. fMRI-BOLD measurements at 9.4 Telsa were made during normal and exsanguinated condition previously known to alter cerebral blood flow (CBF) fluctuations in anesthetized rats. fMRI signal time series were low-pass filtered and studied by spectral analysis. During normal conditions, baseline mean arterial pressure (MAP) was 110 +/- 10 mm Hg and low-frequency fluctuations in BOLD signal were observed in the frequency range of 0.01 - 0.125 Hz. Following blood withdrawal (exsanguination), MAP decreased to 68 +/- 7 mm Hg, resulting in an increase in the amplitude of the low-frequency fluctuations in BOLD signal time series and an increase in power at several frequencies between 0.01 and 0.125 Hz. Spatially, the BOLD fluctuations were confined to the cortex and thalamus spanning both hemispheres with sparse presence in the caudate putamen and hippocampus during both normal and exsanguinated states. Spatial distribution of the low frequency fluctuations in BOLD signal, from cross correlation analysis, indicates substantial inter-hemispheric synchrony similar to that observed in the conscious human brain. The behavior of the resting state BOLD signal fluctuations similar to CBF fluctuations during exsanguination indicates a myogenic dependence. Also, a high inter-hemispheric synchrony combined with different phase characteristics of the low frequency BOLD fluctuations particularly in the hippocampus relative to the cortex emphasizes distinct functional networks.

Electrophysiological signatures of resting state networks in the human brain

Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.

Dynamic Forcing of End-Tidal Carbon Dioxide and Oxygen Applied to Functional Magnetic Resonance Imaging

Investigations into the blood oxygenation level-dependent (BOLD) functional MRI signal have used respiratory challenges with the aim of probing cerebrovascular physiology. Such challenges have altered the inspired partial pressures of either carbon dioxide or oxygen, typically to a fixed and constant level (fixed inspired challenge (FIC)). The resulting end-tidal gas partial pressures then depend on the subject's metabolism and ventilatory responses. In contrast, dynamic end-tidal forcing (DEF) rapidly and independently sets end-tidal oxygen and carbon dioxide to desired levels by altering the inspired gas partial pressures on a breath-by-breath basis using computer-controlled feedback. This study implements DEF in the MRI environment to map BOLD signal reactivity to CO(2). We performed BOLD (T2(*)) contrast FMRI in four healthy male volunteers, while using DEF to provide a cyclic normocapnic-hypercapnic challenge, with each cycle lasting 4 mins (PET(CO(2)) mean+/-s.d., from 40.9+/-1.8 to 46.4+/-1.6 mm Hg). This was compared with a traditional fixed-inspired (FI(CO(2))=5%) hypercapnic challenge (PET(CO(2)) mean+/-s.d., from 38.2+/-2.1 to 45.6+/-1.4 mm Hg). Dynamic end-tidal forcing achieved the desired target PET(CO(2)) for each subject while maintaining PET(O(2)) constant. As a result of CO(2)-induced increases in ventilation, the FIC showed a greater cyclic fluctuation in PET(O(2)). These were associated with spatially widespread fluctuations in BOLD signal that were eliminated largely by the control of PET(O(2)) during DEF. The DEF system can provide flexible, convenient, and physiologically well-controlled respiratory challenges in the MRI environment for mapping dynamic responses of the cerebrovasculature.

Task demand modulation of steady‐state functional connectivity to primary motor cortex

Correlations in blood oxygen level-dependent (BOLD) MRI signals from separate areas within the human brain have been used as a measure of functional connectivity. Steady-state measures of interregional correlations are particularly useful because they do not depend on the specific design of a task nor on subtracting conditions in a blocked design task. However, the conditions under which such correlations are measured may influence these indices of functional connectivity. The aim of this study was to investigate the influence of task demand on interregional correlations within the motor system. Specifically, tapping rates in audibly paced finger-tapping tasks were controlled and varied between runs in order to observe their effects on interregional correlations to contralateral primary motor cortex (PM). Regions of interest included the supplementary motor area, ipsilateral cerebellum, ipsilateral auditory cortex, and a control region. It was found that tapping rate was a significant factor in determining the mean correlation of some regions to PM, and that correlations measured during tapping in general increased relative to resting state. Furthermore, analysis of the percent of voxels in each region significantly correlated to PM suggested that changes in the mean correlation of that region to PM could be accounted for by changes in the fraction of significantly correlated voxels within a region. This provides insight into the manner in which steady-state correlations are modified in response to different task demands and further evidence that low-frequency fluctuations in BOLD signals reflect functional connectivity.

Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages

A number of recent studies of human brain activity using blood-oxygen-level-dependent (BOLD) fMRI and EEG have reported the presence of spatiotemporal patterns of correlated activity in the absence of external stimuli. Although these patterns have been hypothesized to contain important information about brain architecture, little is known about their origin or about their relationship to active cognitive processes such as conscious awareness and monitoring of the environment. In this study, we have investigated the amplitude and spatiotemporal characteristics of resting-state activity patterns and their dependence on the subjects' alertness. For this purpose, BOLD fMRI was performed at 3.0 T on 12 normal subjects using a visual stimulation protocol, followed by a 27 min rest period, during which subjects were allowed to fall asleep. In subjects who were asleep at the end of the scan, we found (a) a higher amplitude of BOLD signal fluctuation during rest compared with subjects who were awake at the end of the scan; (b) spatially independent patterns of correlated activity that involve all of gray matter, including deep brain nuclei; (c) many patterns that were consistent across subjects; (d) that average percentage levels of fluctuation in visual cortex (VC) and whole brain were higher in subjects who were asleep (up to 1.71% and 1.16%, respectively) than in those who were awake (up to 1.15% and 0.96%) at the end of the scan and were comparable with those levels evoked by intense visual stimulation (up to 1.85% and 0.76% for two subject groups); (e) no confirmation of correlation, positive or negative, between thalamus and VC found in earlier studies. These findings suggest that resting-state activity continues during sleep and does not require active cognitive processes or conscious awareness.

