Mapping and correction of vascular hemodynamic latency in the BOLD signal

Correlation and causality metrics can be applied to blood-oxygen level-dependent (BOLD) signal time series in order to infer neural synchrony and directions of information flow from fMRI data. However, the BOLD signal reflects both the underlying neural activity and the vascular response, the latter of which is governed by local vasomotor physiology. The presence of potential vascular latency differences thus poses a confound in the detection of neural synchrony as well as inferences about the causality of neural processes. In the present study, we investigate the use of a breath holding (BH) task for characterizing and correcting for voxel-wise neurovascular latency differences across the whole brain. We demonstrate that BH yields reliable measurements of relative timing differences between voxels, and further show that a BH-derived latency correction can impact both functional connectivity maps of the resting-state default-mode network and activation maps of an event-related working memory (WM) task.     

Improving human brain mapping via joint inversion of brain electrodynamics and the BOLD signal

We present several methods to improve the resolution of human brain mapping by combining information obtained from surface electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) of the same participants performing the same task in separate imaging sessions. As an initial step in our methods we used independent component analysis (ICA) to obtain task-related sources for both EEG and fMRI. We then used that information in an integrated cost function that attempts to match both data sources and trades goodness of fit in one regime for another. We compared the performance and drawbacks of each method in localizing sources for a dual visual evoked response experiment, and we contrasted the results of adding fMRI information to simple EEG-only inversion methods. We found that adding fMRI information in a variety of ways gives superior results to classical minimum norm source estimation. Our findings lead us to favor a method which attempts to match EEG scalp dynamics along with voxel power obtained from ICA-processed blood oxygenation level dependent (BOLD) data; this method of joint inversion enables us to treat the two data sources as symmetrically as possible.     

Impaired hemodynamic response in the ischemic brain assessed with BOLD fMRI

The study aims to investigate the effect of cerebral ischemia or hypoperfusion in the evaluation of neural activity with blood-oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI), and to examine whether the severity of the compromised hemodynamic status in patients with major cerebral artery diseases could, conversely, be assessed with the use of neural activity as endogenous vasodilator. 28 neurological impairment-free patients with anterior-circulation-territory ischemia performed a bimanual hand-grasping task. Magnitude and temporal shift of evoked BOLD response, baseline cerebral blood flow (CBF) and its increment, and the severity of hemodynamic impairment stratified by blood flow pattern were evaluated. For fMRI data, both conventional analysis with a canonical HRF and an HRF-model-free analysis were performed. The severity of hemodynamic impairment was significantly correlated (p<0.0001) with baseline CBF, CBF increment, and magnitude and delay of BOLD response. BOLD response delay was also significantly correlated (p<0.0001) with baseline CBF, CBF increment, and response magnitude. In 10 out of 45 ischemic motor cortices, conventional analysis completely failed to detect areas of activation that were demonstrated by HRF-model-free analysis. These data suggest that delay and reduced magnitude of BOLD response can be an indicator of the severity of compromised hemodynamic status, and that reduced regional baseline CBF and its increment underlie impaired BOLD response, which necessitates an alternative approach to conventional analysis with any single HRF.     

Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses

Estimates of hemodynamic response functions (HRF) are often integral parts of event-related fMRI analyses. Although HRFs vary across individuals and brain regions, few studies have investigated how variations affect the results of statistical analyses using the general linear model (GLM). In this study, we empirically estimated HRFs from primary motor and visual cortices and frontal and supplementary eye fields (SEF) in 20 subjects. We observed more variability across subjects than regions and correlated variation of time-to-peak values across several pairs of regions. Simulations examined the effects of observed variability on statistical results and ways different experimental designs and statistical models can limit these effects. Widely spaced and rapid event-related experimental designs with two sampling rates were tested. Statistical models compared an empirically derived HRF to a canonical HRF and included the first derivative of the HRF in the GLM. Small differences between the estimated and true HRFs did not cause false negatives, but larger differences within an observed range of variation, such as a 2.5-s time-to-onset misestimate, led to false negatives. Although small errors minimally affected detection of activity, time-to-onset misestimates as small as 1 s influenced model parameter estimation and therefore random effects analyses across subjects. Experiment and analysis design methods such as decreasing the sampling rate or including the HRF's temporal derivative in the GLM improved results, but did not eliminate errors caused by HRF misestimates. These results highlight the benefits of determining the best possible HRF estimate and potential negative consequences of assuming HRF consistency across subjects or brain regions.     

