Periods of rest in fMRI contain individual spontaneous events which are related to slowly fluctuating spontaneous activity

fMRI studies of brain activity at rest study slow (<0.1 Hz) intrinsic fluctuations in the blood‐oxygenation‐level‐dependent (BOLD) signal that are observed in a temporal scale of several minutes. The origin of these fluctuations is not clear but has previously been associated with slow changes in rhythmic neuronal activity resulting from changes in cortical excitability or neuronal synchronization. In this work, we show that individual spontaneous BOLD events occur during rest, in addition to slow fluctuations. Individual spontaneous BOLD events were identified by deconvolving the hemodynamic impulse response function for each time point in the fMRI time series, thus requiring no information on timing or a‐priori spatial information of events. The patterns of activation detected were related to the motor, visual, default‐mode, and dorsal attention networks. The correspondence between spontaneous events and slow fluctuations in these networks was assessed using a sliding window, seed‐correlation analysis, where seed regions were selected based on the individual spontaneous event BOLD activity maps. We showed that the correlation varied considerably over time, peaking at the time of spontaneous events in these networks. By regressing spontaneous events out of the fMRI signal, we showed that both the correlation strength and the power in spectral frequencies <0.1 Hz decreased, indicating that spontaneous activation events contribute to low‐frequency fluctuations observed in resting state networks with fMRI. This work provides new insights into the origin of signals detected in fMRI studies of functional connectivity. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.     

Fluctuations of the EEG‐fMRI correlation reflect intrinsic strength of functional connectivity in default mode network

Both functional magnetic resonance imaging (fMRI) and electrophysiological recordings have revealed that resting‐state functional connectivity is temporally variable in human brain. Combined full‐band electroencephalography‐fMRI (fbEEG‐fMRI) studies have shown that infraslow (<.1 Hz) fluctuations in EEG scalp potential are correlated with the blood‐oxygen‐level‐dependent (BOLD) fMRI signals and that also this correlation appears variable over time. Here, we used simultaneous fbEEG‐fMRI to test the hypothesis that correlation dynamics between BOLD and fbEEG signals could be explained by fluctuations in the activation properties of resting‐state networks (RSNs) such as the extent or strength of their activation. We used ultrafast magnetic resonance encephalography (MREG) fMRI to enable temporally accurate and statistically robust short‐time‐window comparisons of infra‐slow fbEEG and BOLD signals. We found that the temporal fluctuations in the fbEEG‐BOLD correlation were dependent on RSN connectivity strength, but not on the mean signal level or magnitude of RSN activation or motion during scanning. Moreover, the EEG‐fMRI correlations were strongest when the intrinsic RSN connectivity was strong and close to the pial surface. Conversely, weak fbEEG‐BOLD correlations were attributable to periods of less coherent or spatially more scattered intrinsic RSN connectivity, or RSN activation in deeper cerebral structures. The results thus show that the on‐average low correlations between infra‐slow EEG and BOLD signals are, in fact, governed by the momentary coherence and depth of the underlying RSN activation, and may reach systematically high values with appropriate source activities. These findings further consolidate the notion of slow scalp potentials being directly coupled to hemodynamic fluctuations.     

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.     

Low frequency BOLD fluctuations during resting wakefulness and light sleep: a simultaneous EEG-fMRI study

Recent blood oxygenation level dependent functional MRI (BOLD fMRI) studies of the human brain have shown that in the absence of external stimuli, activity persists in the form of distinct patterns of temporally correlated signal fluctuations. In this work, we investigated the spontaneous BOLD signal fluctuations during states of reduced consciousness such as drowsiness and sleep. For this purpose, we performed BOLD fMRI on normal subjects during varying levels of consciousness, from resting wakefulness to light (non-slow wave) sleep. Depth of sleep was determined based on concurrently acquired EEG data. During light sleep, significant increases in the fluctuation level of the BOLD signal were observed in several cortical areas, among which visual cortex was the most significant. Correlations among brain regions involved with the default-mode network persisted during light sleep. These results suggest that activity in areas such as the default-mode network and primary sensory cortex, as measured from BOLD fMRI fluctuations, does not require a level of consciousness typical of wakefulness.     

