Spontaneous Blood Oxygen Level-dependent Fluctuations Research Articles

Resting-State Functional Connectivity in Mathematical Expertise.

To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians and non-mathematicians were distinguished depending on features of functional connectivity. We showed diverging involvement of the frontal–thalamic–temporal connections for mathematicians and the medial–frontal areas to precuneus and the lateral orbital gyrus to thalamus connections for non-mathematicians. Moreover, mathematicians who had higher scores in mathematical knowledge showed a weaker connection strength between the left and right caudate nucleus, demonstrating the connections’ characteristics related to mathematical expertise. Separate functional networks between the two groups were validated with a maximum classification accuracy of 91.19% using the distinct resting-state fMRI-based functional connectivity features. We suggest the advantageous role of preconfigured resting-state functional connectivity, as well as the neural efficiency for experts’ successful performance.

Verification of a Central Pacemaker in Brain Stem by Phase-Coupling Analysis Between HR Interval- and BOLD-Oscillations in the 0.10-0.15 Hz Frequency Band.

The origin of slow intrinsic oscillations in resting states of functional magnetic resonance imaging (fMRI) signals is still a matter of debate. The present study aims to test the hypothesis that slow blood oxygenation level-dependent (BOLD) oscillations with frequency components greater than 0.10 Hz result from a central neural pacemaker located in the brain stem. We predict that a central oscillator modulates cardiac beat-to-beat interval (RRI) fluctuations rapidly, with only a short neural lag around 0.3 s. Spontaneous BOLD fluctuations in the brain stem, however, are considerably delayed due to the hemodynamic response time of about ∼2–3 s. In order to test these predictions, we analyzed the time delay between slow RRI oscillations from thorax and BOLD oscillations in the brain stem by calculating the phase locking value (PLV). Our findings show a significant time delay of 2.2 ± 0.2 s between RRI and BOLD signals in 12 out of 23 (50%) participants in axial slices of the pons/brain stem. Adding the neural lag of 0.3 s to the observed lag of 2.2 s we obtain 2.5 s, which is the time between neural activity increase and BOLD increase, termed neuro-BOLD coupling. Note, this time window for neuro-BOLD coupling in awake humans is surprisingly of similar size as in awake head-fixed adult mice (Mateo et al., 2017).

Abnormal Blood Oxygen Level-Dependent Fluctuations in Focal Cortical Dysplasia and the Perilesional Zone: Initial Findings.

Focal cortical dysplasia is a common cause of intractable epilepsy for which neurosurgery is an option. Delineations of a focal cortical dysplasia lesion on structural brain images may not necessarily reflect the functional borders of normal tissue. Our objective was to determine whether abnormalities in spontaneous blood oxygen level-dependent fluctuations arise in focal cortical dysplasia lesions and proximal regions. Fourteen patients with focal cortical dysplasia-related epilepsy and 16 healthy controls underwent structural and resting-state functional MR imaging. Three known blood oxygen level-dependent measures were determined, including the fractional amplitude of low-frequency fluctuations, regional homogeneity, and wavelet entropy. These measures were evaluated in the lesion and perilesional zone and normalized to the contralateral cortex of patients with focal cortical dysplasia and healthy controls. Patients showed significantly decreased fractional amplitude of low-frequency fluctuations and increased wavelet entropy in the focal cortical dysplasia lesion and the perilesional zone (≤2 cm) relative to the contralateral homotopic cortex and the same regions in healthy controls. Regional homogeneity was significantly increased in the focal cortical dysplasia lesion compared with the contralateral homotopic cortex and healthy controls. Abnormalities in spontaneous blood oxygen level-dependent fluctuations were seen up to 2 cm distant from the radiologically visible boundary. It was demonstrated that functional boundaries go beyond structural boundaries of focal cortical dysplasia lesions. Validation is required to reveal whether this information is valuable for surgical planning and outcome evaluation of focal cortical dysplasia lesions and comparing current results with electrophysiologic analysis.

Multiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord.

Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.

Investigating the BOLD spectral power of the intrinsic connectivity networks in fibromyalgia patients: A resting-state fMRI study.

