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

Evaluation of calibrated and uncalibrated optical imaging approaches for relative cerebral oxygen metabolism measurements in awake mice

Objective. The continuous delivery of oxygen is critical to sustain brain function, and therefore, measuring brain oxygen consumption can provide vital physiological insight. In this work, we examine the impact of calibration and cerebral blood flow (CBF) measurements on the computation of the relative changes in the cerebral metabolic rate of oxygen consumption (rCMRO2) from hemoglobin-sensitive intrinsic optical imaging data. Using these data, we calculate rCMRO2, and calibrate the model using an isometabolic stimulus.Approach. We used awake head-fixed rodents to obtain hemoglobin-sensitive optical imaging data to test different calibrated and uncalibrated rCMRO2models. Hypercapnia was used for calibration and whisker stimulation was used to test the impact of calibration.Main results. We found that typical uncalibrated models can provide reasonable estimates of rCMRO2with differences as small as 7%-9% compared to their calibrated models. However, calibrated models showed lower variability and less dependence on baseline hemoglobin concentrations. Lastly, we found that supplying the model with measurements of CBF significantly reduced error and variability in rCMRO2change calculations.Significance. The effect of calibration on rCMRO2calculations remains understudied, and we systematically evaluated different rCMRO2calculation scenarios that consider including different measurement combinations. This study provides a quantitative comparison of these scenarios to evaluate trade-offs that can be vital to the design of blood oxygenation sensitive imaging experiments for rCMRO2calculation.

Time-Lagged Functional Ultrasound for Multi-Parametric Cerebral Hemodynamic Imaging

We introduce an ultrasound speckle decorrelation-based time-lagged functional ultrasound technique (tl-fUS) for the quantification of the relative changes in cerebral blood flow speed (rCBF [Formula: see text]), cerebral blood volume (rCBV) and cerebral blood flow (rCBF) during functional stimulations. Numerical simulations, phantom validations, and in vivo mouse brain experiments were performed to test the capability of tl-fUS to parse out and quantify the ratio change of these hemodynamic parameters. The blood volume change was found to be more prominent in arterioles compared to venules and the peak blood flow changes were around 2.5 times the peak blood volume change during brain activation, agreeing with previous observations in the literature. The tl-fUS shows the ability of distinguishing the relative changes of rCBFspeed, rCBV, and rCBF, which can inform specific physiological interpretations of the fUS measurements.

A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.

A quantitative model for human neurovascular coupling with translated mechanisms from animals

Neurons regulate the activity of blood vessels through the neurovascular coupling (NVC). A detailed understanding of the NVC is critical for understanding data from functional imaging techniques of the brain. Many aspects of the NVC have been studied both experimentally and using mathematical models; various combinations of blood volume and flow, local field potential (LFP), hemoglobin level, blood oxygenation level-dependent response (BOLD), and optogenetics have been measured and modeled in rodents, primates, or humans. However, these data have not been brought together into a unified quantitative model. We now present a mathematical model that describes all such data types and that preserves mechanistic behaviors between experiments. For instance, from modeling of optogenetics and microscopy data in mice, we learn cell-specific contributions; the first rapid dilation in the vascular response is caused by NO-interneurons, the main part of the dilation during longer stimuli is caused by pyramidal neurons, and the post-peak undershoot is caused by NPY-interneurons. These insights are translated and preserved in all subsequent analyses, together with other insights regarding hemoglobin dynamics and the LFP/BOLD-interplay, obtained from other experiments on rodents and primates. The model can predict independent validation-data not used for training. By bringing together data with complementary information from different species, we both understand each dataset better, and have a basis for a new type of integrative analysis of human data.

Measuring neuronal activity with diffuse correlation spectroscopy: a theoretical investigation

Significance: Diffuse correlation spectroscopy (DCS) measures cerebral blood flow non-invasively. Variations in blood flow can be used to detect neuronal activities, but its peak has a latency of a few seconds, which is slow for real-time monitoring. Neuronal cells also deform during activation, which, in principle, can be utilized to detect neuronal activity on fast timescales (within 100 ms) using DCS. Aims: We aim to characterize DCS signal variation quantified as the change of the decay time of the speckle intensity autocorrelation function during neuronal activation on both fast (within 100 ms) and slow (100 ms to seconds) timescales. Approach: We extensively modeled the variations in the DCS signal that are expected to arise from neuronal activation using Monte Carlo simulations, including the impacts of neuronal cell motion, vessel wall dilation, and blood flow changes. Results: We found that neuronal cell motion induces a DCS signal variation of ∼ 10 - 5 . We also estimated the contrast and number of channels required to detect hemodynamic signals at different time delays. Conclusions: From this extensive analysis, we do not expect to detect neuronal cell motion using DCS in the near future based on current technology trends. However, multi-channel DCS will be able to detect hemodynamic response with sub-second latency, which is interesting for brain-computer interfaces.

Seven Mathematical Models of Hemorrhagic Shock

Although mathematical modelling of pressure-flow dynamics in the cardiocirculatory system has a lengthy history, readily finding the appropriate model for the experimental situation at hand is often a challenge in and of itself. An ideal model would be relatively easy to use and reliable, besides being ethically acceptable. Furthermore, it would address the pathogenic features of the cardiovascular disease that one seeks to investigate. No universally valid model has been identified, even though a host of models have been developed. The object of this review is to describe several of the most relevant mathematical models of the cardiovascular system: the physiological features of circulatory dynamics are explained, and their mathematical formulations are compared. The focus is on the whole-body scale mathematical models that portray the subject's responses to hypovolemic shock. The models contained in this review differ from one another, both in the mathematical methodology adopted and in the physiological or pathological aspects described. Each model, in fact, mimics different aspects of cardiocirculatory physiology and pathophysiology to varying degrees: some of these models are geared to better understand the mechanisms of vascular hemodynamics, whereas others focus more on disease states so as to develop therapeutic standards of care or to test novel approaches. We will elucidate key issues involved in the modeling of cardiovascular system and its control by reviewing seven of these models developed to address these specific purposes.