Fractal analysis of spontaneous fluctuations of the BOLD signal in rat brain

Analysis of task-evoked fMRI data ignores low frequency fluctuations (LFF) of the resting-state the BOLD signal, yet LFF of the spontaneous BOLD signal is crucial for analysis of resting-state connectivity maps. We characterized the LFF of resting-state BOLD signal at 11.7T in α-chloralose and domitor anesthetized rat brain and modeled the spontaneous signal as a scale-free (i.e., fractal) distribution of amplitude power (|A|2) across a frequency range (f) compatible with an |A(f)|2 ∝ 1/f(β) model where β is the scaling exponent (or spectral index). We compared β values from somatosensory forelimb area (S1FL), cingulate cortex (CG), and caudate putamen (CPu). With α-chloralose, S1FL and CG β values dropped from ~0.7 at in vivo to ~0.1 at post mortem (p<0.0002), whereas CPu β values dropped from ~0.3 at in vivo to ~0.1 at post mortem (p<0.002). With domitor, cortical (S1FL, CG) β values were slightly higher than with α-chloralose, while subcortical (CPu) β values were similar with α-chloralose. Although cortical and subcortical β values with both anesthetics were significantly different in vivo (p<0.002), at post mortem β values in these regions were not significantly different and approached zero (i.e., range of -0.1 to 0.2). Since a water phantom devoid of susceptibility gradients had a β value of zero (i.e., random), we conclude that deoxyhemoglobin present in voxels post-sacrifice still impacts tissue water diffusion. These results suggest that in the anesthetized rat brain the LFF of BOLD signal at 11.7T follow a general 1/f(β) model of fractality where β is a variable responding to physiology. We describe typical experimental pitfalls which may elude detection of fractality in the resting-state BOLD signal.     

Spatio-temporal characteristics of low-frequency BOLD signal fluctuations in isoflurane-anesthetized rat brain

We studied the spatio-temporal characteristics of the resting state low-frequency fluctuations in fMRI-BOLD signal in isoflurane-anesthetized rats. fMRI-BOLD measurements at 9.4 T 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 to 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.     

Influences of negative BOLD responses on positive BOLD responses

Understanding possible interactions between blood oxygenation level-dependent (BOLD) responses is critical for model-based analyses and the interpretation of experiments that deal with stimuli presented close together in time. Such interactions are well documented in the case of successive positive BOLD responses. However, the influence that a stimulus-induced, negative BOLD response exerts on a subsequent positive BOLD response has yet to be investigated and is the focus of the current study. We performed functional magnetic resonance imaging on 10 healthy subjects during bilateral electrical median nerve stimulation using five different time intervals between left- and right-sided stimuli. We found an acute interruption of the ongoing negative BOLD response at the onset of the positive BOLD response. Different parameters characterizing the positive BOLD response were estimated. There was no impact of the preceding negative BOLD response on the parameters describing the subsequent positive BOLD response. These findings indicate that the underlying mechanisms for negative and positive BOLD responses do not engage parallel processes. We hypothesize that the negative BOLD response is caused by a decreased release of the same vasodilatative agents that evoke the positive BOLD response. Additionally, our results demonstrate that there is no need to adjust the model of a positive BOLD response due to a preceding negative BOLD response in the same brain area.     

