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Neurovascular coupling (NVC), or the adjustment of blood flow in response to local increases in neuronal activity is a hallmark of healthy brain function, and the physiological foundation for functional magnetic resonance imaging (fMRI). However, it remains only partly understood due to the high complexity of the structure and function of the cerebrovascular network. Here we set out to understand NVC at the network level, i.e. map cerebrovascular network reactivity to activation of neighbouring neurons within a 500×500×500 μm3 cortical volume (∼30 high-resolution 3-nL fMRI voxels). Using 3D two-photon fluorescence microscopy data, we quantified blood volume and flow changes in the brain vessels in response to spatially targeted optogenetic activation of cortical pyramidal neurons. We registered the vessels in a series of image stacks acquired before and after stimulations and applied a deep learning pipeline to segment the microvascular network from each time frame acquired. We then performed image analysis to extract the microvascular graphs, and graph analysis to identify the branch order of each vessel in the network, enabling the stratification of vessels by their branch order, designating branches 1–3 as precapillary arterioles and branches 4+ as capillaries. Forty-five percent of all vessels showed significant calibre changes; with 85 % of responses being dilations. The largest absolute CBV change was in the capillaries; the smallest, in the venules. Capillary CBV change was also the largest fraction of the total CBV change, but normalized to the baseline volume, arterioles and precapillary arterioles showed the biggest relative CBV change. From linescans along arteriole-venule microvascular paths, we measured red blood cell velocities and hematocrit, allowing for estimation of pressure and local resistance along these paths. While diameter changes following neuronal activation gradually declined along the paths; the pressure drops from arterioles to venules increased despite decreasing resistance: blood flow thus increased more than local resistance decreases would predict. By leveraging functional volumetric imaging and high throughput deep learning-based analysis, our study revealed distinct hemodynamic responses across the vessel types comprising the microvascular network. Our findings underscore the need for large, dense sampling of brain vessels for characterization of neurovascular coupling at the network level in health and disease.

The cardiac cycle induces blood volume pulsations in the cerebral microvasculature that cause subtle deformation of the surrounding tissue. These tissue deformations are highly relevant as a potential source of information on the brain's microvasculature as well as of tissue condition. Besides, cyclic brain tissue deformations may be a driving force in clearance of brain waste products. We have developed a high-field magnetic resonance imaging (MRI) technique to capture these tissue deformations with full brain coverage and sufficient signal-to-noise to derive the cardiac-induced strain tensor on a voxel by voxel basis, that could not be assessed non-invasively before. We acquired the strain tensor with 3 mm isotropic resolution in 9 subjects with repeated measurements for 8 subjects. The strain tensor yielded both positive and negative eigenvalues (principle strains), reflecting the Poison effect in tissue. The principle strain associated with expansion followed the known funnel shaped brain motion pattern pointing towards the foramen magnum. Furthermore, we evaluate two scalar quantities from the strain tensor: the volumetric strain and octahedral shear strain. These quantities showed consistent patterns between subjects, and yielded repeatable results: the peak systolic volumetric strain (relative to end-diastolic strain) was 4.19⋅10−4 ± 0.78⋅10−4 and 3.98⋅10−4 ± 0.44⋅10−4 (mean ± standard deviation for first and second measurement, respectively), and the peak octahedral shear strain was 2.16⋅10−3 ± 0.31⋅10−3 and 2.31⋅10−3 ± 0.38⋅10−3, for the first and second measurement, respectively. The volumetric strain was typically highest in the cortex and lowest in the periventricular white matter, while anisotropy was highest in the subcortical white matter and basal ganglia. This technique thus reveals new, regional information on the brain's cardiac-induced deformation characteristics, and has the potential to advance our understanding of the role of microvascular pulsations in health and disease.

Microvascular blood volume pulsations due to the cardiac and respiratory cycles induce brain tissue deformation and, as such, are considered to drive the brain’s waste clearance system. We have developed a high-field magnetic resonance imaging (MRI) technique to quantify both cardiac and respiration-induced tissue deformations, which could not be assessed noninvasively before. The technique acquires motion encoded snapshot images in which various forms of motion and confounders are entangled. First, we optimized the motion sensitivity for application in the human brain. Next, we isolated the heartbeat and respiration-related deformations, by introducing a linear model that fits the snapshot series to the recorded physiological information. As a result, we obtained maps of the physiological tissue deformation with 3mm isotropic spatial resolution. Heartbeat and respiration-induced volumetric strain were significantly different from zero in the basal ganglia (median (25–75% interquartile range): 0.85·10−3 (0.39·10−3–1.05·10−3), p ​= ​0.0008 and −0.28·10−3 (−0.41·10−3–0.06·10−3), p ​= ​0.047, respectively. Smaller volumetric strains were observed in the white matter of the centrum semi ovale (0.28·10−3 (0–0.59·10−3) and −0.06·10−3 (−0.17·10−3–0.20·10−3)), which was only significant for the heartbeat (p ​= ​0.02 and p ​= ​0.7, respectively). Furthermore, heartbeat-induced volumetric strain was about three times larger than respiration-induced volumetric strain. This technique opens a window on the driving forces of the human brain clearance system.