Choosing an optimal wavelength to detect brain activity in functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) measures human brain function noninvasively. The optical response to oxy- and deoxy-hemoglobin concentration variations during brain activation is wavelength dependent because of the differing spectral shapes of the extinction coefficients of the two hemoglobin species. Choosing the optimal wavelength in fNIRS measurements is crucial to improving the performance of the technique. Here we report on a framework to estimate the spectral response to neural activation in a pre-defined local region. We found that the wavelength that exhibits the largest fractional change in the detected fluence with respect to the baseline value is around 830 nm.

A quantitative analysis of cell-specific contributions and the role of anesthetics to the neurovascular coupling

The neurovascular coupling (NVC) connects neuronal activity to hemodynamic responses in the brain. This connection is the basis for the interpretation of functional magnetic resonance imaging data. Despite the central role of this coupling, we lack detailed knowledge about cell-specific contributions and our knowledge about NVC is mainly based on animal experiments performed during anesthesia. Anesthetics are known to affect neuronal excitability, but how this affects the vessel diameters is not known. Due to the high complexity of NVC data, mathematical modeling is needed for a meaningful analysis. However, neither the relevant neuronal subtypes nor the effects of anesthetics are covered by current models. Here, we present a mathematical model including GABAergic interneurons and pyramidal neurons, as well as the effect of an anesthetic agent. The model is consistent with data from optogenetic experiments from both awake and anesthetized animals, and it correctly predicts data from experiments with different pharmacological modulators. The analysis suggests that no downstream anesthetic effects are necessary if one of the GABAergic interneuron signaling pathways include a Michaelis-Menten expression. This is the first example of a quantitative model that includes both the cell-specific contributions and the effect of an anesthetic agent on the NVC.

A review on low-dimensional physics-based models of systemic arteries: application to estimation of central aortic pressure

The physiological processes and mechanisms of an arterial system are complex and subtle. Physics-based models have been proven to be a very useful tool to simulate actual physiological behavior of the arteries. The current physics-based models include high-dimensional models (2D and 3D models) and low-dimensional models (0D, 1D and tube-load models). High-dimensional models can describe the local hemodynamic information of arteries in detail. With regard to an exact model of the whole arterial system, a high-dimensional model is computationally impracticable since the complex geometry, viscosity or elastic properties and complex vectorial output need to be provided. For low-dimensional models, the structure, centerline and viscosity or elastic properties only need to be provided. Therefore, low-dimensional modeling with lower computational costs might be a more applicable approach to represent hemodynamic properties of the entire arterial system and these three types of low-dimensional models have been extensively used in the study of cardiovascular dynamics. In recent decades, application of physics-based models to estimate central aortic pressure has attracted increasing interest. However, to our best knowledge, there has been few review paper about reconstruction of central aortic pressure using these physics-based models. In this paper, three types of low-dimensional physical models (0D, 1D and tube-load models) of systemic arteries are reviewed, the application of three types of models on estimation of central aortic pressure is taken as an example to discuss their advantages and disadvantages, and the proper choice of models for specific researches and applications are advised.

Estimating hemodynamic stimulus and blood vessel compliance from cerebral blood flow data

Several key brain imaging modalities that are intended for retrieving information about neuronal activity in brain, the BOLD fMRI as a foremost example, rely on the assumption that elevated neuronal activity elicits spatiotemporally well localized increase of the oxygenated blood volume, which in turn can be monitored non-invasively. The details of the signaling in the neurovascular unit during hyperemia are still not completely understood, and remain a topic of active research, requiring good mathematical models that are able to couple the different aspects of the signaling event. In this work, the question of estimating the hemodynamic stimulus function from cerebral blood flow data is addressed. In the present model, the hemodynamic stimulus is a non-specific signal from the electrophysiological and metabolic complex that controls the compliance of the blood vessels, leading to a vasodilation and thereby to an increase of blood flow. The underlying model is based on earlier literature, and it is further developed in this article for the needs of the inverse problem, which is solved using hierarchical Bayesian methodology, addressing also the poorly known model parameters.

Functional near-infrared spectroscopy for monitoring macaque cerebral motor activity during voluntary movements without head fixation

We developed an fNIRS system for monitoring macaque cerebral motor activity during voluntary movements without head fixation. fNIRS data at 27 channels in 7.5 mm spatial interval were calibrated by simulating light propagation through the macaque cranial tissues. The subject was instructed to repeatedly (75 times) retrieve a food pellet with alternating left or right hands from a food well for each session. We detected significant increases in oxygenated hemoglobin (Hb) and decrease in deoxygenated Hb in the primary motor area (M1) contralateral to the hand used. In more rostral and ventral regions in both hemispheres, the hemodynamic similarly changed regardless of used hand. Direct feeding to the mouth eliminated activity in the hand M1 whereas that at bilateral ventral regions (mouth M1 area) remained. Statistical analyses for the hemodynamics between left/right-hand use revealed the location of each hand M1 in either hemisphere. In these regions, the maximum amplitude and time of the maximum amplitude in the hemodynamic response evoked by food retrieval were highly correlated with the time associated with food retrieval. We could assign each channel to an appropriate functional motor area, providing proof of principle for future studies involving brain damage models in freely moving macaque monkeys.

Characterization of the hemodynamic response function across the majority of human cerebral cortex

A brief (<4 s) period of neural activation evokes a stereotypical sequence of vascular and metabolic events to create the hemodynamic response function (HRF) measured using functional magnetic resonance imaging (fMRI). Linear analysis of fMRI data requires that the HRF be treated as an impulse response, so the character and temporal stability of the HRF are critical issues. Here, a simple audiovisual stimulus combined with a fast-paced task was used to evoke a strong HRF across a majority, ∼77%, of cortex during a single scanning session. High spatiotemporal resolution (2-mm voxels, 1.25-s acquisition time) was used to focus HRF measurements specifically on the gray matter for whole brain. The majority of activated cortex responds with positive HRFs, while ∼27% responds with negative (inverted) HRFs. Spatial patterns of the HRF response amplitudes were found to be similar across subjects. Timing of the initial positive lobe of the HRF was relatively stable across the cortical surface with a mean of 6.1 ± 0.6 s across subjects, yet small but significant timing variations were also evident in specific regions of cortex. The results provide guidance for linear analysis of fMRI data. More importantly, this method provides a means to quantify neurovascular function across most of the brain, with potential clinical utility for the diagnosis of brain pathologies such as traumatic brain injury.

