Evidence of a cerebrovascular postarteriole windkessel with delayed compliance

Hemodynamic nonlinearities affect BOLD fMRI response timing and amplitude

The interpretation of functional magnetic resonance imaging (fMRI) studies based on blood oxygen-level dependent (BOLD) contrast generally relies on the assumption of a linear relationship between evoked neuronal activity and fMRI response. While nonlinearities in this relationship have been suggested by a number of studies, it remains unclear to what extent they relate to the neurovascular response and are therefore inherent to BOLD fMRI. Full characterization of potential vascular nonlinearities is required for accurate inferences about the neuronal system under study. To investigate the extent of vascular nonlinearities, evoked activity was studied in humans with BOLD fMRI (n=28) and magnetoencephalography (MEG) (n=5). Brief (600-800 ms) rapidly repeated (1 Hz) visual stimuli were delivered using a stimulation paradigm that minimized neuronal nonlinearities. Nevertheless, BOLD fMRI experiments showed substantial remaining nonlinearities. The smallest stimulus separation (200-400 ms) resulted in significant response broadening (15-20% amplitude decrease; 10-12% latency increase; 6-14% duration increase) with respect to a linear prediction. The substantial slowing and widening of the response in the presence of preceding stimuli suggest a vascular rather than neuronal origin to the observed nonlinearity. This was confirmed by the MEG data, which showed no significant neuro-electric nonlinear interactions between stimuli as little as 200 ms apart. The presence of substantial vascular nonlinearities has important implications for rapid event-related studies by fMRI and other imaging modalities that infer neuronal activity from hemodynamic parameters.

Increased cerebral blood volume and oxygen consumption in neonatal brain injury

With the increasing interest in treatments for neonatal brain injury, bedside methods for detecting and assessing injury status and evolution are needed. We aimed to determine whether cerebral tissue oxygenation (StO(2)), cerebral blood volume (CBV), and estimates of relative cerebral oxygen consumption (rCMRO(2)) determined by bedside frequency-domain near-infrared spectroscopy (FD-NIRS) have the potential to distinguish neonates with brain injury from those with non-brain issues and healthy controls. We recruited 43 neonates < or =15 days old and >33 weeks gestational age (GA): 14 with imaging evidence of brain injury, 29 without suspicion of brain injury (4 unstable, 6 stable, and 19 healthy). A multivariate analysis of variance with Newman-Keuls post hoc comparisons confirmed group similarity for GA and age at measurement. StO(2) was significantly higher in brain injured compared with unstable neonates, but not statistically different from stable or healthy neonates. Brain-injured neonates were distinguished from all others by significant increases in CBV and rCMRO(2). In conclusion, although NIRS measures of StO(2) alone may be insensitive to evolving brain injury, increased CBV and rCMRO(2) seem to be useful for detecting neonatal brain injury and suggest increased neuronal activity and metabolism occurs acutely in evolving brain injury.

Vascular graph model to simulate the cerebral blood flow in realistic vascular networks

At its most fundamental level, cerebral blood flow (CBF) may be modeled as fluid flow driven through a network of resistors by pressure gradients. The composition of the blood as well as the cross-sectional area and length of a vessel are the major determinants of its resistance to flow. Here, we introduce a vascular graph modeling framework based on these principles that can compute blood pressure, flow and scalar transport in realistic vascular networks. By embedding the network in a computational grid representative of brain tissue, the interaction between the two compartments can be captured in a truly three-dimensional manner and may be applied, among others, to simulate oxygen extraction from the vessels. Moreover, we have devised an upscaling algorithm that significantly reduces the computational expense and eliminates the need for detailed knowledge on the topology of the capillary bed. The vascular graph framework has been applied to investigate the effect of local vascular dilation and occlusion on the flow in the surrounding network.

A cerebrovascular response model for functional neuroimaging including dynamic cerebral autoregulation

Functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) can be used to isolate an evoked response to a stimulus from significant background physiological fluctuations. Data analysis approaches typically use averaging or linear regression to remove this physiological baseline with varying degrees of success. Biophysical model-based analysis of the functional hemodynamic response has also been advanced previously with the Balloon and Windkessel models. In the present work, a biophysical model of systemic and cerebral circulation and gas exchange is applied to resting state NIRS neuroimaging data from 10 human subjects. The model further includes dynamic cerebral autoregulation, which modulates the cerebral arteriole compliance to control cerebral blood flow. This biophysical model allows for prediction, from noninvasive blood pressure measurements, of the background hemodynamic fluctuations in the systemic and cerebral circulations. Significantly higher correlations with the NIRS data were found using the biophysical model predictions compared to blood pressure regression and compared to transfer function analysis (multifactor ANOVA, p<0.0001). This finding supports the further development and use of biophysical models for removing baseline activity in functional neuroimaging analysis. Future extensions of this work could model changes in cerebrovascular physiology that occur during development, aging, and disease.

Human cerebral circulation: positron emission tomography studies

We reviewed the literature on human cerebral circulation and oxygen metabolism, as measured by positron emission tomography (PET), with respect to normal values and of regulation of cerebral circulation. A multicenter study in Japan showed that between-center variations in cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2) values were not considerably larger than the corresponding within-center variations. Overall mean +/- SD values in cerebral cortical regions of normal human subjects were as follows: CBF = 44.4 +/- 6.5 ml/100 ml/min; CBV = 3.8 +/- 0.7 ml/100 ml; OEF = 0.44 +/- 0.06; CMRO2 = 3.3 +/- 0.5 ml/100 ml/min (11 PET centers, 70 subjects). Intrinsic regulation of cerebral circulation involves several factors. Autoregulation maintains CBF in response to changes in cerebral perfusion pressure; chemical factors such as PaCO2 affect cerebral vascular tone and alter CBF; changes in neural activity cause changes in cerebral energy metabolism and CBF; neurogenic control of CBF occurs by sympathetic innervation. Regional differences in vascular response to changes in PaCO2 have been reported, indicating regional differences in cerebral vascular tone. Relations between CBF and CBV during changes in PaCO2 and during changes in neural activity were in good agreement with Poiseuille's law. The mechanisms of vascular response to neural activation and deactivation were independent on those of responses to PaCO2 changes. CBV in a brain region is the sum of three components: arterial, capillary and venous blood volumes. It has been reported that the arterial blood volume fraction is approximately 30% in humans and that changes in human CBV during changes in PaCO2 are caused by changes in arterial blood volume without changes in venous blood volume. These findings should be considered in future studies of the pathophysiology of cerebrovascular diseases.

Sensitivity of neural-hemodynamic coupling to alterations in cerebral blood flow during hypercapnia

The relationship between measurements of cerebral blood oxygenation and neuronal activity is highly complex and depends on both neurovascular and neurometabolic biological coupling. While measurements of blood oxygenation changes via optical and MRI techniques have been developed to map functional brain activity, there is evidence that the specific characteristics of these signals are sensitive to the underlying vascular physiology and structure of the brain. Since baseline blood flow and oxygen saturation may vary between sessions and across subjects, functional blood oxygenation changes may be a less reliable indicator of brain activity in comparison to blood flow and metabolic changes. In this work, we use a biomechanical model to examine the relationships between neural, vascular, metabolic, and hemodynamic responses to parametric whisker stimulation under both normal and hypercapnic conditions in a rat model. We find that the relationship between neural activity and oxy- and deoxyhemoglobin changes is sensitive to hypercapnia-induced changes in baseline cerebral blood flow. In contrast, the underlying relationships between evoked neural activity, blood flow, and model-estimated oxygen metabolism changes are unchanged by the hypercapnic challenge. We conclude that evoked changes in blood flow and cerebral oxygen metabolism are more closely associated with underlying evoked neuronal responses.