Slow fluctuations in eye position and resting‐state functional magnetic resonance imaging brain activity during visual fixation

The neuronal circuitry that supports voluntary changes in eye position in tasks that require attention‐driven oculo‐motor control is well known. However, less is known about the neuronal basis for eye control during visual fixation. This, together with the fact that visual fixation is one of the most commonly used baseline conditions in resting‐state functional magnetic resonance imaging (fMRI) studies, prompted us to conduct a study in which we employed resting‐state fMRI and concurrent recordings of eye gaze to investigate the relationship between spontaneous changes in eye position during passive visual fixation and intrinsic brain activity. As a control experiment, we recorded fMRI brain activity related to cued voluntary vertical and horizontal changes in eye position in a block‐related task‐evoked fMRI experiment. Our results for the voluntarily performed changes in eye position elicited brain activity in the bilateral occipitotemporal cortex, supplementary motor cortex and frontal eye fields. In contrast, we show that slow fluctuations in eye position during passive visual fixation are linked to intrinsic brain activity, foremost in midline cortical brain regions located in the posteromedial parietal cortex and the medial prefrontal cortex, brain regions that act as core cortical hubs in the brain's default mode network. Our results suggest that subconscious and sustained changes in behavior are tied to intrinsic brain activity on a moment‐by‐moment basis.     

Stimulus-induced dissociation of neuronal firing rates and local field potential gamma power and its relationship to the resonance blood oxygen level-dependent signal in macaque primary visual cortex

The functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) signal is regularly used to assign neuronal activity to cognitive function. Recent analyses have shown that the local field potential (LFP) gamma power is a better predictor of the fMRI BOLD signal than spiking activity. However, LFP gamma power and spiking activity are usually correlated, clouding the analysis of the neural basis of the BOLD signal. We show that changes in LFP gamma power and spiking activity in the primary visual cortex (V1) of the awake primate can be dissociated by using grating and plaid pattern stimuli, which differentially engage surround suppression and cross-orientation inhibition/facilitation within and between cortical columns. Grating presentation yielded substantial V1 LFP gamma frequency oscillations and significant multi-unit activity. Plaid pattern presentation significantly reduced the LFP gamma power while increasing population multi-unit activity. The fMRI BOLD activity followed the LFP gamma power changes, not the multi-unit activity. Inference of neuronal activity from the fMRI BOLD signal thus requires detailed a priori knowledge of how different stimuli or tasks activate the cortical network.     

Regional variations in vascular density correlate with resting‐state and task‐evoked blood oxygen level‐dependent signal amplitude

Functional magnetic resonance imaging (fMRI) has become one of the primary tools used for noninvasively measuring brain activity in humans. For the most part, the blood oxygen level‐dependent (BOLD) contrast is used, which reflects the changes in hemodynamics associated with active brain tissue. The main advantage of the BOLD signal is that it is relatively easy to measure and thus is often used as a proxy for comparing brain function across population groups (i.e., control vs. patient). However, it is particularly weighted toward veins whose structural architecture is known to vary considerably across the brain. This makes it difficult to interpret whether differences in BOLD between cortical areas reflect true differences in neural activity or vascular structure. We therefore investigated how regional variations of vascular density (VAD) relate to the amplitude of resting‐state and task‐evoked BOLD signals. To address this issue, we first developed an automated method for segmenting veins in images acquired with susceptibility‐weighted imaging, allowing us to visualize the venous vascular tree across the brain. In 19 healthy subjects, we then applied voxel‐based morphometry (VBM) to T1‐weighted images and computed regional measures of gray matter density (GMD). We found that, independent of spatial scale, regional variations in resting‐state and task‐evoked fMRI amplitudes were better correlated to VAD compared to GMD. Using a general linear model (GLM), it was observed that the bulk of regional variance in resting‐state activity could be modeled by VAD. Cortical areas whose resting‐state activity was most suppressed by VAD correction included Cuneus, Precuneus, Culmen, and BA 9, 10, and 47. Taken together, our results suggest that resting‐state BOLD signals are significantly related to the underlying structure of the brain vascular system. Calibrating resting BOLD activity by venous structure may result in a more accurate interpretation of differences observed between cortical areas and/or individuals. Hum Brain Mapp 35:1906–1920, 2014. © 2013 Wiley Periodicals, Inc .     