Recent advances in multivariate statistical analysis of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) have provided novel insights into the network organization of the human brain. Here, we applied group independent component analysis, a well-established approach for detecting brain intrinsic connectivity networks, to examine the spontaneous BOLD fluctuations in patients with fibromyalgia and healthy controls before and after exposure to a stressor. The BOLD spectral power characteristics of component time courses were calculated using the fast Fourier transform (FFT) algorithm, and group comparison was performed at six frequency bins between 0 and 0.24 Hz at 0.04 Hz intervals. Relative to controls, patients with fibromyalgia displayed significant BOLD spectral power differences in the default-mode, salience, and subcortical networks at the baseline level (PBon ferroni-corrected <; 0.05). Multivariate analysis of covariance (MANCOVA) further revealed significant effects of the cold water temperature, and pain rating on the spectral power of the sensorimotor, salience, and prefrontal networks, while the diagnosis of fibromyalgia influenced the BOLD spectral power of the salience and subcortical networks (PFDR-corrected <; 0.05). Since the BOLD spectral power reflects the degree of fluctuations within a network, future studies of the correlation between BOLD spectral power and pain processing can cast additional light on the nature of the central nervous system dysfunction in patients with chronic pain syndromes.

Brain Resting-State Functional Connectivity Is Preserved Under Sevoflurane Anesthesia in Patients with Pervasive Developmental Disorders: A Pilot Study.

Functional connectivity studies play a huge role in understanding the relationship between the network connections and the behavioral phenotype of patients with pervasive developmental disorders (PDD). Some patients with PDD may not be able to tolerate the imaging procedure while they are awake, and, hence, they often need general anesthesia. General anesthesia is a confounding factor in functional imaging studies due to its effect on the functional connectivity. The objective of this study is to look at the resting-state functional connectivity (RS-FC) under sevoflurane anesthesia in patients with PDDs. Thirteen adults with PDD scheduled for magnetic resonance imaging (MRI) of the brain under general anesthesia were recruited for the study. Resting-state functional MRI (fMRI) scans were acquired at 1 minimum alveolar concentration (MAC) of sevoflurane. Spontaneous blood oxygenation level-dependent fluctuations were measured, and a seed-voxel analysis was done to identify the resting-state networks. Subjects' data were compared with data from 16 nonanesthetized healthy controls. Six networks (default mode network [DMN], executive control network [ECN], salience network [SN], auditory, visual, and sensorimotor) were investigated. At 1 MAC sevoflurane anesthesia, RS-FC was preserved in all the networks. Secondary analysis of connectivity showed a decrease in connectivity within the thalamus and an increase in DMN-ECN and DMN-SN cross-network connectivity in the anesthetized patient group compared to healthy controls. Previous reports suggested that even mild levels of anesthesia could reduce overall fluctuation levels in the major brain. However, our results provide strong evidence that most networks can sustain detectable levels of activity in patients with PDDs even under deep levels of anesthesia.

Towards prognostic biomarkers from BOLD fluctuations to differentiate a first epileptic seizure from new‐onset epilepsy

The diagnosis of epilepsy cannot be reliably made prior to a patient's second seizure in most cases. Therefore, adequate diagnostic tools are needed to differentiate subjects with a first seizure from those with a seizure preceding the onset of epilepsy. The objective was to explore spontaneous blood oxygen level-dependent (BOLD) fluctuations in subjects with a first-ever seizure and patients with new-onset epilepsy (NOE), and to find characteristic biomarkers for seizure recurrence after the first seizure. We examined 17 first-seizure subjects, 19 patients with new-onset epilepsy (NOE), and 18 healthy controls. All subjects underwent clinical investigation and received electroencephalography and resting-state functional magnetic resonance imaging (MRI). The BOLD time series were analyzed in terms of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFFs). We found significantly stronger amplitudes (higher fALFFs) in patients with NOE relative to first-seizure subjects and healthy controls. The frequency range of 73-198 mHz (slow-3 subband) appeared most useful for discriminating patients with NOE from first-seizure subjects. The ReHo measure did not show any significant differences. The fALFF appears to be a noninvasive measure that characterizes spontaneous BOLD fluctuations and shows stronger amplitudes in the slow-3 subband of patients with NOE relative first-seizure subjects and healthy controls. A larger study population with follow-up is required to determine whether fALFF holds promise as a potential biomarker for identifying subjects at increased risk to develop epilepsy.