A model for transient oxygen delivery in cerebral cortex

Popular hemodynamic brain imaging methods, such as blood oxygen-level dependent functional magnetic resonance imaging (BOLD fMRI), would benefit from a detailed understanding of the mechanisms by which oxygen is delivered to the cortex in response to brief periods of neural activity. Tissue oxygen responses in visual cortex following brief visual stimulation exhibit rich dynamics, including an early decrease in oxygen concentration, a subsequent large increase in concentration, and substantial late-time oscillations (“ringing”). We introduce a model that explains the full time-course of these observations made by Thompson et al. (2003). The model treats oxygen transport with a set of differential equations that include a combination of flow and diffusion in a three-compartment (intravascular, extravascular, and intracellular) system. Blood flow in this system is modeled using the impulse response of a lumped linear system that includes an inertive element; this provides a simple biophysical mechanism for the ringing. The model system is solved numerically to produce excellent fits to measurements of tissue oxygen. The results give insight into the dynamics of cerebral oxygen transfer, and can serve as the starting point to understand BOLD fMRI measurements.

Estimating cerebral oxygen metabolism from fMRI with a dynamic multicompartment Windkessel model

Stimulus evoked changes in cerebral blood flow, volume, and oxygenation arise from responses to underlying neuronally mediated changes in vascular tone and cerebral oxygen metabolism. There is increasing evidence that the magnitude and temporal characteristics of these evoked hemodynamic changes are additionally influenced by the local properties of the vasculature including the levels of baseline cerebral blood flow, volume, and blood oxygenation. In this work, we utilize a physiologically motivated vascular model to describe the temporal characteristics of evoked hemodynamic responses and their expected relationships to the structural and biomechanical properties of the underlying vasculature. We use this model in a temporal curve-fitting analysis of the high-temporal resolution functional MRI data to estimate the underlying cerebral vascular and metabolic responses in the brain. We present evidence for the feasibility of our model-based analysis to estimate transient changes in the cerebral metabolic rate of oxygen (CMRO(2)) in the human motor cortex from combined pulsed arterial spin labeling (ASL) and blood oxygen level dependent (BOLD) MRI. We examine both the numerical characteristics of this model and present experimental evidence to support this model by examining concurrently measured ASL, BOLD, and near-infrared spectroscopy to validate the calculated changes in underlying CMRO(2).

The importance of latency in the focality of perfusion and oxygenation changes associated with triggered afterdischarges in human cortex

The spatiotemporal dynamics of neurovascular coupling during epilepsy are not well understood, and there are little data from studies of the human brain. We investigated changes in total hemoglobin (Hbt) and hemoglobin oxygenation in patients undergoing epilepsy surgery with intraoperative intrinsic optical spectroscopy (IOS) during triggered afterdischarges (ADs). We found an early (approximately 0.5 secs) focal dip in hemoglobin oxygenation, arising precisely in the stimulated gyrus that lasted for 11.5+/-10.0 secs, approximately the length of the AD (10.4+/-4.4 secs). A later oxygen overshoot and increase in blood volume occurred in the adjacent surrounding gyri. After a significant delay (approximately 20 to 30 secs), the overshoot and blood volume signal became extremely focal to the area of the onset of the AD. A smaller very late undershoot, the last phase of the 'triphasic' response, was also identified, although localization was inconsistent. In this study, we show that a 'late focal overshoot' and late Hbt signal may be extremely useful, in addition to the early dip, for the localization of seizure onset. It is likely that a separate mechanism underlies the persistent focal increase in cerebral blood volume after a long-duration cortical stimulation, compared with the nonspecific mechanism that causes the initial increase in cerebral blood flow.

Simultaneous imaging of cerebral partial pressure of oxygen and blood flow during functional activation and cortical spreading depression

We developed a novel imaging technique that provides real-time two-dimensional maps of the absolute partial pressure of oxygen and relative cerebral blood flow in rats by combining phosphorescence lifetime imaging with laser speckle contrast imaging. Direct measurement of blood oxygenation based on phosphorescence lifetime is not significantly affected by changes in the optical parameters of the tissue during the experiment. The potential of the system as a novel tool for quantitative analysis of the dynamic delivery of oxygen to support brain metabolism was demonstrated in rats by imaging cortical responses to forepaw stimulation and the propagation of cortical spreading depression waves. This new instrument will enable further study of neurovascular coupling in normal and diseased brain.

Effects of aging on cerebral blood flow, oxygen metabolism, and blood oxygenation level dependent responses to visual stimulation

Calibrated functional magnetic resonance imaging (fMRI) provides a noninvasive technique to assess functional metabolic changes associated with normal aging. We simultaneously measured both the magnitude of the blood oxygenation level dependent (BOLD) and cerebral blood flow (CBF) responses in the visual cortex for separate conditions of mild hypercapnia (5% CO(2)) and a simple checkerboard stimulus in healthy younger (n = 10, mean: 28-years-old) and older (n = 10, mean: 53-years-old) adults. From these data we derived baseline CBF, the BOLD scaling parameter M, the fractional change in the cerebral metabolic rate of oxygen consumption (CMRO(2)) with activation, and the coupling ratio n of the fractional changes in CBF and CMRO(2). For the functional activation paradigm, the magnitude of the BOLD response was significantly lower for the older group (0.57 +/- 0.07%) compared to the younger group (0.95 +/- 0.14%), despite the finding that the fractional CBF and CMRO(2) changes were similar for both groups. The weaker BOLD response for the older group was due to a reduction in the parameter M, which was significantly lower for older (4.6 +/- 0.4%) than younger subjects (6.5 +/- 0.8%), most likely reflecting a reduction in baseline CBF for older (41.7 +/- 4.8 mL/100 mL/min) compared to younger (59.6 +/- 9.1 mL/100 mL/min) subjects. In addition to these primary responses, for both groups the BOLD response exhibited a post-stimulus undershoot with no significant difference in this magnitude. However, the post-undershoot period of the CBF response was significantly greater for older compared to younger subjects. We conclude that when comparing two populations, the BOLD response can provide misleading reflections of underlying physiological changes. A calibrated approach provides a more quantitative reflection of underlying metabolic changes than the BOLD response alone.

Origins of the BOLD post-stimulus undershoot

The interpretation of the blood-oxygenation level-dependent (BOLD) post-stimulus undershoot has been a topic of considerable interest, as the mechanisms behind this prominent BOLD transient may provide valuable clues on the neurovascular response process and energy supply routes of the brain. Biomechanical theories explain the origin of the BOLD undershoot through the passive ballooning of post-capillary vessels which leads to an increase in venous blood volume (CBV(v), comprising deoxygenated blood in capillary, venular and arteriolar compartments), resulting in susceptibility-induced signal decrease. While there has been substantial evidence supporting a role for venous ballooning, there have also been reports arguing for a prolonged post-stimulus elevation in cerebral oxygenation consumption (CMRo(2)) as the primary cause. Furthermore, a contribution of post-stimulus cerebral blood flow (CBF) undershoots has also been demonstrated. To clarify the role of the venous compartment in causing the BOLD undershoot, we performed in vivo fMRI measurements of the transient DeltaCBV(v), DeltaCBF and DeltaBOLD responses in healthy humans. We observed a slow post-stimulus return to baseline in venous CBV which supports the existence of a passive "balloon" effect, implying that previous observations of a quicker recovery of the total CBV response may be dominated by arterial CBV change. Our findings also support a significant contribution from the CBF undershoots, which, combined with a slow venous CBV response, would account for much of the BOLD undershoot.