Study of the Spatial Correlation Between Neuronal Activity and BOLD fMRI Responses Evoked by Sensory and Channelrhodopsin-2 Stimulation in the Rat Somatosensory Cortex

In this work, we combined optogenetic tools with high-resolution blood oxygenation level-dependent functional MRI (BOLD fMRI), electrophysiology, and optical imaging of cerebral blood flow (CBF), to study the spatial correlation between the hemodynamic responses and neuronal activity. We first investigated the spatial and temporal characteristics of BOLD fMRI and the underlying neuronal responses evoked by sensory stimulations at different frequencies. The results demonstrated that under dexmedetomidine anesthesia, BOLD fMRI and neuronal activity in the rat primary somatosensory cortex (S1) have different frequency–dependency and distinct laminar activation profiles. We then found that localized activation of channelrhodopsin-2 (ChR2) expressed in neurons throughout the cortex induced neuronal responses that were confined to the light stimulation S1 region (<500 μm) with distinct laminar activation profile. However, the spatial extent of the hemodynamic responses measured by CBF and BOLD fMRI induced by both ChR2 and sensory stimulation was greater than 3 mm. These results suggest that due to the complex neurovascular coupling, it is challenging to determine specific characteristics of the underlying neuronal activity exclusively from the BOLD fMRI signals.     

Effects of anesthesia on BOLD signal and neuronal activity in the somatosensory cortex

Most functional magnetic resonance imaging (fMRI) animal studies rely on anesthesia, which can induce a variety of drug-dependent physiological changes, including depression of neuronal activity and cerebral metabolism as well as direct effects on the vasculature. The goal of this study was to characterize the effects of anesthesia on the BOLD signal and neuronal activity. Simultaneous fMRI and electrophysiology were used to measure changes in single units (SU), multi-unit activity (MUA), local field potentials (LFP), and the blood oxygenation level-dependent (BOLD) response in the somatosensory cortex during whisker stimulation of rabbits before, during and after anesthesia with fentanyl or isoflurane. Our results indicate that anesthesia modulates the BOLD signal as well as both baseline and stimulus-evoked neuronal activity, and, most significantly, that the relationship between the BOLD and electrophysiological signals depends on the type of anesthetic. Specifically, the behavior of LFP observed under isoflurane did not parallel the behavior of BOLD, SU, or MUA. These findings suggest that the relationship between these signals may not be straightforward. BOLD may scale more closely with the best measure of the excitatory subcomponents of the underlying neuronal activity, which may vary according to experimental conditions that alter the excitatory/inhibitory balance in the cortex.     