How networks communicate: propagation patterns in spontaneous brain activity.

Initially regarded as 'noise', spontaneous (intrinsic) activity accounts for a large portion of the brain's metabolic cost. Moreover, it is now widely known that infra-slow (less than 0.1 Hz) spontaneous activity, measured using resting state functional magnetic resonance imaging of the blood oxygen level-dependent (BOLD) signal, is correlated within functionally defined resting state networks (RSNs). However, despite these advances, the temporal organization of spontaneous BOLD fluctuations has remained elusive. By studying temporal lags in the resting state BOLD signal, we have recently shown that spontaneous BOLD fluctuations consist of remarkably reproducible patterns of whole brain propagation. Embedded in these propagation patterns are unidirectional 'motifs' which, in turn, give rise to RSNs. Additionally, propagation patterns are markedly altered as a function of state, whether physiological or pathological. Understanding such propagation patterns will likely yield deeper insights into the role of spontaneous activity in brain function in health and disease.This article is part of the themed issue 'Interpreting blood oxygen level-dependent: a dialogue between cognitive and cellular neuroscience'.

EP 115. Effective connectivity of subcortical–cortical networks revealed by simultaneous scalp and depth EEG recordings in humans

Functional magnetic resonance imaging (fMRI) studies showed that the brain at rest exhibits spontaneous BOLD (Blood Oxygenation Level Dependent) fluctuations over time that correlate between functionally connected brain areas ( Biswal et al., 1995 ). However, the lower temporal resolution of fMRI precludes the study of neuronal coding and temporal information flow with an appropriate level of temporal acuity in these networks. EEG is better suited for the study of the temporal dynamics in such networks because of its millisecond resolution; however, due to its limited spatial resolution, contributions from subcortical structures are likely not well represented. Not surprisingly though, results from fMRI resting state studies clearly indicate that subcortical structures are important key players in these networks. In order to gain better insights into the interactions of cortical–subcortical circuits at rest, we performed recordings from multiple scalp electrodes simultaneously with chronically implanted deep brain stimulation electrodes in subcortical targets of human subjects. Computed partial directed coherence based on Granger causality ( Plomp et al., 2014 ) was performed to identify the major drivers of the network and the sites that were subject to them. Here we report on obsessive–compulsive disorder patients who were bilaterally implanted in the nucleus accumbens as well as Tourette syndrome patients with bilateral thalamic implants. In all patients, local circumscribed networks surrounding specific subcortical electrodes were identified as major drivers of the larger pathological network. Recordings which were performed with 256-channel scalp EEG electrodes were subject to source localization methods and connectivity analysis was performed in the source space ( Coito et al., 2015 ). Our cortical–subcortical simultaneous recordings provide the platform for a deeper understanding of the temporal dynamics of whole-brain networks in humans, which includes the intimate contribution of deep structures and opens new ways of identifying neurophysiological markers of these psychiatric diseases.

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].

Quasi-periodic patterns (QPP): Large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders.

The resting‐state neurovascular coupling relationship: rapid changes in spontaneous neural activity in the somatosensory cortex are associated with haemodynamic fluctuations that resemble stimulus‐evoked haemodynamics

Although promise exists for patterns of resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) brain connectivity to be used as biomarkers of early brain pathology, a full understanding of the nature of the relationship between neural activity and spontaneous fMRI BOLD fluctuations is required before such data can be correctly interpreted. To investigate this issue, we combined electrophysiological recordings of rapid changes in multi-laminar local field potentials from the somatosensory cortex of anaesthetized rats with concurrent two-dimensional optical imaging spectroscopy measurements of resting-state haemodynamics that underlie fluctuations in the BOLD fMRI signal. After neural 'events' were identified, their time points served to indicate the start of an epoch in the accompanying haemodynamic fluctuations. Multiple epochs for both neural 'events' and the accompanying haemodynamic fluctuations were averaged. We found that the averaged epochs of resting-state haemodynamic fluctuations taken after neural 'events' closely resembled the temporal profile of stimulus-evoked cortical haemodynamics. Furthermore, we were able to demonstrate that averaged epochs of resting-state haemodynamic fluctuations resembling the temporal profile of stimulus-evoked haemodynamics could also be found after peaks in neural activity filtered into specific electroencephalographic frequency bands (theta, alpha, beta, and gamma). This technique allows investigation of resting-state neurovascular coupling using methodologies that are directly comparable to that developed for investigating stimulus-evoked neurovascular responses.