1/f noise in diffuse optical imaging and wavelet-based response estimation

In diffuse optical imaging (DOI) data analysis, the functional response is contaminated with physiological noise as in functional magnetic resonance imaging (fMRI). In this work we extend a previously proposed method for fMRI to estimate the parameters of a linear model of DOI time series. The regression is performed in the wavelet domain to infer drift coefficients at different scales and to estimate the strength of the hemodynamic response function (HRF). This multiresolution approach benefits from the whitening property of the discrete wavelet transform (DWT), which approximately decorrelates long-memory noise processes. We also show that a more accurate estimation is obtained by removing some regressors correlating with the protocol. Moreover, we observe that this improvement is related to a quantitative measure of 1/f noise. The performances of the method are first evaluated against a standard spline-cosine drift approach with simulated HRF and real background physiology. Lastly, the technique is applied to experimental event-related data acquired by near-infrared spectroscopy (NIRS).

Object representations in the temporal cortex of monkeys and humans as revealed by functional magnetic resonance imaging

Increasing evidence suggests that the neural processes associated with identifying everyday stimuli include the classification of those stimuli into a limited number of semantic categories. How the neural representations of these stimuli are organized in the temporal lobe remains under debate. Here we used functional magnetic resonance imaging (fMRI) to identify correlates for three current hypotheses concerning object representations in the inferior temporal (IT) cortex of monkeys and humans: representations based on animacy, semantic categories, or visual features. Subjects were presented with blocked images of faces, body parts (animate stimuli), objects, and places (inanimate stimuli), and multiple overlapping contrasts were used to identify the voxels most selective for each category. Stimulus representations appeared to segregate according to semantic relationships. Discrete regions selective for animate and inanimate stimuli were found in both species. These regions could be further subdivided into regions selective for individual categories. Notably, face-selective regions were contiguous with body-part-selective regions, and object-selective regions were contiguous with place-selective regions. When category-selective regions in monkeys were tested with blocks of single exemplars, individual voxels showed preferences for visually dissimilar exemplars from the same category and voxels with similar preferences tended to cluster together. Our results provide some novel observations with respect to how stimulus representations are organized in IT cortex. In addition, they further support the idea that representations of complex stimuli in IT cortex are organized into multiple hierarchical tiers, encompassing both semantic and physical properties.

Effect of inflow of fresh blood on vascular-space-occupancy (VASO) contrast

In vascular-space-occupancy (VASO)-MRI, cerebral blood volume (CBV)-weighted contrast is generated by applying a nonselective inversion pulse followed by imaging when blood water magnetization is zero. An uncertainty in VASO relates to the completeness of blood water nulling. Specifically, radio frequency (RF) coils produce a finite inversion volume, rendering the possibility of fresh, non-nulled blood. Here, VASO-functional MRI (fMRI) was performed for varying inversion volume and TR using body coil RF transmission. For thin inversion volume thickness (delta(tot) < 10 mm), VASO signal changes were positive (DeltaS/S = 2.1-2.6%). Signal changes were negative and varied in magnitude for intermediate inversion volumes (delta(tot) = 100-300 mm), yet did not differ significantly (P > 0.05) for delta(tot) > 300 mm. These data suggest that blood water is in steady state for delta(tot) > 300 mm. In this appropriate range, long-TR VASO data converged to a less negative value (DeltaS/S = -1.4% +/- 0.2%) than short-TR data (DeltaS/S = -2.2% +/- 0.2%), implying that cerebral blood flow or transit-state effects may influence VASO contrast at short TR.

Model estimation of cerebral hemodynamics between blood flow and volume changes: a data-based modeling approach

It is well known that there is a dynamic relationship between cerebral blood flow (CBF) and cerebral blood volume (CBV). With increasing applications of functional MRI, where the blood oxygen-level-dependent signals are recorded, the understanding and accurate modeling of the hemodynamic relationship between CBF and CBV becomes increasingly important. This study presents an empirical and data-based modeling framework for model identification from CBF and CBV experimental data. It is shown that the relationship between the changes in CBF and CBV can be described using a parsimonious autoregressive with exogenous input model structure. It is observed that neither the ordinary least-squares (LS) method nor the classical total least-squares (TLS) method can produce accurate estimates from the original noisy CBF and CBV data. A regularized total least-squares (RTLS) method is thus introduced and extended to solve such an error-in-the-variables problem. Quantitative results show that the RTLS method works very well on the noisy CBF and CBV data. Finally, a combination of RTLS with a filtering method can lead to a parsimonious but very effective model that can characterize the relationship between the changes in CBF and CBV.

Exploring neuro-vascular and neuro-metabolic coupling in rat somatosensory cortex

The existence of a coupling between changes in neuronal activity, cerebral blood flow and blood oxygenation is well known. The explicit relationship between these systems, however, is complex and remains a subject of intense research. Here, we use direct electrophysiological recordings to predict blood flow and oxygenation changes measured with optical methods during parametric stimulation applied to the somatosensory cortex in rat brain. Using a multimodal model of the cerebral functional unit, we estimate a neuro-vascular and a neuro-metabolic transfer function relating the experimentally measured neural responses with the inputs to a vascular model predicting hemodynamic and blood oxygenation changes. We show that our model can accurately predict experimentally measured parametric hemodynamic evoked responses by using a single linear transfer function relationship with a reduced number of state parameters to relate the level of neural activity to evoked cerebral blood flow and oxygen metabolism changes. At the same time, we characterize the metabolic and vascular neural response functions and interpret their physiological significance.

Hemodynamic changes after visual stimulation and breath holding provide evidence for an uncoupling of cerebral blood flow and volume from oxygen metabolism

Functional neuroimaging is most commonly performed using the blood-oxygenation-level-dependent (BOLD) approach, which is sensitive to changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and the cerebral metabolic rate of oxygen (CMRO(2)). However, the precise mechanism by which neuronal activity elicits a hemodynamic response remains controversial. Here, visual stimulation (14 secs flashing checkerboard) and breath-hold (4 secs exhale+14 secs breath hold) experiments were performed in alternating sequence on healthy volunteers using BOLD, CBV-weighted, and CBF-weighted fMRI. After visual stimulation, the BOLD signal persisted for 33+/-5 secs (n=9) and was biphasic with a negative component (undershoot), whereas CBV and CBF returned to baseline without an undershoot at 20+/-5 and 20+/-3 secs, respectively. After breath hold, the BOLD signal returned to baseline (23+/-7 secs) at the same time (P>0.05) as CBV (21+/-6 secs) and CBF (18+/-3 secs), without a poststimulus undershoot. These data suggest that the BOLD undershoot after visual activation reflects a persistent increase in CMRO(2). These observations support the view that CBV and CBF responses elicited by neuronal activation are not necessarily coupled to local tissue metabolism.