A comparison of signal instability in 2D and 3D EPI resting-state fMRI

Spatiotemporally structured noise, such as physiological noise, is a potential source of artifacts in functional magnetic resonance imaging (fMRI) and is the main limiting factor for the detection of small blood oxygen level-dependent (BOLD) signal variations. fMRI was employed to detect low-frequency BOLD signal fluctuations, which are thought to be related to spontaneous neuronal activity in the resting human brain. The sensitivity to noise, that is, signal variations of non-BOLD origin, was investigated for two- (2D) and three-dimensional (3D) imaging techniques. Incomplete relaxation between subsequent scans increases the level of temporally and spatially correlated signal variations originating from physiological and/or systemic noise. Although inflow effects are suspected to be reduced in 3D echo-planar imaging (EPI) compared with multi-slice 2D EPI, the noise level was higher in the 3D technique. The noise level in 3D fMRI experiments was significantly increased by instabilities of the transverse steady-state magnetization as the repetition time was of the order of T(2). By implementing radiofrequency spoiling, temporal signal fluctuations and erroneous inter-regional correlation in connectivity maps were diminished to a level present in data sets acquired with 2D EPI.

Brain metabolic fluctuations in absence of stimuli

Mapping of brain function with blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) BOLD-MRI relies on the detection of focal changes in cerebral blood flow (CBF) in response to conditioned stimuli. However, in the absence of stimuli, the brain continues to show temporal fluctuations in blood flow as measured with BOLD and perfusion-based MRI (Biswal, NMR. Biomed. 1997). These fluctuations are substantially synchronized across functional regions that have an apparent functional relationship, and therefore might allow mapping and classification of the networks that underlie human brain function without the need for carefully conditioned stimuli. Despite their potential functional siginificance, the origin of the blood flow fluctuations has not been established. Potential sources include cognitive processes, fluctuations in vigilance and conscious awareness, and homeostatic (restorative) processes. Alternatively, the fluctuations might be caused by purely vascular events (e.g. vasomotor effect), without a substantial metabolic or neuronal component. In this study we used MRI methods to establish whether blood flow fluctuations in absence of stimuli subserve a metabolic process. For this purpose, we performed simultaneous BOLD and perfusion MRI at 3.0 T on 7 normal volunteers during a visual task (5 min checkerboard-grey paradigm) and an extended (25 min) rest period. The ratio between BOLD and perfusion changes was used as an indicator of metabolism (Hoge, Proc. Nat. Acad. Sci. 1999). As reference, a 10-minute breath-holding paradigm was inserted between the two conditions. The paradigm consisted of 5 stages of 40 s breath-hold, 80 s normal breathing. Physiologic monitoring included respiratory and cardiac cycles, as well as scalp potentials using a 64-channel EEG system. During rest conditions, we found substantial BOLD and perfusion signal fluctuations in most of neocortex, with strong correlations between functionally related regions. No significant correlations were found with cardiac and respiratory cycles. Frequency analysis of the fluctuations suggested that most energy was concentrated in the 0.01–0.1 Hz band. The strongest fluctuations were observed during early (non-REM) sleep, as identified from EEG. Within visual cortex (VC), the amplitude of the fluctuations reached a level similar to that evoked with the task. BOLD and perfusion signals were highly correlated over most of cortex. The ratio of their fluctuation amplitude in VC averaged 1.66(0.41), 2.82(0.70), and 1.80(0.57) for task, breath holding paradigm, and rest (sleep) respectively. The difference between task and rest was insignificant (p=0.56), while the ratios during task and rest were significantly (p=0.0003/0.017) lower than during the breath-holding paradigm. The lower ratios are indicative of a relatively high oxygen extraction, suggesting involvement of a metabolic process during task and rest, and less so during breathholding. The findings indicate that spatially correlated fluctuations in CBF in absence of stimuli have a metabolic component and continue during early sleep. This has important implication for the design of brain mapping experiments and could shed light on the physiologic processes present during of rest and sleep. Further experiments are planned to investigate a potential role of processes facilitating synaptic plasticity (Huber, Nature 2004).

Spontaneous low‐frequency BOLD signal fluctuations: An fMRI investigation of the resting‐state default mode of brain function hypothesis

Recent neuroimaging studies have lead to the proposal that rest is characterized by an organized, baseline level of activity, a default mode of brain function that is suspended during specific goal-oriented mental activity. Previous studies have shown that the primary function subserved by the default mode is that of an introspectively oriented, self-referential mode of mental activity. The default mode of brain function hypothesis is readdressed from the perspective of the presence of low-frequency blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal changes (0.012-0.1 Hz) in the resting brain. The results show that the brain during rest is not tonically active in a single mode of brain function. Rather, the findings presented here suggest that the brain recurrently toggles between an introspectively oriented mode (default mode) and a state-of-mind that tentatively might be interpreted as an extrospectively oriented mode that involves a readiness and alertness to changes in the external and internal environment.