Statistical properties of BOLD magnetic resonance activity in the human brain

We investigated the random variability of BOLD (blood oxygen level dependent) activation during rest, or null-hypothesis, conditions in which the observers were neither receiving controlled sensory stimuli nor performing cognitive tasks. The data indicate that the distributions for the BOLD variation across space are skewed, with non-Gaussian tails, while the distributions for the temporal variation within individual voxels are predominantly Gaussian. The proportion of voxels that show non-Gaussian properties is highly correlated with the magnitude of head movement of the observers. In all observers, the white matter showed less variability than the gray matter. The distributions for the spatial and the temporal variations are robust across observers despite differences in the data acquisition methods (EPI vs. spiral) and magnetic field strength (1.5 vs. 3 T). In most cases, the non-Gaussian tails of the spatial distribution can be eliminated by normalizing the amplitude in each voxel to its standard deviation before cumulating across voxels. We therefore recommend such a normalization procedure before any data manipulations are performed on fMRI data.     

Nonlinear estimation of the BOLD signal

Signal variations in functional Magnetic Resonance Imaging experiments essentially reflect the vascular system response to increased demand for oxygen caused by neuronal activity, termed the blood oxygenation level dependent (BOLD) effect. The most comprehensive model to date of the BOLD signal is formulated as a mixed continuous-discrete-time system of nonlinear stochastic differential equations. Previous approaches to the analysis of this system have been based on linearised approximations of the dynamics, which are limited in their ability to capture the inherent nonlinearities in the physiological system. In this paper we present a nonlinear filtering method for simultaneous estimation of the hidden physiological states and the system parameters, based on an iterative coordinate descent framework. State estimates of the cerebral blood flow, cerebral blood volume and deoxyhaemoglobin content are determined using a particle filter, demonstrated via simulation to be accurate, robust and efficient in comparison to linearisation-based techniques. The adaptive state and parameter estimation algorithm generates physiologically reasonable parameter estimates for experimental fMRI data. It is anticipated that signal processing techniques for modelling and estimation will become increasingly important in fMRI analyses as limitations of linear and linearised modelling are reached.     

Nonlinear coupling between evoked rCBF and BOLD signals: a simulation study of hemodynamic responses

The aim of this work was to investigate the dependence of BOLD responses on different patterns of stimulus input/neuronal changes. In an earlier report, we described an input-state-output model that combined (i) the Balloon/Windkessel model of nonlinear coupling between rCBF and BOLD signals, and (ii) a linear model of how regional flow changes with synaptic activity. In the present investigation, the input-state-output model was used to explore the dependence of simulated PET (rCBF) and fMRI (BOLD) signals on various parameters pertaining to experimental design. Biophysical simulations were used to estimate rCBF and BOLD responses as functions of (a) a prior stimulus, (b) epoch length (for a fixed SOA), (c) SOA (for a fixed number of events), and (d) stimulus amplitude. We also addressed the notion that a single neuronal response may differ, in terms of the relative contributions of early and late neural components, and investigated the effect of (e) the relative size of the late or "endogenous" neural component. We were interested in the estimated average rCBF and BOLD responses per stimulus or event, not in the statistical efficiency with which these responses are detected. The BOLD response was underestimated relative to rCBF with a preceding stimulus, increasing epoch length, and increasing SOA. Furthermore, the BOLD response showed some highly nonlinear behaviour when varying stimulus amplitude, suggesting some form of hemodynamic "rectification." Finally, the BOLD response was underestimated in the context of large late neuronal components. The difference between rCBF and BOLD is attributed to the nonlinear transduction of rCBF to BOLD signal. Our simulations support the idea that varying parameters that specify the experimental design may have differential effects in PET and fMRI. Moreover, they show that fMRI can be asymmetric in its ability to detect deactivations relative to activations when an absolute baseline is stipulated. Finally, our simulations suggest that relative insensitivity to BOLD signal in specific regions, such as the temporal lobe, may be partly explained by higher cognitive functions eliciting a relatively large late endogenous neuronal component.     