Dissociated mean and functional connectivity BOLD signals in visual cortex during eyes closed and fixation.

We investigated the effects of resting state type on blood oxygen level-dependent (BOLD) signal and functional connectivity in two paradigms: participants either alternated between fixation and eyes closed or maintained fixation or eyes closed throughout each scan. The BOLD signal and functional connectivity of lower and higher tiers of the visual cortical hierarchy were found to be differentially modulated during eyes closed versus fixation. Fixation was associated with greater mean BOLD signals in primary visual cortex and lower mean BOLD signals in extrastriate visual areas than periods of eyes closed. In addition, analysis of thalamocortical functional connectivity during scans in which participants maintained fixation showed synchronized BOLD fluctuations between those thalamic nuclei whose mean BOLD signal was systematically modulated during alternating epochs of eyes closed and fixation, primary visual cortex and the attention network, while during eyes closed negatively correlated fluctuations were seen between the same thalamic nuclei and extrastriate visual areas. Finally, in all visual areas the amplitude of spontaneous BOLD fluctuations was greater during eyes closed than during fixation. The dissociation between early and late tiers of visual cortex, which characterizes both mean and functionally connected components of the BOLD signal, may depend on the reorganization of thalamocortical networks. Since dissociated changes in local blood flow also characterize transitions between different stages of sleep and wakefulness (Braun AR, Balkin TJ, Wesenten NJ, Gwadry F, Carson RE, Varga M, Baldwin P, Belenky G, Herscovitch P. Science 279: 91-95, 1998), our results suggest that dissociated endogenous neural activity in primary and extrastriate cortex may represent a general aspect of brain function.

Caffeine increases the temporal variability of resting-state BOLD connectivity in the motor cortex

Correlations between spontaneous fluctuations in the blood oxygenation level dependent (BOLD) signal measured with functional MRI are finding increasing use as measures of functional connectivity in the brain, where differences can potentially predict cognitive performance and diagnose disease. Caffeine, which is a widely consumed neural stimulant and vasoactive agent, has been found to decrease the amplitude and correlation of resting-state BOLD fluctuations, and hence is an important factor to consider in functional connectivity studies. However, because the BOLD signal is sensitive to neural and vascular factors, the physiological mechanisms by which caffeine alters spontaneous BOLD fluctuations remain unclear. Resting-state functional connectivity has traditionally been assessed using stationary measures, such as the correlation coefficient between BOLD signals measured across the length of a scan. However, recent work has shown that the correlation of resting-state networks can vary considerably over time, with periods as short as 10 s. In this study, we used a sliding window correlation analysis to assess temporal variations in resting-state functional connectivity of the motor cortex before and after caffeine ingestion. We found that the temporal variability of BOLD correlation was significantly higher following a caffeine dose, with transient periods of strong correlation alternating with periods of low or negative correlation. This phenomenon was primarily due to increased variability in the phase difference between BOLD time courses in the left and right motor cortices. These results indicate that caffeine may cause underlying spontaneous neural fluctuations to go in and out of coherence more frequently, and emphasizes the need to consider non-stationary measures when studying changes in functional connectivity.

Breakdown of within- and between-network Resting State Functional Magnetic Resonance Imaging Connectivity during Propofol-induced Loss of Consciousness

Mechanisms of anesthesia-induced loss of consciousness remain poorly understood. Resting-state functional magnetic resonance imaging allows investigating whole-brain connectivity changes during pharmacological modulation of the level of consciousness. Low-frequency spontaneous blood oxygen level-dependent fluctuations were measured in 19 healthy volunteers during wakefulness, mild sedation, deep sedation with clinical unconsciousness, and subsequent recovery of consciousness. Propofol-induced decrease in consciousness linearly correlates with decreased corticocortical and thalamocortical connectivity in frontoparietal networks (i.e., default- and executive-control networks). Furthermore, during propofol-induced unconsciousness, a negative correlation was identified between thalamic and cortical activity in these networks. Finally, negative correlations between default network and lateral frontoparietal cortices activity, present during wakefulness, decreased proportionally to propofol-induced loss of consciousness. In contrast, connectivity was globally preserved in low-level sensory cortices, (i.e., in auditory and visual networks across sedation stages). This was paired with preserved thalamocortical connectivity in these networks. Rather, waning of consciousness was associated with a loss of cross-modal interactions between visual and auditory networks. Our results shed light on the functional significance of spontaneous brain activity fluctuations observed in functional magnetic resonance imaging. They suggest that propofol-induced unconsciousness could be linked to a breakdown of cerebral temporal architecture that modifies both within- and between-network connectivity and thus prevents communication between low-level sensory and higher-order frontoparietal cortices, thought to be necessary for perception of external stimuli. They emphasize the importance of thalamocortical connectivity in higher-order cognitive brain networks in the genesis of conscious perception.