Estimating a modified Grubb's exponent in healthy human brains with near infrared spectroscopy and transcranial Doppler

The relationship between cerebral blood volume (CBV) and flow (CBF) has been widely studied. One of the most significant early studies was by Grubb et al (1974 Stroke 5 630-9), who conducted hypercapnia studies in primates with positron emission tomography (PET) and empirically found CBV = 0.8 CBF(0.38). The exponent used here has since been known as the Grubb's exponent. In this paper, we define a similar exponent known as the modified Grubb's exponent, G', which is based on CBV and cerebral blood flow velocity (CBFV) estimated by near infrared spectroscopy (NIRS) and transcranial Doppler respectively, i.e. G' = log(CBV/CBV(0))/log(CBFV/CBFV(0)), where CBV(0) and CBFV(0) are baseline values. The aim of this study was to estimate the nominal value of the modified Grubb's exponent in healthy human brains. We conducted hypercapnia and hypocapnia studies on 14 healthy adult subjects. The correlation coefficient between log(CBV/CBV(0)) and log(CBFV/CBFV(0)) is 0.71 (p < 0.0001). We found a modified Grubb's exponent of 0.13 (the 95% confidence bounds are 0.10 and 0.17) which is expectedly lower than the conventional Grubb's exponents estimated by other techniques. The modified Grubb's exponent is a simple measure to quantify the hemodynamics between local CBV and global CBFV in the brain and as such may provide insight on brain physiology. Both NIRS and transcranial Doppler techniques are non-invasive and portable, facilitating future studies in other population groups such as brain-injured patients.

Multimodal functional neuroimaging: integrating functional MRI and EEG/MEG

Noninvasive functional neuroimaging, as an important tool for basic neuroscience research and clinical diagnosis, continues to face the need of improving the spatial and temporal resolution. While existing neuroimaging modalities might approach their limits in imaging capability mostly due to fundamental as well as technical reasons, it becomes increasingly attractive to integrate multiple complementary modalities in an attempt to significantly enhance the spatiotemporal resolution that cannot be achieved by any modality individually. Electrophysiological and hemodynamic/metabolic signals reflect distinct but closely coupled aspects of the underlying neural activity. Combining fMRI and EEG/MEG data allows us to study brain function from different perspectives. In this review, we start with an overview of the physiological origins of EEG/MEG and fMRI, as well as their fundamental biophysics and imaging principles, we proceed with a review of the major advances in the understanding and modeling of neurovascular coupling and in the methodologies for the fMRI-EEG/MEG simultaneous recording. Finally, we summarize important remaining issues and perspectives concerning multimodal functional neuroimaging, including brain connectivity imaging.

Cortical layer-dependent dynamic blood oxygenation, cerebral blood flow and cerebral blood volume responses during visual stimulation

The spatiotemporal characteristics of cerebral blood volume (CBV) and flow (CBF) responses are important for understanding neurovascular coupling mechanisms and blood oxygenation level-dependent (BOLD) signals. For this, cortical layer-dependent BOLD, CBV and CBF responses were measured at the cat visual cortex using fMRI. Major findings are: (i) the time-dependent fMRI cortical profile is dependent on imaging modality. Overall, the peak across the cortex occurs at the cortical surface for BOLD, but at the middle cortical layer for CBV and CBF. Compared to an initial stimulation period (4-10 s), the spatial specificity of CBV to the middle cortical layer increases significantly at a later time, while the specificity of BOLD and CBF slightly changes. (ii) The CBV response at the upper cortical area containing large pial vessels has a faster onset time and time to peak than the BOLD response at the same area, and a faster time to peak than CBV at the middle cortical area with microvessels. This suggests that the dilation of microvessels at the middle cortical area follows arterial volume increase at the surface of the cortex. (iii) For all three modalities, the post-stimulus undershoot was observed with the 60-s stimulation paradigm, indicating that the post-stimulus BOLD undershoot cannot be explained by the delayed venous CBV recovery theory under our experimental conditions. (iv) The relationship between CBV and CBF responses is both spatially and temporally dependent. Thus, a single power-law scaling constant (gamma value) may not be applicable for high-resolution study.

Identification and comparison of stochastic metabolic/hemodynamic models (sMHM) for the generation of the BOLD signal

This paper extends a previously formulated deterministic metabolic/hemodynamic model for the generation of blood oxygenated level dependent (BOLD) responses to include both physiological and observation stochastic components (sMHM). This adds a degree of flexibility when fitting the model to actual data by accounting for un-modelled activity. We then show how the innovation method can be used to estimate unobserved metabolic/hemodynamic as well as vascular variables of the sMHM, from simulated and actual BOLD data. The proposed estimation method allowed for doing model comparison by calculating the model's AIC and BIC. This methodology was then used to select between different neurovascular coupling assumptions underlying sMHM. The proposed framework was first validated on simulations and then applied to BOLD data from a motor task experiment. The models under comparison in the analysis of the actual data considered that vascular response was coupled to: (I) inhibition, (II) excitation, (III) both excitation and inhibition. Data was best described by model II, although model III was also supported.

Direct estimation of evoked hemoglobin changes by multimodality fusion imaging

In the last two decades, both diffuse optical tomography (DOT) and blood oxygen level dependent (BOLD)-based functional magnetic resonance imaging (fMRI) methods have been developed as noninvasive tools for imaging evoked cerebral hemodynamic changes in studies of brain activity. Although these two technologies measure functional contrast from similar physiological sources, i.e., changes in hemoglobin levels, these two modalities are based on distinct physical and biophysical principles leading to both limitations and strengths to each method. In this work, we describe a unified linear model to combine the complimentary spatial, temporal, and spectroscopic resolutions of concurrently measured optical tomography and fMRI signals. Using numerical simulations, we demonstrate that concurrent optical and BOLD measurements can be used to create cross-calibrated estimates of absolute micromolar deoxyhemoglobin changes. We apply this new analysis tool to experimental data acquired simultaneously with both DOT and BOLD imaging during a motor task, demonstrate the ability to more robustly estimate hemoglobin changes in comparison to DOT alone, and show how this approach can provide cross-calibrated estimates of hemoglobin changes. Using this multimodal method, we estimate the calibration of the 3 tesla BOLD signal to be -0.55%+/-0.40% signal change per micromolar change of deoxyhemoglobin.

Tracking the effects of crusher gradients on gradient-echo BOLD signal in space and time during rat sensory stimulation

A unique method to map the effect of crusher gradients in space and time on the gradient echo blood oxygen level dependent (BOLD) signal is introduced. Using the Radial Correlation Contrast (RCC) analysis method, amplitude-RCC maps at different time segments and different gradient strengths were obtained. The ratio of amplitude-RCC cluster volumes, with and without crusher gradients, showed a temporal dependency with stronger volume reduction for stimulation-onset versus stimulation-decline. Aside from signal-to-noise ratio reduction in diffusion weighted images, the average temporal patterns were equal. Comparison of the data with and without crushers showed a stronger reduction in local coherence for stimulation-onset times. We hypothesize that the stimulation decline was weighted by extravascular effects originating in expanded veins due to their larger volume and long range susceptibility which couples neighboring voxels. The ratio of amplitude-RCC with and without crushers calculated for each voxel at each time segment yielded a spatial-temporal mapping of the crusher effect. These maps suggest that early stimulation-onset ( approximately 9 s) is weighted by flow; later a dynamic steady-state between intra- and extravascular effects is obtained. Stimulation-decline was dominated by extravascular effects, and at late stimulation decline as well as at early stimulation onset, clusters were small and localized to expected site of neuronal activity.