A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans

In this study, we have preformed simultaneous near-infrared spectroscopy (NIRS) along with BOLD (blood oxygen level dependent) and ASL (arterial spin labeling)-based fMRI during an event-related motor activity in human subjects in order to compare the temporal dynamics of the hemodynamic responses recorded in each method. These measurements have allowed us to examine the validity of the biophysical models underlying each modality and, as a result, gain greater insight into the hemodynamic responses to neuronal activation. Although prior studies have examined the relationships between these two methodologies through similar experiments, they have produced conflicting results in the literature for a variety of reasons. Here, by employing a short-duration, event-related motor task, we have been able to emphasize the subtle temporal differences between the hemodynamic parameters with a high contrast-to-noise ratio. As a result of this improved experimental design, we are able to report that the fMRI measured BOLD response is more correlated with the NIRS measure of deoxy-hemoglobin (R = 0.98; P < 10(-20)) than with oxy-hemoglobin (R = 0.71), or total hemoglobin (R = 0.53). This result was predicted from the theoretical grounds of the BOLD response and is in agreement with several previous works [Toronov, V.A.W., Choi, J.H., Wolf, M., Michalos, A., Gratton, E., Hueber, D., 2001. "Investigation of human brain hemodynamics by simultaneous near-infrared spectroscopy and functional magnetic resonance imaging." Med. Phys. 28 (4) 521-527.; MacIntosh, B.J., Klassen, L.M., Menon, R.S., 2003. "Transient hemodynamics during a breath hold challenge in a two part functional imaging study with simultaneous near-infrared spectroscopy in adult humans". NeuroImage 20 1246-1252.; Toronov, V.A.W., Walker, S., Gupta, R., Choi, J.H., Gratton, E., Hueber, D., Webb, A., 2003. "The roles of changes in deoxyhemoglobin concentration and regional cerebral blood volume in the fMRI BOLD signal" Neuroimage 19 (4) 1521-1531]. These data have also allowed us to examine more detailed measurement models of the fMRI signal and comment on the roles of the oxygen saturation and blood volume contributions to the BOLD response. In addition, we found high correlation between the NIRS measured total hemoglobin and ASL measured cerebral blood flow (R = 0.91; P < 10(-10)) and oxy-hemoglobin with flow (R = 0.83; P < 10(-05)) as predicted by the biophysical models. Finally, we note a significant amount of cross-modality, correlated, inter-subject variability in amplitude change and time-to-peak of the hemodynamic response. The observed co-variance in these parameters between subjects is in agreement with hemodynamic models and provides further support that fMRI and NIRS have similar vascular sensitivity.     

BOLD MRI responses to repetitive TMS over human dorsal premotor cortex

Functional magnetic resonance imaging (fMRI) studies in humans have hitherto failed to demonstrate activity changes in the direct vicinity of transcranial magnetic stimulation (TMS) that cannot be attributed to re-afferent somatosensory feedback or a spread of excitation. In order to investigate the underlying activity changes at the site of stimulation as well as in remote connected regions, we applied short trains of high-intensity (110% of resting motor threshold) and low-intensity (90% of active motor threshold) repetitive TMS (rTMS; 3 Hz, 10 s duration) over the presumed location of the left dorsal premotor cortex (PMd) during fMRI. Signal increases in the direct vicinity of the stimulated PMd were observed during rTMS at 110% RMT. However, positive BOLD MRI responses were observed with rTMS at both 90% and 110% RMT in connected brain regions such as right PMd, bilateral PMv, supplementary motor area, somatosensory cortex, cingulate motor area, left posterior temporal lobe, cerebellum, and caudate nucleus. Responses were generally smaller during low-intensity rTMS. The results indicate that short trains of TMS can modify local hemodynamics in the absence of overt motor responses. In addition, premotor rTMS cannot only effectively stimulate cortico-cortical but also cortico-subcortical connections even at low stimulation intensities.     