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.

Learning and Memory: While You Rest, Your Brain Keeps Working

A recent study shows that brain activity recorded while the human subject is at 'rest' is significantly affected by a prior learning episode. These results suggest that understanding resting brain activity may be critical to understanding how humans learn from experience.

Functional connectivity in the default network during resting state is preserved in a vegetative but not in a brain dead patient

Recent studies on spontaneous fluctuations in the functional MRI blood oxygen level-dependent (BOLD) signal in awake healthy subjects showed the presence of coherent fluctuations among functionally defined neuroanatomical networks. However, the functional significance of these spontaneous BOLD fluctuations remains poorly understood. By means of 3 T functional MRI, we demonstrate absent cortico-thalamic BOLD functional connectivity (i.e. between posterior cingulate/precuneal cortex and medial thalamus), but preserved cortico-cortical connectivity within the default network in a case of vegetative state (VS) studied 2.5 years following cardio-respiratory arrest, as documented by extensive behavioral and paraclinical assessments. In the VS patient, as in age-matched controls, anticorrelations could also be observed between posterior cingulate/precuneus and a previously identified task-positive cortical network. Both correlations and anticorrelations were significantly reduced in VS as compared to controls. A similar approach in a brain dead patient did not show any such long-distance functional connectivity. We conclude that some slow coherent BOLD fluctuations previously identified in healthy awake human brain can be found in alive but unaware patients, and are thus unlikely to be uniquely due to ongoing modifications of conscious thoughts. Future studies are needed to give a full characterization of default network connectivity in the VS patients population.

The Global Signal and Observed Anticorrelated Resting State Brain Networks

Resting state studies of spontaneous fluctuations in the functional MRI (fMRI) blood oxygen level dependent (BOLD) signal have shown great promise in mapping the brain's intrinsic, large-scale functional architecture. An important data preprocessing step used to enhance the quality of these observations has been removal of spontaneous BOLD fluctuations common to the whole brain (the so-called global signal). One reproducible consequence of global signal removal has been the finding that spontaneous BOLD fluctuations in the default mode network and an extended dorsal attention system are consistently anticorrelated, a relationship that these two systems exhibit during task performance. The dependence of these resting-state anticorrelations on global signal removal has raised important questions regarding the nature of the global signal, the validity of global signal removal, and the appropriate interpretation of observed anticorrelated brain networks. In this study, we investigate several properties of the global signal and find that it is, indeed, global, not residing preferentially in systems exhibiting anticorrelations. We detail the influence of global signal removal on resting state correlation maps both mathematically and empirically, showing an enhancement in detection of system-specific correlations and improvement in the correspondence between resting-state correlations and anatomy. Finally, we show that several characteristics of anticorrelated networks including their spatial distribution, cross-subject consistency, presence with modified whole brain masks, and existence before global regression are not attributable to global signal removal and therefore suggest a biological basis.

Electrophysiological correlates of the brain's intrinsic large-scale functional architecture

Spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signals demonstrate consistent temporal correlations within large-scale brain networks associated with different functions. The neurophysiological correlates of this phenomenon remain elusive. Here, we show in humans that the slow cortical potentials recorded by electrocorticography demonstrate a correlation structure similar to that of spontaneous BOLD fluctuations across wakefulness, slow-wave sleep, and rapid-eye-movement sleep. Gamma frequency power also showed a similar correlation structure but only during wakefulness and rapid-eye-movement sleep. Our results provide an important bridge between the large-scale brain networks readily revealed by spontaneous BOLD signals and their underlying neurophysiology.