Reliability of the depth-dependent high-resolution BOLD hemodynamic response in human visual cortex and vicinity

Functional magnetic resonance imaging (fMRI) often relies on a hemodynamic response function (HRF), the stereotypical blood oxygen level dependent (BOLD) response elicited by a brief (<4s) stimulus. Early measurements of the HRF used coarse spatial resolutions (≥3mm voxels) that would generally include contributions from white matter, gray matter, and the extra-pial compartment (the space between the pial surface and skull including pial blood vessels) within each voxel. To resolve these contributions, high-resolution fMRI (0.9-mm voxels) was performed at 3T in early visual cortex and its apposed white-matter and extra-pial compartments. The results characterized the depth dependence of the HRF and its reliability during nine fMRI sessions. Significant HRFs were observed in white-matter and extra-pial compartments as well as in gray matter. White-matter HRFs were faster and weaker than in the gray matter, while extra-pial HRFs were comparatively slower and stronger. Depth trends of the HRF peak amplitude were stable throughout a broad depth range that included all three compartments for each session. Across sessions, however, the depth trend of HRF peak amplitudes was stable only in the white matter and deep-intermediate gray matter, while there were strong session-to-session variations in the superficial gray matter and the extra-pial compartment. Thus, high-resolution fMRI can resolve significant and dynamically distinct HRFs in gray matter, white matter, and extra-pial compartments.

The capillary bed offers the largest hemodynamic resistance to the cortical blood supply

The cortical angioarchitecture is a key factor in controlling cerebral blood flow and oxygen metabolism. Difficulties in imaging the complex microanatomy of the cortex have so far restricted insight about blood flow distribution in the microcirculation. A new methodology combining advanced microscopy data with large scale hemodynamic simulations enabled us to quantify the effect of the angioarchitecture on the cerebral microcirculation. High-resolution images of the mouse primary somatosensory cortex were input into with a comprehensive computational model of cerebral perfusion and oxygen supply ranging from the pial vessels to individual brain cells. Simulations of blood flow, hematocrit and oxygen tension show that the wide variation of hemodynamic states in the tortuous, randomly organized capillary bed is responsible for relatively uniform cortical tissue perfusion and oxygenation. Computational analysis of microcirculatory blood flow and pressure drops further indicates that the capillary bed, including capillaries adjacent to feeding arterioles (d < 10 µm), are the largest contributors to hydraulic resistance.

Impact of temporal resolution on estimating capillary RBC-flux with optical coherence tomography

Optical coherence tomography (OCT) has been used to measure capillary red blood cell (RBC) flux. However, one important technical issue is that the accuracy of this method is subject to the temporal resolution ( ? t ) of the repeated RBC-passage B-scans. A ceiling effect arises due to an insufficient ? t limiting the maximum RBC-flux that can be measured. In this letter, we first present simulations demonstrating that ? t = 1.5 ?? ms permits measuring RBC-flux up to 150 ?? RBCs / s with an underestimation of 9%. The simulations further show that measurements with ? t = 3 and 4.5 ms provide relatively less accurate estimates for typical physiological fluxes. We provide experimental data confirming the simulation results showing that reduced temporal resolution (i.e., a longer ? t ) results in an underestimation of mean flux and compresses the distribution of measured fluxes, which potentially confounds physiological interpretation of the results. The results also apply to RBC-passage measurements made with confocal and two-photon microscopy for estimating capillary RBC-flux.

Investigating Human Neurovascular Coupling Using Functional Neuroimaging: A Critical Review of Dynamic Models

The mechanisms that link a transient neural activity to the corresponding increase of cerebral blood flow (CBF) are termed neurovascular coupling (NVC). They are possibly impaired at early stages of small vessel or neurodegenerative diseases. Investigation of NVC in humans has been made possible with the development of various neuroimaging techniques based on variations of local hemodynamics during neural activity. Specific dynamic models are currently used for interpreting these data that can include biophysical parameters related to NVC. After a brief review of the current knowledge about possible mechanisms acting in NVC we selected seven models with explicit integration of NVC found in the literature. All these models were described using the same procedure. We compared their physiological assumptions, mathematical formalism, and validation. In particular, we pointed out their strong differences in terms of complexity. Finally, we discussed their validity and their potential applications. These models may provide key information to investigate various aspects of NVC in human pathology.

Nonlinear extension of a hemodynamic linear model for coherent hemodynamics spectroscopy

In this work, we are proposing an extension of a recent hemodynamic model (Fantini, 2014a), which was developed within the framework of a novel approach to the study of tissue hemodynamics, named coherent hemodynamics spectroscopy (CHS). The previous hemodynamic model, from a signal processing viewpoint, treats the tissue microvasculature as a linear time-invariant system, and considers changes of blood volume, capillary blood flow velocity and the rate of oxygen diffusion as inputs, and the changes of oxy-, deoxy-, and total hemoglobin concentrations (measured in near infrared spectroscopy) as outputs. The model has been used also as a forward solver in an inversion procedure to retrieve quantitative parameters that assess physiological and biological processes such as microcirculation, cerebral autoregulation, tissue metabolic rate of oxygen, and oxygen extraction fraction. Within the assumption of "small" capillary blood flow velocity oscillations the model showed that the capillary and venous compartments "respond" to this input as low pass filters, characterized by two distinct impulse response functions. In this work, we do not make the assumption of "small" perturbations of capillary blood flow velocity by solving without approximations the partial differential equation that governs the spatio-temporal behavior of hemoglobin saturation in capillary and venous blood. Preliminary comparison between the linear time-invariant model and the extended model (here identified as nonlinear model) are shown for the relevant parameters measured in CHS as a function of the oscillation frequency (CHS spectra). We have found that for capillary blood flow velocity oscillations with amplitudes up to 10% of the baseline value (which reflect typical scenarios in CHS), the discrepancies between CHS spectra obtained with the linear and nonlinear models are negligible. For larger oscillations (~50%) the linear and nonlinear models yield CHS spectra with differences within typical experimental errors, but further investigation is needed to assess the effect of these differences. Flow oscillations larger than 10-20% are not typically induced in CHS; therefore, the results presented in this work indicate that a linear hemodynamic model, combined with a method to elicit controlled hemodynamic oscillations (as done for CHS), is appropriate for the quantitative assessment of cerebral microcirculation.