Differentiating sensitivity of post-stimulus undershoot under diffusion weighting: implication of vascular and neuronal hierarchy

The widely used blood oxygenation level dependent (BOLD) signal during brain activation, as measured in typical fMRI methods, is composed of several distinct phases, the last of which, and perhaps the least understood, is the post-stimulus undershoot. Although this undershoot has been consistently observed, its hemodynamic and metabolic sources are still under debate, as evidences for sustained blood volume increases and metabolic activities have been presented. In order to help differentiate the origins of the undershoot from vascular and neuronal perspectives, we applied progressing diffusion weighting gradients to investigate the BOLD signals during visual stimulation. Three distinct regions were established and found to have fundamentally different properties in post-stimulus signal undershoot. The first region, with a small but focal spatial extent, shows a clear undershoot with decreasing magnitude under increasing diffusion weighting, which is inferred to represent intravascular signal from larger vessels with large apparent diffusion coefficients (ADC), or high mobility. The second region, with a large continuous spatial extent in which some surrounds the first region while some spreads beyond, also shows a clear undershoot but no change in undershoot amplitude with progressing diffusion weighting. This would indicate a source based on extravascular and small vessel signal with smaller ADC, or lower mobility. The third region shows no significant undershoot, and is largely confined to higher order visual areas. Given their intermediate ADC, it would likely include both large and small vessels. Thus the consistent observation of this third region would argue against a vascular origin but support a metabolic basis for the post-stimulus undershoot, and would appear to indicate a lack of sustained metabolic rate likely due to a lower oxygen metabolism in these higher visual areas. Our results are the first, to our knowledge, to suggest that the post-stimulus undershoots have a spatial dependence on the vascular and neuronal hierarchy, and that progressing flow-sensitized diffusion weighting can help delineate these dependences.

Quantification of venous blood signal contribution to BOLD functional activation in the auditory cortex at 3 T

Most modern techniques for functional magnetic resonance imaging (fMRI) rely on blood-oxygen-level-dependent (BOLD) contrast as the basic principle for detecting neuronal activation. However, the measured BOLD effect depends on a transfer function related to neurophysiological changes accompanying electrical neural activation. The spatial accuracy and extension of the region of interest are determined by vascular effect, which introduces incertitude on real neuronal activation maps. Our efforts have been directed towards the development of a new methodology that is capable of combining morphological, vascular and functional information; obtaining new insight regarding foci of activation; and distinguishing the nature of activation on a pixel-by-pixel basis. Six healthy volunteers were studied in a parametric auditory functional experiment at 3 T; activation maps were overlaid on a high-resolution brain venography obtained through a novel technique. The BOLD signal intensities of vascular and nonvascular activated voxels were analyzed and compared: it was shown that nonvascular active voxels have lower values for signal peak (P<10(-7)) and area (P<10(-8)) with respect to vascular voxels. The analysis showed how venous blood influenced the measured BOLD signals, supplying a technique to filter possible venous artifacts that potentially can lead to misinterpretation of fMRI results. This methodology, although validated in the auditory cortex activation, maintains a general applicability to any cortical fMRI study, as the basic concepts on which it relies on are not limited to this cortical region. The results obtained in this study can represent the basis for new methodologies and tools that are capable of adding further characterization to the BOLD signal properties.

A vascular anatomical network model of the spatio-temporal response to brain activation

Neuronal activity-induced changes in vascular tone and oxygen consumption result in a dynamic evolution of blood flow, volume, and oxygenation. Functional neuroimaging techniques, such as functional magnetic resonance imaging, optical imaging, and PET, provide indirect measures of the neural-induced vascular dynamics driving the blood parameters. Models connecting changes in vascular tone and oxygen consumption to observed changes in the blood parameters are needed to guide more quantitative physiological interpretation of these functional neuroimaging modalities. Effective lumped-parameter vascular balloon and Windkessel models have been developed for this purpose, but the lumping of the complex vascular network into a series of arterioles, capillaries, and venules allows only qualitative interpretation. We have therefore developed a parallel vascular anatomical network (VAN) model based on microscopically measurable properties to improve quantitative interpretation of the vascular response. The model, derived from measured physical properties, predicts baseline blood pressure and oxygen saturation distributions and dynamic responses consistent with literature. Furthermore, the VAN model allows investigation of spatial features of the dynamic vascular and oxygen response to neuronal activity. We find that a passive surround negative vascular response ("negative BOLD") is predicted, but that it underestimates recently observed surround negativity suggesting that additional active surround vasoconstriction is required to explain the experimental data.

Coupling between neuronal activity and microcirculation: implications for functional brain imaging

In the neocortex, neurons with similar response properties are often clustered together in column-like structures, giving rise to what has become known as functional architecture-the mapping of various stimulus feature dimensions onto the cortical sheet. At least partially, we owe this finding to the availability of several functional brain imaging techniques, both post-mortem and in-vivo, which have become available over the last two generations, revolutionizing neuroscience by yielding information about the spatial organization of active neurons in the brain. Here, we focus on how our understanding of such functional architecture is linked to the development of those functional imaging methodologies, especially to those that image neuronal activity indirectly, through metabolic or haemodynamic signals, rather than directly through measurement of electrical activity. Some of those approaches allow exploring functional architecture at higher spatial resolution than others. In particular, optical imaging of intrinsic signals reaches the striking detail of approximately 50 mum, and, together with other methodologies, it has allowed characterizing the metabolic and haemodynamic responses induced by sensory-evoked neuronal activity. Here, we review those findings about the spatio-temporal characteristics of neurovascular coupling and discuss their implications for functional brain imaging, including position emission tomography, and non-invasive neuroimaging techniques, such as funtional magnetic resonance imaging, applicable also to the human brain.

Biphasic hemodynamic responses influence deactivation and may mask activation in block-design fMRI paradigms

A previous block-design fMRI study revealed deactivation in the hippocampus in the transverse patterning task, specifically designed, on the basis of lesion literature, to engage hippocampal information processing. In the current study, a mixed block/event-related design was used to determine the temporal nature of the signal change leading to the seemingly paradoxical deactivation. All positive activations in the hippocampal-dependent condition, relative to a closely matched control task, were seen to result from positive BOLD transients in the typical 4-7 s poststimulus time range. However, most deactivations, including in the hippocampus and in other "default mode" regions commonly deactivated in cognitive tasks, were attributable to enhanced negative transient signals in a later time range, 10-12 s. This late hemodynamic transient was most pronounced in medial prefrontal cortex. In some regions, the hippocampal-dependent condition enhanced both the early positive and late negative transients to approximately the same degree, resulting in no significant signal change when block analysis is used, despite very different event-related responses. These results imply that delayed negative transients can play a role in determining the presence and sign of brain activation in block-design studies, in which case an event-related analysis can be more sensitive than a block analysis, even if the different conditions occur within blocks. In this case, default mode deactivations are timelocked to stimulus presentation as much as positive activations are, but in a later time range, suggesting a specific role of negative transient signals in task performance.