Spatial heterogeneity of the relation between resting‐state connectivity and blood flow: An important consideration for pharmacological studies

Resting state fMRI (RSfMRI) and arterial spin labeling (ASL) provide the field of pharmacological Neuroimaging tool for investigating states of brain activity in terms of functional connectivity or cerebral blood flow (CBF). Functional connectivity reflects the degree of synchrony or correlation of spontaneous fluctuations—mostly in the blood oxygen level dependent (BOLD) signal—across brain networks; but CBF reflects mean delivery of arterial blood to the brain tissue over time. The BOLD and CBF signals are linked to common neurovascular and hemodynamic mechanisms that necessitate increased oxygen transportation to the site of neuronal activation; however, the scale and the sources of variation in static CBF and spatiotemporal BOLD correlations are likely different. We tested this hypothesis by examining the relation between CBF and resting‐state‐network consistency (RSNC)—representing average intranetwork connectivity, determined from dual regression analysis with eight standard networks of interest (NOIs)—in a crossover placebo‐controlled study of morphine and alcohol. Overall, we observed spatially heterogeneous relations between RSNC and CBF, and between the experimental factors (drug‐by‐time, time, drug and physiological rates) and each of these metrics. The drug‐by‐time effects on CBF were significant in all networks, but significant RSNC changes were limited to the sensorimotor, the executive/salience and the working memory networks. The post‐hoc voxel‐wise statistics revealed similar dissociations, perhaps suggesting differential sensitivity of RSNC and CBF to neuronal and vascular endpoints of drug actions. The spatial heterogeneity of RSNC/CBF relations encourages further investigation into the role of neuroreceptor distribution and cerebrovascular anatomy in predicting spontaneous fluctuations under drugs. Hum Brain Mapp 35:929–942, 2014. © 2012 Wiley Periodicals, Inc.     

Granger causal influence predicts BOLD activity levels in the default mode network

Although the brain areas in the default-mode network (DMN) act in a coordinated way during rest, the activity levels in the individual areas of the DMN are highly heterogeneous. The relation between the activity levels and the pattern of causal interaction among the DMN areas remains unknown. In the present fMRI study, seven nodes of the DMN were identified and their activity levels were rank-ordered based on a power spectral analysis of the resting blood oxygenation level-dependent (BOLD) signals. Furthermore, the direction of information flow among these DMN nodes was determined using Granger causality analysis and graph-theoretic methods. We found that the activity levels in these seven DMN nodes had a highly consistent hierarchical distribution, with the highest activity level in the posterior cingulate/precuneus cortices, followed by ventral medial prefrontal cortex and dorsal medial prefrontal cortex, and with the lowest level in the left inferior temporal gyrus. Importantly, a significant correlation was found between the activity levels and the In-Out degrees of information flow across the DMN nodes, suggesting that Granger causal influences can be used to predict BOLD activity levels. These findings shed light on the dynamical organization of cortical neuronal networks and may provide the basis for characterizing network disruption by brain disorders.     

Partitioning of physiological noise signals in the brain with concurrent near-infrared spectroscopy and fMRI

The blood–oxygen level dependent (BOLD) signals measured by functional magnetic resonance imaging (fMRI) are contaminated with noise from various physiological processes, such as spontaneous low-frequency oscillations (LFOs), respiration, and cardiac pulsation. These processes are coupled to the BOLD signal by different mechanisms, and represent variations with very different frequency content; however, because of the low sampling rate of fMRI, these signals are generally not separable by frequency, as the cardiac and respiratory waveforms alias into the LFO band. In this study, we investigated the spatial and temporal characteristics of the individual noise processes by conducting concurrent near-infrared spectroscopy (NIRS) and fMRI studies on six subjects during a resting state acquisition. Three time series corresponding to LFO, respiration, and cardiac pulsation were extracted by frequency from the NIRS signal (which has sufficient temporal resolution to critically sample the cardiac waveform) and used as regressors in a BOLD fMRI analysis. Our results suggest that LFO and cardiac signals modulate the BOLD signal independently through the circulatory system. The spatiotemporal evolution of the LFO signal in the BOLD data correlates with the global cerebral blood flow. Near-infrared spectroscopy can be used to partition these contributing factors and independently determine their contribution to the BOLD signal.     