Arterial impulse model for the BOLD response to brief neural activation

The blood oxygen level dependent (BOLD) signal evoked by brief neural stimulation, the hemodynamic response function (HRF), is a critical feature of neurovascular coupling. The HRF is directly related to local transient changes in oxygen supplied by cerebral blood flow (CBF) and oxygen demand, the cerebral metabolic rate of oxygen (CMRO2). Previous efforts to explain the HRF have relied upon the hypothesis that CBF produces a non-linear venous dilation within the cortical parenchyma. Instead, the observed dynamics correspond to prompt arterial dilation without venous volume change. This work develops an alternative biomechanical model for the BOLD response based on the hypothesis that prompt upstream dilation creates an arterial flow impulse amenable to linear description. This flow model is coupled to a continuum description of oxygen transport. Measurements using high-resolution fMRI demonstrate the efficacy of the model. The model predicts substantial spatial variations of the oxygen saturation along the length of capillaries and veins, and fits the varied gamut of measured HRFs by the combined effects of corresponding CBF and CMRO2 responses. Three interesting relationships among the hemodynamic parameters are predicted. First, there is an offset linear correlation with approximately unity slope between CBF and CMRO2 responses. Second, the HRF undershoot is strongly correlated to the corresponding CBF undershoot. Third, late-time-CMRO2 response can contribute to a slow recovery to baseline, lengthening the HRF undershoot. The model provides a powerful mathematical framework to understand the dynamics of neurovascular and neurometabolic responses that form the BOLD HRF.

Quantifying the microvascular origin of BOLD-fMRI from first principles with two-photon microscopy and an oxygen-sensitive nanoprobe

The blood oxygenation level-dependent (BOLD) contrast is widely used in functional magnetic resonance imaging (fMRI) studies aimed at investigating neuronal activity. However, the BOLD signal reflects changes in blood volume and oxygenation rather than neuronal activity per se. Therefore, understanding the transformation of microscopic vascular behavior into macroscopic BOLD signals is at the foundation of physiologically informed noninvasive neuroimaging. Here, we use oxygen-sensitive two-photon microscopy to measure the BOLD-relevant microvascular physiology occurring within a typical rodent fMRI voxel and predict the BOLD signal from first principles using those measurements. The predictive power of the approach is illustrated by quantifying variations in the BOLD signal induced by the morphological folding of the human cortex. This framework is then used to quantify the contribution of individual vascular compartments and other factors to the BOLD signal for different magnet strengths and pulse sequences.

A mathematical model relating cortical oxygenated and deoxygenated hemoglobin flows and volumes to neural activity

OBJECTIVE

To describe a toolkit of components for mathematical models of the relationship between cortical neural activity and space-resolved and time-resolved flows and volumes of oxygenated and deoxygenated hemoglobin motivated by optical intrinsic signal imaging (OISI).

APPROACH

Both blood flow and blood volume and both oxygenated and deoxygenated hemoglobin and their interconversion are accounted for. Flow and volume are described by including analogies to both resistive and capacitive electrical circuit elements. Oxygenated and deoxygenated hemoglobin and their interconversion are described by generalization of Kirchhoff's laws based on well-mixed compartments.

MAIN RESULTS

Mathematical models built from this toolkit are able to reproduce experimental single-stimulus OISI results that are described in papers from other research groups and are able to describe the response to multiple-stimuli experiments as a sublinear superposition of responses to the individual stimuli.

SIGNIFICANCE

The same assembly of tools from the toolkit but with different parameter values is able to describe effects that are considered distinctive, such as the presence or absence of an initial decrease in oxygenated hemoglobin concentration, indicating that the differences might be due to unique parameter values in a subject rather than different fundamental mechanisms.

The effects of transit time heterogeneity on brain oxygenation during rest and functional activation

The interpretation of regional blood flow and blood oxygenation changes during functional activation has evolved from the concept of 'neurovascular coupling', and hence the regulation of arteriolar tone to meet metabolic demands. The efficacy of oxygen extraction was recently shown to depend on the heterogeneity of capillary flow patterns downstream. Existing compartment models of the relation between tissue metabolism, blood flow, and blood oxygenation, however, typically assume homogenous microvascular flow patterns. To take capillary flow heterogeneity into account, we modeled the effect of capillary transit time heterogeneity (CTH) on the 'oxygen conductance' used in compartment models. We show that the incorporation of realistic reductions in CTH during functional hyperemia improves model fits to dynamic blood flow and oxygenation changes acquired during functional activation in a literature animal study. Our results support earlier observations that oxygen diffusion properties seemingly change during various physiologic stimuli, and posit that this phenomenon is related to parallel changes in capillary flow patterns. Furthermore, our results suggest that CTH must be taken into account when inferring brain metabolism from changes in blood flow- or blood oxygenation-based signals .

Regulation of blood flow in the retinal trilaminar vascular network

Light stimulation evokes neuronal activity in the retina, resulting in the dilation of retinal blood vessels and increased blood flow. This response, named functional hyperemia, brings oxygen and nutrients to active neurons. However, it remains unclear which vessels mediate functional hyperemia. We have characterized blood flow regulation in the rat retina in vivo by measuring changes in retinal vessel diameter and red blood cell (RBC) flux evoked by a flickering light stimulus. We found that, in first- and second-order arterioles, flicker evoked large (7.5 and 5.0%), rapid (0.73 and 0.70 s), and consistent dilations. Flicker-evoked dilations in capillaries were smaller (2.0%) and tended to have a slower onset (0.97 s), whereas dilations in venules were smaller (1.0%) and slower (1.06 s) still. The proximity of pericyte somata did not predict capillary dilation amplitude. Expression of the contractile protein α-smooth muscle actin was high in arterioles and low in capillaries. Unexpectedly, we found that blood flow in the three vascular layers was differentially regulated. Flicker stimulation evoked far larger dilations and RBC flux increases in the intermediate layer capillaries than in the superficial and deep layer capillaries (2.6 vs 0.9 and 0.7% dilation; 25.7 vs 0.8 and 11.3% RBC flux increase). These results indicate that functional hyperemia in the retina is driven primarily by active dilation of arterioles. The dilation of intermediate layer capillaries is likely mediated by active mechanisms as well. The physiological consequences of differential regulation in the three vascular layers are discussed.