Efficacy of using mean arterial blood pressure sequence for three-element Windkessel model estimation

The three-element Windkessel model is widely used and accepted for analyzing blood flow and pressure in arterial system and cerebral circulation. In most studies, changes in mean arterial blood pressure data is used as input to estimate the model parameters. However, estimation of linear model parameters, using input-output data, requires that the input be persistently exciting. This study examined the efficacy of using mean arterial blood pressure (MABP) sequence as an input stimulus for estimating the parameters of the three-element Windkessel model. Additionally, the study explored the use of a shorter MABP data segment of 1.5 mm as compared to the commonly used 6 mm data. MABP data was obtained from 11 healthy subjects. One thousand three-element Windkessel models, with parameter values randomly selected to be within physiological range, were subjected to seven different input sequences. For each input sequence and model, the values of the model (target-parameters) were estimated. The seven input sequence were: 1) six minutes of MABP measured from subjects; 2-5) four 1.5 mm of measured MABP obtained by dividing the measured six minutes of MABP into non- overlapping contiguous segments; 6) a six-minutes of pseudo random binary sequence (PRBS) with amplitudes comparable to the MABP sequence; and 7) a 1.5 mm of PRBS sequence with amplitudes comparable to the MABP sequence. The MABP data used was randomly selected from the 11 subjects for each estimation run. The model parameter estimation method had two phases of optimization. In the first phase, the parameters were estimated and optimized using the frequency transform of the input and output. In the second phase, the values of the estimated parameters were used as initial estimates and time-domain optimization was carried out to further refine the estimates. Results from the study, comparing the estimated-parameters with the target-parameters, show that for the MABP data, there was no significant difference between using the six minutes or 1.5 mm of data for estimating the target-parameters. Also, parameters estimated from the MABP data were either equivalent or superior to the PRBS results, suggesting that changes in MABP can be used as an effective sequence for linear model estimation.

DEM: a variational treatment of dynamic systems

This paper presents a variational treatment of dynamic models that furnishes time-dependent conditional densities on the path or trajectory of a system's states and the time-independent densities of its parameters. These are obtained by maximising a variational action with respect to conditional densities, under a fixed-form assumption about their form. The action or path-integral of free-energy represents a lower bound on the model's log-evidence or marginal likelihood required for model selection and averaging. This approach rests on formulating the optimisation dynamically, in generalised coordinates of motion. The resulting scheme can be used for online Bayesian inversion of nonlinear dynamic causal models and is shown to outperform existing approaches, such as Kalman and particle filtering. Furthermore, it provides for dual and triple inferences on a system's states, parameters and hyperparameters using exactly the same principles. We refer to this approach as dynamic expectation maximisation (DEM).

CBF, BOLD, CBV, and CMRO(2) fMRI signal temporal dynamics at 500-msec resolution

PURPOSE

To investigate the temporal dynamics of blood oxygenation level-dependent (BOLD), cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of oxygen (CMRO(2)) changes due to forepaw stimulation with 500-msec resolution in a single setting.

MATERIALS AND METHODS

Forepaw stimulation and hypercapnic challenge on rats were studied. CBF and BOLD functional MRI (fMRI) were measured using the pseudo-continuous arterial spin-labeling technique at 500-msec resolution. CBV fMRI was measured using monocrystalline iron-oxide particles following CBF and BOLD measurements in the same animals. CMRO(2) change was estimated via the biophysical BOLD model with hypercapnic calibration. Percent changes and onset times were analyzed for the entire forepaw somatosensory cortices and three operationally defined cortical segments, denoted Layers I-III, IV-V, and VI.

RESULTS

BOLD change was largest in Layers I-III, whereas CBF, CBV, and CMRO(2) changes were largest in Layers IV-V. Among all fMRI signals in all layers, only the BOLD signal in Layers I-III showed a poststimulus undershoot. CBF and CBV dynamics were similar. Closer inspection showed that CBV increased slightly first (P < 0.05), but was slow to peak. CBF increased second, but peaked first. BOLD significantly lagged both CBF and CBV (P < 0.05).

CONCLUSION

This study provides important temporal dynamics of multiple fMRI signals at high temporal resolution in a single setting.

The post-stimulation undershoot in BOLD fMRI of human brain is not caused by elevated cerebral blood volume

Functional magnetic resonance imaging (fMRI) based on blood oxygenation level dependent (BOLD) contrast is the most widely used technique for imaging human brain function. However, the dynamic interplay of altered cerebral blood flow (CBF), cerebral blood volume (CBV), and oxidative metabolism (CMRO2) is not yet fully understood. One of the characteristics of the BOLD response is the post-stimulation undershoot, that is increased deoxyhemoglobin, which has been suggested to originate from a delayed recovery of elevated CBV or CMRO2 to baseline. To investigate the CBV contribution to the post-stimulation BOLD undershoot, we performed bolus-tracking experiments using a paramagnetic contrast agent in eight healthy subjects at 3 T. In an initial BOLD experiment without contrast agent, we determined the individual hemodynamic responsiveness. In two separate experiments, we then evaluated the relative CBV (rCBV) during visual stimulation and the post-stimulation undershoot, respectively. The results confirm a pronounced rCBV increase during stimulation (31.4+/-8.6%), but reveal no change in rCBV relative to baseline in the post-stimulation phase (0.7+/-7.2%). This finding renders a CBV contribution to the BOLD MRI undershoot unlikely and--in conjunction with a rapid post-stimulation return of CBF to baseline--supports the idea of a prolonged elevation of oxidative metabolism.

Differential activation of frontal and parietal regions during visual word recognition: an optical topography study

The present study examined cortical oxygenation changes during lexical decision on words and pseudowords using functional Near-Infrared Spectroscopy (fNIRS). Focal hyperoxygenation as an indicator of functional activation was compared over three target areas over the left hemisphere. A 52-channel Hitachi ETG-4000 was used covering the superior frontal gyrus (SFG), the left inferior parietal gyrus (IPG) and the left inferior frontal gyrus (IFG). To allow for anatomical inference a recently developed probabilistic mapping method was used to determine the most likely anatomic locations of the changes in cortical activation [Tsuzuki, D., Jurcak, V., Singh, A.K., Okamoto, M., Watanabe, E., Dan, I., 2007. Virtual spatial registration of stand-alone fNIRS data to MNI space. NeuroImage 43 (4), 1506-1518. Subjects made lexical decisions on 50 low and 50 high frequency words and 100 pseudowords. With respect to the lexicality effect, words elicited a larger focal hyperoxygenation in comparison to pseudowords in two regions identified as the SFG and left IPG. The SFG activation difference was interpreted to reflect decision-related mechanisms according to the Multiple Read-Out Model [Grainger, J., Jacobs, A.M., 1996. Orthographic processing in visual word recognition: A multiple read-out model. Psychological Review 103, 518-565]. The greater oxygenation response to words in the left IPG suggests that this region connects orthographic, phonological and semantic representations. A decrease of deoxygenated hemoglobin was observed to low frequency in comparison to high frequency words in a region identified as IFG. This region's sensitivity to word frequency suggests its involvement in grapheme-phoneme conversion, or its role during the selection of pre-activated semantic candidates.

Modelling vascular reactivity to investigate the basis of the relationship between cerebral blood volume and flow under CO2 manipulation

Changes in cerebral blood flow (f) and vascular volume (v) are of major interest in mapping cerebral activity and metabolism, but the relation between them currently lacks a sufficient theoretical basis. To address this we considered three models: a uniform reactive tube model (M1); an extension of M1 that includes passive arterial inflow and venous volume (M2); and a more anatomically plausible model (M3) consisting of 19 compartments representing the whole range of vascular sizes and respective CO2 reactivities, derived from literature data. We find that M2 cannot be described as the simple scaling of a tube law, but any divergence from a linear approximation is negligible within the narrow physiological range encountered experimentally. In order to represent correctly the empirically observed slope of the overall v-f relationship, the reactive bed should constitute about half of the total vascular volume, thus including a significant fraction of capillaries and/or veins. Model M3 demonstrates systematic variation of the slope of the v-f relationship between 0.16 and 1.0, depending on the vascular compartment under consideration. This is further complicated when other experimental approaches such as flow velocity are used as substitute measurements. The effect is particularly large in microvascular compartments, but when averaged with larger vessels the variations in slope are contained within 0.25 to 0.55 under conditions typical for imaging methods. We conclude that the v-f relationship is not a fixed function but that both the shape and slope depend on the composition of the reactive volume and the experimental methods used.