EEG‐fMRI in atypical benign partial epilepsy

Atypical benign partial epilepsy (ABPE) is a subgroup among the idiopathic focal epilepsies of childhood. Aim of this study was to investigate neuronal networks underlying ABPE and compare the results with previous electroencephalography (EEG)–functional magnetic resonance imaging (fMRI) studies of related epilepsy syndromes. Ten patients with ABPE underwent simultaneous EEG‐fMRI recording. In all 10 patients several types of interictal epileptiform discharges (IEDs) were recorded. Individual IED‐associated blood oxygen level–dependent (BOLD) signal changes were analyzed in a single subject analysis for each IED type (33 studies). A group analysis was also performed to determine common BOLD signal changes across the patients. IED‐associated BOLD signal changes were found in 31 studies. Focal BOLD signal changes concordant with the spike field (21 studies) and distant cortical and subcortical BOLD signal changes (31 studies) were detected. The group analysis revealed a thalamic activation. This study demonstrated that ABPE is characterized by patterns similar to studies in rolandic epilepsy (focal BOLD signal changes in the spike field) as well as patterns observed in continuous spikes and waves during slow sleep (CSWS) (distant BOLD signal changes in cortical and subcortical structures), thereby underscoring that idiopathic focal epilepsies of childhood form a spectrum of overlapping syndromes.     

Distinct Neurophysiological Correlates of the fMRI BOLD Signal in the Hippocampus and Neocortex

Functional magnetic resonance imaging (fMRI) is among the foremost methods for mapping human brain function but provides only an indirect measure of underlying neural activity. Recent findings suggest that the neurophysiological correlates of the fMRI blood oxygenation level-dependent (BOLD) signal might be regionally specific. We examined the neurophysiological correlates of the fMRI BOLD signal in the hippocampus and neocortex, where differences in neural architecture might result in a different relationship between the respective signals. Fifteen human neurosurgical patients (10 female, 5 male) implanted with depth electrodes performed a verbal free recall task while electrophysiological activity was recorded simultaneously from hippocampal and neocortical sites. The same patients subsequently performed a similar version of the task during a later fMRI session. Subsequent memory effects (SMEs) were computed for both imaging modalities as patterns of encoding-related brain activity predictive of later free recall. Linear mixed-effects modeling revealed that the relationship between BOLD and gamma-band SMEs was moderated by the lobar location of the recording site. BOLD and high gamma (70–150 Hz) SMEs positively covaried across much of the neocortex. This relationship was reversed in the hippocampus, where a negative correlation between BOLD and high gamma SMEs was evident. We also observed a negative relationship between BOLD and low gamma (30–70 Hz) SMEs in the medial temporal lobe more broadly. These results suggest that the neurophysiological correlates of the BOLD signal in the hippocampus differ from those observed in the neocortex.SIGNIFICANCE STATEMENT The BOLD signal forms the basis of fMRI but provides only an indirect measure of neural activity. Task-related modulation of BOLD signals are typically equated with changes in gamma-band activity; however, relevant empirical evidence comes largely from the neocortex. We examined neurophysiological correlates of the BOLD signal in the hippocampus, where the differing neural architecture might result in a different relationship between the respective signals. We identified a positive relationship between encoding-related changes in BOLD and gamma-band activity in the frontal and parietal cortices. This effect was reversed in the hippocampus, where BOLD and gamma-band effects negatively covaried. These results suggest regional variability in the transfer function between neural activity and the BOLD signal in the hippocampus and neocortex.     