Model of the transient neurovascular response based on prompt arterial dilation

Brief neural stimulation results in a stereotypical pattern of vascular and metabolic response that is the basis for popular brain-imaging methods such as functional magnetic resonance imagine. However, the mechanisms of transient oxygen transport and its coupling to cerebral blood flow (CBF) and oxygen metabolism (CMRO2) are poorly understood. Recent experiments show that brief stimulation produces prompt arterial vasodilation rather than venous vasodilation. This work provides a neurovascular response model for brief stimulation based on transient arterial effects using one-dimensional convection-diffusion transport. Hemoglobin oxygen dissociation is included to enable predictions of absolute oxygen concentrations. Arterial CBF response is modeled using a lumped linear flow model, and CMRO2 response is modeled using a gamma function. Using six parameters, the model successfully fit 161/166 measured extravascular oxygen time courses obtained for brief visual stimulation in cat cerebral cortex. Results show how CBF and CMRO2 responses compete to produce the observed features of the hemodynamic response: initial dip, hyperoxic peak, undershoot, and ringing. Predicted CBF and CMRO2 response amplitudes are consistent with experimental measurements. This model provides a powerful framework to quantitatively interpret oxygen transport in the brain; in particular, its intravascular oxygen concentration predictions provide a new model for fMRI responses.

Extra permeability is required to model dynamic oxygen measurements: evidence for functional recruitment?

Neural activation triggers a rapid, focal increase in blood flow and thus oxygen delivery. Local oxygen consumption also increases, although not to the same extent as oxygen delivery. This 'uncoupling' enables a number of widely-used functional neuroimaging techniques; however, the physiologic mechanisms that govern oxygen transport under these conditions remain unclear. Here, we explore this dynamic process using a new mathematical model. Motivated by experimental observations and previous modeling, we hypothesized that functional recruitment of capillaries has an important role during neural activation. Using conventional mechanisms alone, the model predictions were inconsistent with in vivo measurements of oxygen partial pressure. However, dynamically increasing net capillary permeability, a simple description of functional recruitment, led to predictions consistent with the data. Increasing permeability in all vessel types had the same effect, but two alternative mechanisms were unable to produce predictions consistent with the data. These results are further evidence that conventional models of oxygen transport are not sufficient to predict dynamic experimental data. The data and modeling suggest that it is necessary to include a mechanism that dynamically increases net vascular permeability. While the model cannot distinguish between the different possibilities, we speculate that functional recruitment could have this effect in vivo.

Cerebral microcirculation and oxygen tension in the human secondary cortex

The three-dimensional spatial arrangement of the cortical microcirculatory system is critical for understanding oxygen exchange between blood vessels and brain cells. A three-dimensional computer model of a 3 × 3 × 3 mm(3) subsection of the human secondary cortex was constructed to quantify oxygen advection in the microcirculation, tissue oxygen perfusion, and consumption in the human cortex. This computer model accounts for all arterial, capillary and venous blood vessels of the cerebral microvascular bed as well as brain tissue occupying the extravascular space. Microvessels were assembled with optimization algorithms emulating angiogenic growth; a realistic capillary bed was built with space filling procedures. The extravascular tissue was modeled as a porous medium supplied with oxygen by advection-diffusion to match normal metabolic oxygen demand. The resulting synthetic computer generated network matches prior measured morphometrics and fractal patterns of the cortical microvasculature. This morphologically accurate, physiologically consistent, multi-scale computer network of the cerebral microcirculation predicts the oxygen exchange of cortical blood vessels with the surrounding gray matter. Oxygen tension subject to blood pressure and flow conditions were computed and validated for the blood as well as brain tissue. Oxygen gradients along arterioles, capillaries and veins agreed with in vivo trends observed recently in imaging studies within experimental tolerances and uncertainty.

Neurovascular coupling: in vivo optical techniques for functional brain imaging

Optical imaging techniques reflect different biochemical processes in the brain, which is closely related with neural activity. Scientists and clinicians employ a variety of optical imaging technologies to visualize and study the relationship between neurons, glial cells and blood vessels. In this paper, we present an overview of the current optical approaches used for the in vivo imaging of neurovascular coupling events in small animal models. These techniques include 2-photon microscopy, laser speckle contrast imaging (LSCI), voltage-sensitive dye imaging (VSDi), functional photoacoustic microscopy (fPAM), functional near-infrared spectroscopy imaging (fNIRS) and multimodal imaging techniques. The basic principles of each technique are described in detail, followed by examples of current applications from cutting-edge studies of cerebral neurovascular coupling functions and metabolic. Moreover, we provide a glimpse of the possible ways in which these techniques might be translated to human studies for clinical investigations of pathophysiology and disease. In vivo optical imaging techniques continue to expand and evolve, allowing us to discover fundamental basis of neurovascular coupling roles in cerebral physiology and pathophysiology.

Dynamic model for the tissue concentration and oxygen saturation of hemoglobin in relation to blood volume, flow velocity, and oxygen consumption: Implications for functional neuroimaging and coherent hemodynamics spectroscopy (CHS)

This article presents a dynamic model that quantifies the temporal evolution of the concentration and oxygen saturation of hemoglobin in tissue, as determined by time-varying hemodynamic and metabolic parameters: blood volume, flow velocity, and oxygen consumption. This multi-compartment model determines separate contributions from arterioles, capillaries, and venules that comprise the tissue microvasculature, and treats them as a complete network, without making assumptions on the details of the architecture and morphology of the microvascular bed. A key parameter in the model is the effective blood transit time through the capillaries and its associated probability of oxygen release from hemoglobin to tissue, as described by a rate constant for oxygen diffusion. The solution of the model in the time domain predicts the signals measured by hemodynamic-based neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) in response to brain activation. In the frequency domain, the model yields an analytical solution based on a phasor representation that provides a framework for quantitative spectroscopy of coherent hemodynamic oscillations. I term this novel technique coherent hemodynamics spectroscopy (CHS), and this article describes how it can be used for the assessment of cerebral autoregulation and the study of hemodynamic oscillations resulting from a variety of periodic physiological challenges, brain activation protocols, or physical maneuvers.