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.

Comparing hemodynamic models with DCM

The classical model of blood oxygen level-dependent (BOLD) responses by Buxton et al. [Buxton, R.B., Wong, E.C., Frank, L.R., 1998. Dynamics of blood flow and oxygenation changes during brain activation: the Balloon model. Magn. Reson. Med. 39, 855-864] has been very important in providing a biophysically plausible framework for explaining different aspects of hemodynamic responses. It also plays an important role in the hemodynamic forward model for dynamic causal modeling (DCM) of fMRI data. A recent study by Obata et al. [Obata, T., Liu, T.T., Miller, K.L., Luh, W.M., Wong, E.C., Frank, L.R., Buxton, R.B., 2004. Discrepancies between BOLD and flow dynamics in primary and supplementary motor areas: application of the Balloon model to the interpretation of BOLD transients. NeuroImage 21, 144-153] linearized the BOLD signal equation and suggested a revised form for the model coefficients. In this paper, we show that the classical and revised models are special cases of a generalized model. The BOLD signal equation of this generalized model can be reduced to that of the classical Buxton model by simplifying the coefficients or can be linearized to give the Obata model. Given the importance of hemodynamic models for investigating BOLD responses and analyses of effective connectivity with DCM, the question arises which formulation is the best model for empirically measured BOLD responses. In this article, we address this question by embedding different variants of the BOLD signal equation in a well-established DCM of functional interactions among visual areas. This allows us to compare the ensuing models using Bayesian model selection. Our model comparison approach had a factorial structure, comparing eight different hemodynamic models based on (i) classical vs. revised forms for the coefficients, (ii) linear vs. non-linear output equations, and (iii) fixed vs. free parameters, epsilon, for region-specific ratios of intra- and extravascular signals. Using fMRI data from a group of twelve subjects, we demonstrate that the best model is a non-linear model with a revised form for the coefficients, in which epsilon is treated as a free parameter.

Modeling dynamic cerebral blood volume changes during brain activation on the basis of the blood-nulled functional MRI signal

Recently, vascular space occupancy (VASO) based functional magnetic resonance imaging (fMRI) was proposed to detect dynamic cerebral blood volume (CBV) changes using the blood-nulled non-selective inversion recovery (NSIR) sequence. However, directly mapping the dynamic CBV change by the NSIR signal change is based on the assumption of slow water exchange (SWE) around the capillary regime without cerebral blood flow (CBF) effects. In the present study, a fast water exchange (FWE) model incorporating with flow effects was derived from the Bloch equations and implemented for the quantification of dynamic CBV changes using VASO-fMRI during brain activation. Simulated results showed that only subtle differences in CBV changes estimated by these two models were observed on the basis of previously published VASO results. The influence of related physiological and biophysical factors within typical ranges was evaluated in steady-state simulations. It was revealed that in the transient state the CBV curves could be delayed in comparison with measured NSIR curves owing to the imbalance between the inflowing and outflowing blood signals.

Optical brain imaging in vivo: techniques and applications from animal to man

Optical brain imaging has seen 30 years of intense development, and has grown into a rich and diverse field. In-vivo imaging using light provides unprecedented sensitivity to functional changes through intrinsic contrast, and is rapidly exploiting the growing availability of exogenous optical contrast agents. Light can be used to image microscopic structure and function in vivo in exposed animal brain, while also allowing noninvasive imaging of hemodynamics and metabolism in a clinical setting. This work presents an overview of the wide range of approaches currently being applied to in-vivo optical brain imaging, from animal to man. Techniques include multispectral optical imaging, voltage sensitive dye imaging and speckle-flow imaging of exposed cortex, in-vivo two-photon microscopy of the living brain, and the broad range of noninvasive topography and tomography approaches to near-infrared imaging of the human brain. The basic principles of each technique are described, followed by examples of current applications to cutting-edge neuroscience research. In summary, it is shown that optical brain imaging continues to grow and evolve, embracing new technologies and advancing to address ever more complex and important neuroscience questions.

Biophysical model for integrating neuronal activity, EEG, fMRI and metabolism

Our goal is to model the coupling between neuronal activity, cerebral metabolic rates of glucose and oxygen consumption, cerebral blood flow (CBF), electroencephalography (EEG) and blood oxygenation level-dependent (BOLD) responses. In order to accomplish this, two previous models are coupled: a metabolic/hemodynamic model (MHM) for a voxel, linking BOLD signals and neuronal activity, and a neural mass model describing the neuronal dynamics within a voxel and its interactions with voxels of the same area (short-range interactions) and other areas (long-range interactions). For coupling both models, we take as the input to the BOLD model, the number of active synapses within the voxel, that is, the average number of synapses that will receive an action potential within the time unit. This is obtained by considering the action potentials transmitted between neuronal populations within the voxel, as well as those arriving from other voxels. Simulations are carried out for testing the integrated model. Results show that realistic evoked potentials (EP) at electrodes on the scalp surface and the corresponding BOLD signals for each voxel are produced by the model. In another simulation, the alpha rhythm was reproduced and reasonable similarities with experimental data were obtained when calculating correlations between BOLD signals and the alpha power curve. The origin of negative BOLD responses and the characteristics of EEG, PET and BOLD signals in Alzheimer's disease were also studied.

Cerebral blood flow and BOLD responses to a memory encoding task: a comparison between healthy young and elderly adults

Functional magnetic resonance imaging (fMRI) studies of the medial temporal lobe have primarily made use of the blood oxygenation level dependent (BOLD) response to neural activity. The interpretation of the BOLD signal as a measure of medial temporal lobe function can be complicated, however, by changes in the cerebrovascular system that can occur with both normal aging and age-related diseases, such as Alzheimer's disease. Quantitative measures of the functional cerebral blood flow (CBF) response offer a useful complement to BOLD measures and have been shown to aid in the interpretation of fMRI studies. Despite these potential advantages, the application of ASL to fMRI studies of cognitive tasks and at-risk populations has been limited. In this study, we demonstrate the application of ASL fMRI to obtain measures of the CBF and BOLD responses to the encoding of natural scenes in healthy young (mean 25 years) and elderly (mean 74 years) adults. The percent CBF increase in the medial temporal lobe was significantly higher in the older adults, whereas the CBF levels during baseline and task conditions and during a separate resting-state scan were significantly lower in the older group. The older adults also showed slightly higher values for the BOLD response amplitude and the absolute change in CBF, but the age group differences were not significant. The percent CBF and BOLD responses are consistent with an age-related increase in the cerebral metabolic rate of oxygen metabolism (CMRO(2)) response to memory encoding.