Cortical layer-dependent BOLD and CBV responses measured by spin-echo and gradient-echo fMRI: insights into hemodynamic regulation

Spatial specificity of functional magnetic resonance imaging (fMRI) signals to sub-millimeter functional architecture remains controversial. To investigate this issue, high-resolution fMRI in response to visual stimulus was obtained in isoflurane-anesthetized cats at 9.4 T using conventional gradient-echo (GE) and spin-echo (SE) techniques; blood oxygenation-level dependent (BOLD) and cerebral blood volume (CBV)-weighted data were acquired without and with injection of 10 mg Fe/kg monocrystalline iron oxide nanoparticles (MION), respectively. Studies after MION injection at two SE times show that the T2' contribution to SE fMRI is minimal. GE and SE BOLD changes were spread across the cortical layers. GE and SE CBV-weighted fMRI responses peaked at the middle cortical layer, which has the highest experimentally-determined microvascular volume; full-width at half-maximum was <1.0 mm. Parenchymal sensitivity of GE CBV-weighted fMRI was approximately 3 times higher than that of SE CBV-weighted fMRI and approximately 1.5 times higher than that of BOLD fMRI. It is well known that GE CBV-weighted fMRI detects a volume change in vessels of all sizes, while SE CBV-weighted fMRI is heavily weighted toward microvascular changes. Peak CBV change of 10% at the middle of the cortex in GE measurements was 1.8 times higher than that in SE measurements, indicating that CBV changes occur predominantly for vasculature connecting the intracortical vessels and capillaries. Our data supports the notion of laminar-dependent CBV regulation at a sub-millimeter scale.     

Assessment of brain responses to innocuous and noxious electrical forepaw stimulation in mice using BOLD fMRI

Functional magnetic resonance imaging (fMRI) using the blood oxygen level-dependent (BOLD) contrast was used to study sensory processing in the brain of isoflurane-anesthetized mice. The use of a cryogenic surface coil in a small animal 9.4T system provided the sensitivity required for detection and quantitative analysis of hemodynamic changes caused by neural activity in the mouse brain in response to electrical forepaw stimulation at different amplitudes. A gradient echo-echo planar imaging (GE-EPI) sequence was used to acquire five coronal brain slices of 0.5 mm thickness. BOLD signal changes were observed in primary and secondary somatosensory cortices, the thalamus and the insular cortex, important regions involved in sensory and nociceptive processing. Activation was observed consistently bilateral despite unilateral stimulation of the forepaw. The temporal BOLD profile was segregated into two signal components with different temporal characteristics. The maximum BOLD amplitude of both signal components correlated strongly with the stimulation amplitude. Analysis of the dynamic behavior of the somatosensory ‘fast’ BOLD component revealed a decreasing signal decay rate constant k_off with increasing maximum BOLD amplitude (and stimulation amplitude). This study demonstrates the feasibility of a robust BOLD fMRI protocol to study nociceptive processing in isoflurane-anesthetized mice. The reliability of the method allows for detailed analysis of the temporal BOLD profile and for investigation of somatosensory and noxious signal processing in the brain, which is attractive for characterizing genetically engineered mouse models.     