Computational modeling of the transient hemodynamic response in cerebral cortex

Neural activity triggers a vascular response in the brain that leads to transient changes in oxygen transport, and this mechanism is the basis for popular and powerful functional imaging methods. However, there is limited understanding of oxygen delivery to cerebral cortex both in steady state and during transient perturbations. In this study, a computational model for oxygen transport in the brain was developed and used to fit polarographic oxygen measurements during transient stimulation in cerebral cortex. The hemodynamic response function (HRF) was modeled with convection-diffusion transport in a four-compartment system (erythrocyte, intravascular, extravascular, and intracellular) that includes oxygen dissociation from hemoglobin. This model explained the dynamics of oxygen transport in cortex after brief visual stimulation, successfully fitting ~90% of experimental measurements within a realistic range of parameters for steady-state flow speed and oxygen consumption, as well as flow and oxygen uptake perturbations.

Separation of fNIRS signals into functional and systemic components based on differences in hemodynamic modalities

In conventional functional near-infrared spectroscopy (fNIRS), systemic physiological fluctuations evoked by a body's motion and psychophysiological changes often contaminate fNIRS signals. We propose a novel method for separating functional and systemic signals based on their hemodynamic differences. Considering their physiological origins, we assumed a negative and positive linear relationship between oxy- and deoxyhemoglobin changes of functional and systemic signals, respectively. Their coefficients are determined by an empirical procedure. The proposed method was compared to conventional and multi-distance NIRS. The results were as follows: (1) Nonfunctional tasks evoked substantial oxyhemoglobin changes, and comparatively smaller deoxyhemoglobin changes, in the same direction by conventional NIRS. The systemic components estimated by the proposed method were similar to the above finding. The estimated functional components were very small. (2) During finger-tapping tasks, laterality in the functional component was more distinctive using our proposed method than that by conventional fNIRS. The systemic component indicated task-evoked changes, regardless of the finger used to perform the task. (3) For all tasks, the functional components were highly coincident with signals estimated by multi-distance NIRS. These results strongly suggest that the functional component obtained by the proposed method originates in the cerebral cortical layer. We believe that the proposed method could improve the reliability of fNIRS measurements without any modification in commercially available instruments.

Neurovascular deconvolution of optical signals as a proxy for the true neuronal inputs

Since the Kalman filter and Monte Carlo techniques, much theoretical work has been put into the development of signal deconvolution tools. Among recent developments taking place in neuroscience are Dynamic Expectation Maximization, Generalized Filtering and the Cubature Kalman Filter. While there are exciting prospects to use these tools for Dynamic Causal Modeling and other analyses of networks, there has been comparatively little work to validate the algorithms on controlled experimental data. In this work, the latest evolution of these tools, the square-root cubature Kalman smoother (SCKS), is tested for its effectiveness on multimodal neurovascular data. Multispectral intrinsic optical imaging and electrophysiological measurements of Wistar rats are used in combination with somatosensory stimulation. The Buxton-Friston (B-F) balloon model is then deconvolved with the SCKS algorithm to obtain the estimated neuronal inputs u(t) from the hemodynamic measurements (flow, oxy- and deoxygenated hemoglobin).

RESULTS

The estimated neuronal inputs are compared to the stimulation protocol and a sensitivity and specificity analysis is carried out. SCKS succeeds in recovering most of the stimulations. Next, the estimated inputs are compared to actual measures of neuronal activity: local field potentials (LFPs) and multiunit activity (MUA). Good sensitivity of the technique is obtained with both LFPs and MUA over the whole recordings, with the area of the ROC curves favoring LFPs. A weak correlation between SCKS estimated inputs and LFPs is found outside stimulation periods, significant at one standard deviation. Finally, the accuracy of state reconstructions is studied and SCKS reconstructed states are highly concordant with measured states.

Arteries dominate volume changes during brief functional hyperemia: evidence from mathematical modelling

Variations in local neural activity are accompanied by rapid, focal changes in cerebral blood flow and volume. While a range of observations have shown that dilation occurs in cerebral arteries, there is conflicting evidence about the significance of volume changes in post-arteriole vessels. Here, we reconcile the competing observations using a new mathematical model of the hemodynamic response. First, we followed a 'top down' approach, without constraining the model, but using experimental observations at progressively more detailed scales to ensure physiological behaviour. Then, we blocked dilation of post-arteriole vessels, and predicted observations at progressively more aggregated scales (a 'bottom up' approach). Predictions of blood flow, volume, velocity, and vessel diameter changes were consistent with experimental observations. Interestingly, the model predicted small, slow increases in capillary and venous diameter in agreement with recent in vivo data. Blocking dilation in these vessels led to erroneous volume predictions. The results are further evidence that arteries make up the majority of blood volume increases during brief functional activation. However, dilation of capillaries and veins appears to be increasingly significant during extended stimulation. These are important considerations when interpreting results from different neurovascular imaging modalities.

Optical probes and techniques for O2 measurement in live cells and tissue

In recent years, significant progress has been achieved in the sensing and imaging of molecular oxygen (O₂) in biological samples containing live cells and tissue. We review recent developments in the measurement of O₂ in such samples by optical means, particularly using the phosphorescence quenching technique. The main types of soluble O₂ sensors are assessed, including small molecule, supramolecular and particle-based structures used as extracellular or intracellular probes in conjunction with different detection modalities and measurement formats. For the different O₂ sensing systems, particular attention is paid to their merits and limitations, analytical performance, general convenience and applicability in specific biological applications. The latter include measurement of O₂ consumption rate, sample oxygenation, sensing of intracellular O₂, metabolic assessment of cells, and O₂ imaging of tissue, vasculature and individual cells. Altogether, this gives the potential user a comprehensive guide for the proper selection of the appropriate optical probe(s) and detection platform to suit their particular biological applications and measurement requirements.