Network structure of cerebral cortex shapes functional connectivity on multiple time scales

Neuronal dynamics unfolding within the cerebral cortex exhibit complex spatial and temporal patterns even in the absence of external input. Here we use a computational approach in an attempt to relate these features of spontaneous cortical dynamics to the underlying anatomical connectivity. Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, we find structure-function relations at multiple temporal scales. Functional networks recovered from long windows of neural activity (minutes) largely overlap with the underlying structural network. As a result, hubs in these long-run functional networks correspond to structural hubs. In contrast, significant fluctuations in functional topology are observed across the sequence of networks recovered from consecutive shorter (seconds) time windows. The functional centrality of individual nodes varies across time as interregional couplings shift. Furthermore, the transient couplings between brain regions are coordinated in a manner that reveals the existence of two anticorrelated clusters. These clusters are linked by prefrontal and parietal regions that are hub nodes in the underlying structural network. At an even faster time scale (hundreds of milliseconds) we detect individual episodes of interregional phase-locking and find that slow variations in the statistics of these transient episodes, contingent on the underlying anatomical structure, produce the transfer entropy functional connectivity and simulated blood oxygenation level-dependent correlation patterns observed on slower time scales.

A multicompartment vascular model for inferring baseline and functional changes in cerebral oxygen metabolism and arterial dilation

Functional hemodynamic responses are the composite results of underlying variations in cerebral oxygen consumption and the dilation of arterial vessels after neuronal activity. The development of biophysically based models of the cerebral vasculature allows the separation of the neuro-metabolic and neuro-vascular influences on measurable hemodynamic signals such as functional magnetic resonance imaging or optical imaging. We describe a multicompartment model of the vascular and oxygen transport dynamics associated with stimulus-driven neuronal activation. Our model offers several unique features compared with previous formulations such as the ability to estimate baseline blood flow, volume, and oxygen consumption from functional data. In addition, we introduce a capillary compliance model, arterial and venous oxygen permeability, and model the dynamics of extravascular tissue oxygenation. We apply this model to multimodal optical spectroscopic and laser speckle imaging of the rat somato-sensory cortex during nine conditions of whisker stimulation. By fitting the model using a psuedo-Bayesian framework to incorporate multimodal observations, we estimate baseline blood flow to be 94 (+/-15) mL/100 g min and baseline oxygen consumption to be 6.7 (+/-1.3) mL O(2)/100 g min. We calculate parametric, linear increases in arterial dilation (R(2)=0.96) and CMRO(2) (R(2)=0.87) responses over the nine conditions. Other parameters estimated by the model include vascular transit time and volume reserve, oxygen content, saturation, diffusivity rate constants, and partial pressure of oxygen in the vascular compartments and in the extravascular tissue. Finally, we compare this model to earlier work and find that the multicompartment model more accurately describes the observed oxygenation changes when compared with a single compartment version.

Arterial versus total blood volume changes during neural activity-induced cerebral blood flow change: implication for BOLD fMRI

Quantifying both arterial cerebral blood volume (CBV(a)) changes and total cerebral blood volume (CBV(t)) changes during neural activation can provide critical information about vascular control mechanisms, and help to identify the origins of neurovascular responses in conventional blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI). Cerebral blood flow (CBF), CBV(a), and CBV(t) were quantified by MRI at 9.4 T in isoflurane-anesthetized rats during 15-s duration forepaw stimulation. Cerebral blood flow and CBV(a) were simultaneously determined by modulation of tissue and vessel signals using arterial spin labeling, while CBV(t) was measured with a susceptibility-based contrast agent. Baseline versus stimulation values in a region centered over the somatosensory cortex were: CBF=150+/-18 versus 182+/-20 mL/100 g/min, CBV(a)=0.83+/-0.21 versus 1.17+/-0.30 mL/100 g, CBV(t)=3.10+/-0.55 versus 3.41+/-0.61 mL/100 g, and CBV(a)/CBV(t)=0.27+/-0.05 versus 0.34+/-0.06 (n=7, mean+/-s.d.). Neural activity-induced absolute changes in CBV(a) and CBV(t) are statistically equivalent and independent of the spatial extent of regional analysis. Under our conditions, increased CBV(t) during neural activation originates mainly from arterial rather than venous blood volume changes, and therefore a critical implication is that venous blood volume changes may be negligible in BOLD fMRI.

Functional MRI impulse response for BOLD and CBV contrast in rat somatosensory cortex

The contrast mechanism in functional MRI (fMRI) results from several vascular processes with different time scales, thus establishing a finite temporal resolution to fMRI experiments. In this work we measured the blood oxygen level-dependent (BOLD) and iron-oxide-derived cerebral blood volume (CBV) impulse response (IR) in a rat model of somatosensory brain activation at 11.7T. A binary m-sequence probe method was used to obtain high-sensitivity single-pixel estimates of the IR, from which two parameters-the full width at half maximum (FWHM) and the time to peak (TTP)-were determined as indices of the temporal resolution of the hemodynamic response (HDR). The results (N = 11) show that the CBV IR (N = 5, subset) is significantly narrower (FWHM = 1.37 +/- 0.11 s), and peaks earlier (TTP = 1.65 +/- 0.15 s) than the BOLD IR (N = 11, FWHM = 1.92 +/- 0.22 s and TTP = 2.18 +/- 0.14 s, respectively). These findings indicate that neurovascular control mechanisms have a temporal resolution better than 1.5 s FWHM, and point to a substantial contribution to BOLD of the dispersive transit of oxygenated hemoglobin across the rat vasculature, bringing important implications for the ultimately attainable temporal resolution of fMRI.

Theoretical study of BOLD response to sinusoidal input

This is a theoretical study of a compelling model of blood oxygen level-dependent (BOLD) response dynamics, measured in functional magnetic resonance imaging (fMRI). The novelty of this study involves the way the model is driven sinusoidally, in order to avoid onset and offset transients that pose difficulties in data analysis and interpretation. The driving frequency ranges over the natural time scales of the hemodynamic response (0.01-1 Hz), which also corresponds to the period in typical boxcar stimulus designs. At low stimulus amplitude, the predicted BOLD response is quasi-linear. The amplitude exhibits a mild peak near the modulation frequency 0.1 Hz, and falls rapidly for higher frequencies. The phase lag relative to the stimulus is a monotonically increasing function of the modulation frequency. These findings illustrate the dynamical nature of the BOLD response, and could be used to optimize experimental designs that admit sinusoidal modulation. Higher stimulus amplitude elicits nonlinear behavior characterized by a double peak during the positive deflection of the BOLD response. This finding is particularly interesting, because similar double peaks are seen frequently in BOLD data.

The triphasic intrinsic signal: implications for functional imaging

Intrinsic signal optical imaging with red illumination (ISOI) is used extensively to provide high spatial resolution maps of stimulus-evoked hemodynamic-related signals as an indirect means to map evoked neuronal activity. This evoked signal is generally described as beginning with an undershoot or "dip" in signal that is faster, more transient, and weaker compared with the subsequent signal overshoot. In contrast, the evoked signal detected with blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is generally described as containing an undershoot after the initial dip and overshoot, even though it, too, detects hemodynamic-related signals and its first two phases appear complementary to those of ISOI. Here, we used ISOI with 635 nm illumination to image over 13.5 s after a 1 s stimulus delivery to detect and successfully use the ISOI undershoot phase for functional mapping. Eight spatiotemporal attributes were assessed per signal phase including maximum areal extent and peak magnitude, both of which were largest for the ISOI overshoot, followed by the undershoot and then the initial dip. Peak activity location did not colocalize well between the three phases; furthermore, we found mostly modest correlations between attributes within each phase and sparse correlations between phases. Extended (13.5 s) electrophysiology recordings did not exhibit a reoccurrence of evoked suprathreshold or subthreshold neuronal responses that could be associated with the undershoot. Beyond the undershoot, additional overshoot/undershoot fluctuations were also mapped, but were typically less spatiotemporally specific to stimulus delivery. Implications for ISOI and BOLD fMRI are discussed.