Where the BOLD signal goes when alpha EEG leaves

Previous studies using simultaneous EEG and fMRI recordings have yielded discrepant results regarding the topography of brain activity in relation to spontaneous power fluctuations in the alpha band of the EEG during eyes-closed rest. Here, we explore several possible explanations for this discrepancy by re-analyzing in detail our previously reported data. Using single subject analyses as a starting point, we found that alpha power decreases are associated with fMRI signal increases that mostly follow two distinct patterns: either 'visual' areas in the occipital lobe or 'attentional' areas in the frontal and parietal lobe. On examination of the EEG spectra corresponding to these two fMRI patterns, we found greater relative theta power in sessions yielding the 'visual' fMRI pattern during alpha desynchronization and greater relative beta power in sessions yielding the 'attentional' fMRI pattern. The few sessions that fell into neither pattern featured the overall lowest theta and highest beta power. We conclude that the pattern of brain activation observed during spontaneous power reduction in the alpha band depends on the general level of brain activity as indexed over a broader spectral range in the EEG. Finally, we relate these findings to the concepts of 'resting state' and 'default mode' and discuss how - as for sleep - EEG-based criteria might be used for staging brain activity during wakefulness.     

Controlled inspiration depth reduces variance in breath-holding-induced BOLD signal

Recent studies have shown that blood oxygen level dependent (BOLD) response amplitude during short periods of breath holding (BH) measured by functional magnetic resonance imaging (fMRI) can be an effective metric for intersubject calibration procedures. However, inconsistency in the depth of inspiration during the BH scan may account for a portion of BOLD variation observed in such scans, and it is likely to reduce the effectiveness of the calibration measurement. While modulation of BOLD signal has been correlated with end-tidal CO2 and other measures of breathing, fluctuations in performance of BH have not been studied in the context of their impact on BOLD signal. Here, we studied the degree to which inspiration depth corresponds to BOLD signal change and tested the effectiveness of a method designed to control inspiration level through visual cues during the BH task paradigm. We observed reliable differences in BOLD signal amplitude corresponding to the depth of inspiration. It was determined that variance in BOLD signal response to BH could be significantly reduced when subjects were given visual feedback during task inspiration periods. The implications of these findings for routine BH studies of BOLD-derived neurovascular response are discussed.     

Magnitude and phase behavior of multiresolution BOLD signal

High spatial resolution fMRI provides a more precise estimate of brain activity than low resolution fMRI. The magnitude and phase parts of the BOLD signals are impacted differently by changes in the scan resolution. In this paper, we report on a numerical simulation to show the impact of spatial resolution upon the complex-valued BOLD signal in terms of magnitude and phase variation. We generate realistic capillary networks in cortex voxels, calculate the BOLD-induced magnetic field disturbance and the complex BOLD signals for the voxel and its subvoxels, and thereby characterize the magnitude and phase behaviors across multiple grid resolutions. Our results show that: 1) at higher spatial resolution there is greater spatial variation in the phase of the BOLD signal as compared to its magnitude; 2) the spatial variation of the phase signal monotonically increases with respect to spatial resolution while for the magnitude the spatial variation may reach a maximum at some resolution level; 3) voxels containing large capillaries have higher phase spatial variation than those with smaller capillaries; 4) the amplitude spatial variation at a resolution level increases with respect to relaxation time whereas the phase variation is generally unaffected.     

Spatio-temporal information analysis of event-related BOLD responses

A new approach for analysis of event-related fMRI (BOLD) signals is proposed. The technique is based on measures from information theory and is used both for spatial localization of task-related activity, as well as for extracting temporal information regarding the task-dependent propagation of activation across different brain regions. This approach enables whole brain visualization of voxels (areas) most involved in coding of a specific task condition, the time at which they are most informative about the condition, as well as their average amplitude at that preferred time. The approach does not require prior assumptions about the shape of the hemodynamic response function (HRF) nor about linear relations between BOLD response and presented stimuli (or task conditions). We show that relative delays between different brain regions can also be computed without prior knowledge of the experimental design, suggesting a general method that could be applied for analysis of differential time delays that occur during natural, uncontrolled conditions. Here we analyze BOLD signals recorded during performance of a motor learning task. We show that, during motor learning, the BOLD response of unimodal motor cortical areas precedes the response in higher-order multimodal association areas, including posterior parietal cortex. Brain areas found to be associated with reduced activity during motor learning, predominantly in prefrontal brain regions, are informative about the task typically at significantly later times.