IRON fMRI measurements of CBV and implications for BOLD signal

Changes in cerebral blood volume (CBV) and blood magnetization each induce changes in the transverse relaxation rate of MRI signal that are associated with changes in cerebral activity. BOLD signal, the preeminent method for non-invasive localization of task-induced brain function in human subjects, reflects a combination of changes in CBV and blood magnetization. Intravenous injection of paramagnetic contrast media, usually iron oxide particles surrounded by larger macromolecules, can overwhelm the BOLD response and sensitize signal to blood plasma volume, a method we have deemed "IRON" fMRI. The practical advantage of this technique is the ability to optimize blood magnetization at any echo time, enabling high detection power and the use of short echo times; for these reasons, IRON fMRI has become a valuable imaging tool in animal models. The temporal response of blood plasma volume is quite different from blood flow and BOLD signal; thus, CBV has been identified as a prominent source of transient features of the BOLD response. This article reviews the methodological advantages of the IRON method and how CBV measurements have informed our understanding of the BOLD response.

Calcium signaling in cerebral vasoregulation

The tight coupling of regional neurometabolic activity with synaptic activity and regional cerebral blood perfusion constitutes a single functional unit, described generally as a neurovascular unit. This is central to any discussion of haemodynamic response linked to any neuronal activation. In normal as well as in pathologic conditions, neurons, astrocytes and endothelial cells of the vasculature interact to generate the complex activity-induced cerebral haemodynamic responses, with astrocytes not only partaking in the signaling but actually controlling it in many cases. Neurons and astrocytes have highly integrated signaling mechanisms, yet they form two separate networks. Bidirectional neuron-astrocyte interactions are crucial for the function and survival of the central nervous system. The primary purpose of such regulation is the homeostasis of the brain's microenvironment. In the maintenance of such homeostasis, astrocytic calcium response is a crucial variable in determining neurovascular control. Future work will be directed towards resolving the nature and extent of astrocytic calcium-mediated mechanisms for gene transcription, in modelling neurovascular control, and in determining calcium sensitive imaging assays that can capture disease variables.

Implicit and explicit prior information in near-infrared spectral imaging: accuracy, quantification and diagnostic value

Near-infrared spectroscopy (NIRS) of tissue provides quantification of absorbers, scattering and luminescent agents in bulk tissue through the use of measurement data and assumptions. Prior knowledge can be critical about things such as (i) the tissue shape and/or structure, (ii) spectral constituents, (iii) limits on parameters, (iv) demographic or biomarker data, and (v) biophysical models of the temporal signal shapes. A general framework of NIRS imaging with prior information is presented, showing that prior information datasets could be incorporated at any step in the NIRS process, with the general workflow being: (i) data acquisition, (ii) pre-processing, (iii) forward model, (iv) inversion/reconstruction, (v) post-processing, and (vi) interpretation/diagnosis. Most of the development in NIRS has used ad hoc or empirical implementations of prior information such as pre-measured absorber or fluorophore spectra, or tissue shapes as estimated by additional imaging tools. A comprehensive analysis would examine what prior information maximizes the accuracy in recovery and value for medical diagnosis, when implemented at separate stages of the NIRS sequence. Individual applications of prior information can show increases in accuracy or improved ability to estimate biochemical features of tissue, while other approaches may not. Most beneficial inclusion of prior information has been in the inversion/reconstruction process, because it solves the mathematical intractability. However, it is not clear that this is always the most beneficial stage.

Measurements and modeling of transient blood flow perturbations induced by brief somatosensory stimulation

Proper interpretation of BOLD fMRI and other common functional imaging methods requires an understanding of neurovascular coupling. We used laser speckle-contrast optical imaging to measure blood-flow responses in rat somatosensory cortex elicited by brief (2 s) forepaw stimulation. Results show a large increase in local blood flow speed followed by an undershoot and possible late-time oscillations. The blood flow measurements were modeled using the impulse response of a simple linear network, a four-element windkessel. This model yielded excellent fits to the detailed time courses of activated regions. The four-element windkessel model thus provides a simple explanation and interpretation of the transient blood-flow response, both its initial peak and its late-time behavior.

NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation

We used Near-Infrared Spectroscopy (NIRS) to simultaneously measure brain activity in two people while they played a computer-based cooperation game side by side. Inter-brain activity coherence was calculated between the two participants. We found that the coherence between signals generated by participants' right superior frontal cortices increased during cooperation, but not during competition. Increased coherence was also associated with better cooperation performance. To our knowledge, this work represents the first use of a single NIRS instrument for simultaneous measurements of brain activity in two people. This study demonstrates the use of NIRS-based hyperscanning in studies of social interaction in a naturalistic environment.

Prefrontal Brain Activation During Emotional Processing: A Functional Near Infrared Spectroscopy Study (fNIRS)

The limbic system and especially the amygdala have been identified as key structures in emotion induction and regulation. Recently research has additionally focused on the influence of prefrontal areas on emotion processing in the limbic system and the amygdala. Results from fMRI studies indicate that the prefrontal cortex (PFC) is involved not only in emotion induction but also in emotion regulation. However, studies using fNIRS only report prefrontal brain activation during emotion induction. So far it lacks the attempt to compare emotion induction and emotion regulation with regard to prefrontal activation measured with fNIRS, to exclude the possibility that the reported prefrontal brain activation in fNIRS studies are mainly caused by automatic emotion regulation processes. Therefore this work tried to distinguish emotion induction from regulation via fNIRS of the prefrontal cortex. 20 healthy women viewed neutral pictures as a baseline condition, fearful pictures as induction condition and reappraised fearful pictures as regulation condition in randomized order. As predicted, the view-fearful condition led to higher arousal ratings than the view-neutral condition with the reappraise-fearful condition in between. For the fNIRS results the induction condition showed an activation of the bilateral PFC compared to the baseline condition (viewing neutral). The regulation condition showed an activation only of the left PFC compared to the baseline condition, although the direct comparison between induction and regulation condition revealed no significant difference in brain activation. Therefore our study underscores the results of previous fNIRS studies showing prefrontal brain activation during emotion induction and rejects the hypothesis that this prefrontal brain activation might only be a result of automatic emotion regulation processes.