Variability of the relationship between electrophysiology and BOLD-fMRI across cortical regions in humans

The relationship between blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signal and the underlying neural electrical activity in humans is a topic of intense interest to systems neuroscience. This relationship has generally been assumed to be invariant regardless of the brain region and the cognitive task being studied. We critically evaluated these assumptions by comparing the BOLD-fMRI response with local field potential (LFP) measurements during visually cued common noun and verb generation in 11 humans in whom 1210 subdural electrodes were implanted. As expected, power in the mid-gamma band (60-120 Hz) correlated positively (r(2) = 0.16, p < 10(-16)) and power in the beta band (13-30 Hz) correlated negatively (r(2) = 0.09, p < 10(-16)) with the BOLD signal change. Beta and mid-gamma band activity independently explain different components of the observed BOLD signal. Importantly, we found that the location (i.e., lobe) of the recording site modulates the relationship between the electrocorticographic (ECoG) signal and the observed fMRI response (p < 10(-16), F(21,1830) = 52.7), while the type of language task does not. Across all brain regions, ECoG activity in the gamma and beta bands explains 22% of the fMRI response, but if the lobar location is considered, 28% of the variance can be explained. Further evaluation of this relationship at the level of individual gyri provides additional evidence of differences in the BOLD-LFP relationship by cortical locus. This spatial variability in the relationship between the fMRI signal and neural activity carries implications for modeling of the hemodynamic response function, an essential step for interregional fMRI comparisons.     

Neurophysiologic correlates of fMRI in human motor cortex

The neurophysiological underpinnings of functional magnetic resonance imaging (fMRI) are not well understood. To understand the relationship between the fMRI blood oxygen level dependent (BOLD) signal and neurophysiology across large areas of cortex, we compared task related BOLD change during simple finger movement to brain surface electric potentials measured on a similar spatial scale using electrocorticography (ECoG). We found that spectral power increases in high frequencies (65-95 Hz), which have been related to local neuronal activity, colocalized with spatially focal BOLD peaks on primary sensorimotor areas. Independent of high frequencies, decreases in low frequency rhythms (<30 Hz), thought to reflect an aspect of cortical-subcortical interaction, colocalized with weaker BOLD signal increase. A spatial regression analysis showed that there was a direct correlation between the amplitude of the task induced BOLD change on different areas of primary sensorimotor cortex and the amplitude of the high frequency change. Low frequency change explained an additional, different part of the spatial BOLD variance. Together, these spectral power changes explained a significant 36% of the spatial variance in the BOLD signal change (R(2) = 0.36). These results suggest that BOLD signal change is largely induced by two separate neurophysiological mechanisms, one being spatially focal neuronal processing and the other spatially distributed low frequency rhythms.     

FMRI of brain activation in a genetic rat model of absence seizures

PURPOSE: EEG-triggered functional magnetic resonance imaging (fMRI) was used to identify areas of brain activation during spontaneous spike-and-wave discharges (SWDs) in an epileptic rat strain under awake conditions. METHODS: Spontaneous absence seizures from 10 WAG/Rij rats were imaged by using T2*-weighted echo planar imaging at 4.7 Tesla. fMRI of the blood-oxygenation-level-dependent (BOLD) signal was triggered based on EEG recordings during imaging. Images obtained during spontaneous SWDs were compared with baseline images. RESULTS: Significant positive BOLD signal changes were apparent in several areas of the cortex and several important nuclei of the thalamus. In addition, no negative BOLD signal was found in any brain area. CONCLUSIONS: We have shown that EEG-triggered BOLD fMRI can be used to detect cortical and thalamic activation related to the spontaneous SWDs that characterize absence seizures in awake WAG/Rij rats. These results draw an anatomic correlation between areas in which increased BOLD signal is found and those in which SWDs have been recorded. In addition, no negative BOLD signal was found to be associated with these spontaneous SWDs. We also demonstrated the technical feasibility of using EEG-triggered fMRI in a genetic rat model of absence seizure.     

Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients: anomalies in the default network

Spontaneous low-frequency fluctuations in the blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (MRI) signal have been shown to reflect neural synchrony between brain regions. A "default network" of spontaneous low-frequency fluctuations has been described in healthy volunteers during stimulus-independent thought. Negatively correlated with this network are regions activated during attention-demanding tasks. Both these networks involve brain regions and functions that have been linked with schizophrenia in previous research. The present study examined spontaneous slow fluctuations in the BOLD signal at rest, as measured by correlation with low-frequency oscillations in the posterior cingulate, in 17 schizophrenic patients, and 17 comparable healthy volunteers. Healthy volunteers demonstrated correlation between spontaneous low-frequency fluctuations of the BOLD signal in the posterior cingulate and fluctuations in the lateral parietal, medial prefrontal, and cerebellar regions, similar to previous reports. Schizophrenic patients had significantly less correlation between spontaneous slow activity in the posterior cingulate and that in the lateral parietal, medial prefrontal, and cerebellar regions. Connectivity of the posterior cingulate was found to vary with both positive and negative symptoms in schizophrenic patients. Because these data suggest significant abnormalities in resting-state neural networks in schizophrenia, further investigations of spontaneous slow fluctuations of the BOLD signal seem warranted in this population.     

Search for fMRI BOLD signals in networks of spiking neurons

In a recent experiment, functional magnetic resonance imaging blood oxygen level-dependent (fMRI BOLD) signals were compared in different cortical areas (primary-visual and associative), when subjects were required covertly to name images in two protocols: sequences of images, with and without intervening delays. The amplitude of the BOLD signal in protocols with delay was found to be closer to that without delays in associative areas than in primary areas. The present study provides an exploratory proposal for the identification of the neural activity substrate of the BOLD signal in quasi-realistic networks of spiking neurons, in networks sustaining selective delay activity (associative) and in networks responsive to stimuli, but whose unique stationary state is one of spontaneous activity (primary). A variety of observables are 'recorded' in the network simulations, applying the experimental stimulation protocol. The ratios of the candidate BOLD signals, in the two protocols, are compared in networks with and without delay activity. There are several options for recovering the experimental result in the model networks. One common conclusion is that the distinguishing factor is the presence of delay activity. The effect of NMDAr is marginal. The ultimate quantitative agreement with the experiment results depends on a distinction of the baseline signal level from its value in delay-period spontaneous activity. This may be attributable to the subjects' attention. Modifying the baseline results in a quantitative agreement for the ratios, and provided a definite choice of the candidate signals. The proposed framework produces predictions for the BOLD signal in fMRI experiments, upon modification of the protocol presentation rate and the form of the response function.     

Evidence that neurovascular coupling underlying the BOLD effect increases with age during childhood

Functional MRI using blood–oxygen‐level‐dependent (BOLD) imaging has provided unprecedented insights into the maturation of the human brain. Task‐based fMRI studies have shown BOLD signal increases with age during development (ages 5–18) for many cognitive domains such as language and executive function, while functional connectivity (resting‐state) fMRI studies investigating regionally synchronous BOLD fluctuations have revealed a developing functional organization of the brain from a local into a more distributed architecture. However, interpretation of these results is confounded by the fact that the BOLD signal is directly related to blood oxygenation driven by changes in blood flow and only indirectly related to neuronal activity, and may thus be affected by changing neuronal–vascular coupling. BOLD signal and cerebral blood flow (CBF) were measured simultaneously in a cohort of 113 typically developing awake participants ages 3–18 performing a narrative comprehension task. Using a novel voxelwise wild bootstrap analysis technique, an increased ratio of BOLD signal to relative CBF signal change with age (indicative of increased neuronal–vascular coupling) was seen in the middle temporal gyri and the left inferior frontal gyrus. Additionally, evidence of decreased relative oxygen metabolism (indicative of decreased neuronal activity) with age was found in the same regions. These findings raise concern that results of developmental BOLD studies cannot be unambiguously attributed to neuronal activity. Astrocytes and astrocytic processes may significantly affect the maturing functional architecture of the brain, consistent with recent research demonstrating a key role for astrocytes in mediating increased CBF following neuronal activity and for astrocyte processes in modulating synaptic connectivity. Hum Brain Mapp, 36:1–15, 2015. © 2014 Wiley Periodicals, Inc .