Biophysical model estimation of neurovascular parameters in a rat model of healthy aging

Neuronal, vascular and metabolic factors result in a deterioration of the cerebral hemodynamic response with age. The interpretation of neuroimaging studies in the context of aging is rendered difficult due to the challenge in untangling the composite effect of these modifications. In this work we integrate multimodal optical imaging in biophysical models to investigate vascular and metabolic changes occurring in aging. Multispectral intrinsic optical imaging of an animal model of healthy aging, the LOU/c rat, is used in combination with somatosensory stimulation to study the modifications of the hemodynamic response with increasing age. Results are fitted with three macroscopic biophysical models to extract parameters, providing a phenomenological description of vascular and metabolic changes. Our results show that 1) biophysical parameters are estimable from multimodal data and 2) parameter estimates in this population change with aging.

Cerebrovascular hemodynamic correlates of aging in the Lou/c rat: a model of healthy aging

The LOU/c rat is an inbred strain considered a model of healthy aging. It exhibits a longer free disease lifespan and a low adiposity throughout life. While this animal model has been shown to maintain eating behavior and neuroendocrine, metabolic and cognitive functions with age, no study has yet investigated vascular correlates in this model of healthy aging. In the present work, multispectral optical imaging was used to investigate the hemodynamic response in the somatosensory cortex of LOU/c rats following forepaw stimulation in three age groups, 4, 24 and 40months. Results indicate reduced hemodynamic responses in the contralateral somatosensory cortex between young (4months) and older groups following stimulation. This decrease was associated with an increase in the spatial extent of activation. The ipsilateral response did not change with aging leading to decreased laterality. Estimations of the relative change in the local cerebral metabolic rate of oxygen during stimulation based on multimodal data showed no significant change with age. The exponent describing the relation between blood volume and blood flow changes, Grubb's parameter, did display a significant change with age which may suggest vessel compliance modifications. This work finds its relevance in recent findings underlying the importance of vascular changes with aging and its impact on neurodegenerative disease.

Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling

Diffuse optical imaging (DOI) allows the recovery of the hemodynamic response associated with evoked brain activity. The signal is contaminated with systemic physiological interference which occurs in the superficial layers of the head as well as in the brain tissue. The back-reflection geometry of the measurement makes the DOI signal strongly contaminated by systemic interference occurring in the superficial layers. A recent development has been the use of signals from small source-detector separation (1cm) optodes as regressors. Since those additional measurements are mainly sensitive to superficial layers in adult humans, they help in removing the systemic interference present in longer separation measurements (3 cm). Encouraged by those findings, we developed a dynamic estimation procedure to remove global interference using small optode separations and to estimate simultaneously the hemodynamic response. The algorithm was tested by recovering a simulated synthetic hemodynamic response added over baseline DOI data acquired from 6 human subjects at rest. The performance of the algorithm was quantified by the Pearson R(2) coefficient and the mean square error (MSE) between the recovered and the simulated hemodynamic responses. Our dynamic estimator was also compared with a static estimator and the traditional adaptive filtering method. We observed a significant improvement (two-tailed paired t-test, p<0.05) in both HbO and HbR recovery using our Kalman filter dynamic estimator compared to the traditional adaptive filter, the static estimator and the standard GLM technique.

Quantitative investigation of the effect of the extra-cerebral vasculature in diffuse optical imaging: a simulation study

Diffuse optical imaging (DOI) is a non invasive technique allowing the recovery of hemodynamic changes in the brain. Due to the diffusive nature of photon propagation in turbid media and the fact that cerebral tissues are located around 1.5 cm under the adult human scalp, DOI measurements are subject to partial volume errors. DOI measurements are also sensitive to large pial vessels because oxygenated and deoxygenated hemoglobin are the dominant chromophores in the near infrared window. In this study, the effect of the extra-cerebral vasculature in proximity of the sagittal sinus was investigated for its impact on DOI measurements simulated over the human adult visual cortex. Numerical Monte Carlo simulations were performed on two specific models of the human head derived from magnetic resonance imaging (MRI) scans. The first model included the extra-cerebral vasculature in which constant hemoglobin concentrations were assumed while the second did not. The screening effect of the vasculature was quantified by comparing recovered hemoglobin changes from each model for different optical arrays and regions of activation. A correction factor accounting for the difference between the recovered and the simulated hemoglobin changes was computed in each case. The results show that changes in hemoglobin concentration are better estimated when the extra-cerebral vasculature is modeled and the correction factors obtained in this case were at least 1.4-fold lower. The effect of the vasculature was also examined in a high-density diffuse optical tomography configuration. In this case, the difference between changes in hemoglobin concentration recovered with each model was reduced down to 10%.

A quantitative comparison of NIRS and fMRI across multiple cognitive tasks

Near infrared spectroscopy (NIRS) is an increasingly popular technology for studying brain function. NIRS presents several advantages relative to functional magnetic resonance imaging (fMRI), such as measurement of concentration changes in both oxygenated and deoxygenated hemoglobin, finer temporal resolution, and ease of administration, as well as disadvantages, most prominently inferior spatial resolution and decreased signal-to-noise ratio (SNR). While fMRI has become the gold standard for in vivo imaging of the human brain, in practice NIRS is a more convenient and less expensive technology than fMRI. It is therefore of interest to many researchers how NIRS compares to fMRI in studies of brain function. In the present study we scanned participants with simultaneous NIRS and fMRI on a battery of cognitive tasks, placing NIRS probes over both frontal and parietal brain regions. We performed detailed comparisons of the signals in both temporal and spatial domains. We found that NIRS signals have significantly weaker SNR, but are nonetheless often highly correlated with fMRI measurements. Both SNR and the distance between the scalp and the brain contributed to variability in the NIRS/fMRI correlations. In the spatial domain, we found that a photon path forming an ellipse between the NIRS emitter and detector correlated most strongly with the BOLD response. Taken together these findings suggest that, while NIRS can be an appropriate substitute for fMRI for studying brain activity related to cognitive tasks, care should be taken when designing studies with NIRS to ensure that: 1) the spatial resolution is adequate for answering the question of interest and 2) the design accounts for weaker SNR, especially in brain regions more distal from the scalp.