Displacement Encoding with Stimulated Echoes (DENSE) has recently shown potential for measuring cardiac-induced cerebral volumetric strain in the human brain. As such, it may provide a powerful tool for investigating the cerebral small vessels. However, further development and validation are necessary. This study aims, first, to validate a retrospectively-gated implementation of the DENSE method for assessing brain tissue pulsations as a physiological marker, and second, to use the acquired measurements to explore intracranial volume dynamics. We acquired repeated measurements of cerebral volumetric strain in 8 healthy subjects, and internally validated these measurements by comparing them to spinal CSF stroke volumes obtained in the same scan session.Peak volumetric strain was found to be highly repeatable between scan sessions. First/second measured peak volumetric strains were: (6.4 ​± ​1.7)x10−4/(6.7 ​± ​1.6)x10−4 for whole brain, (9.5 ​± ​2.5)x10−4/(9.6 ​± ​2.4)x10−4 for grey matter, and (4.4 ​± ​1.7)x10−4/(4.1 ​± ​0.8)x10−4 for white matter. Grey matter showed significantly higher peak strain (p ​

• We acquired in situ 3D two-photon fluorescence microscopy data in an optogenetic mouse model and applied our deep learning-based vascular segmentation and image analysis pipeline to map geometric changes across the cerebrovascular network following neuronal activation. • Following neuronal stimulation, 45 % of all vessels showed caliber changes and only 15 % of the responses were constrictions. The absolute CBV change was the largest in the capillaries and smallest in the venules. • We presented first hitherto experimentally-based profiles of resistance and pressure along brain arteriovenous paths, demonstrating U-shaped resistance and sigmoidal pressure gradients. • The flow increases were greater than local resistance decreases would predict, supporting luxurious perfusion of the activated brain region. Neurovascular coupling (NVC), or the adjustment of blood flow in response to local increases in neuronal activity is a hallmark of healthy brain function, and the physiological foundation for functional magnetic resonance imaging (fMRI). However, it remains only partly understood due to the high complexity of the structure and function of the cerebrovascular network. Here we set out to understand NVC at the network level, i.e. map cerebrovascular network reactivity to activation of neighbouring neurons within a 500×500×500 μm3 cortical volume (∼30 high-resolution 3-nL fMRI voxels). Using 3D two-photon fluorescence microscopy data, we quantified blood volume and flow changes in the brain vessels in response to spatially targeted optogenetic activation of cortical pyramidal neurons. We registered the vessels in a series of image stacks acquired before and after stimulations and applied a deep learning pipeline to segment the microvascular network from each time frame acquired. We then performed image analysis to extract the microvascular graphs, and graph analysis to identify the branch order of each vessel in the network, enabling the stratification of vessels by their branch order, designating branches 1–3 as precapillary arterioles and branches 4+ as capillaries. Forty-five percent of all vessels showed significant calibre changes; with 85 % of responses being dilations. The largest absolute CBV change was in the capillaries; the smallest, in the venules. Capillary CBV change was also the largest fraction of the total CBV change, but normalized to the baseline volume, arterioles and precapillary arterioles showed the biggest relative CBV change. From linescans along arteriole-venule microvascular paths, we measured red blood cell velocities and hematocrit, allowing for estimation of pressure and local resistance along these paths. While diameter changes following neuronal activation gradually declined along the paths; the pressure drops from arterioles to venules increased despite decreasing resistance: blood flow thus increased more than local resistance decreases would predict. By leveraging functional volumetric imaging and high throughput deep learning-based analysis, our study revealed distinct hemodynamic responses across the vessel types comprising the microvascular network. Our findings underscore the need for large, dense sampling of brain vessels for characterization of neurovascular coupling at the network level in health and disease. [ABSTRACT FROM AUTHOR]

In this review focusing primarily on the work conducted in my group at the RIKEN Brain Science Institute, I will first briefly summarize what we have achieved in mapping columnar organizations in human primary visual cortex using blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI), including ocular dominance columns, temporal frequency dependent domains, and orientation selective columns. I will then touch upon a couple of recent successful attempts in the field in mapping functional architectures in human extrastriate cortices, including human middle temporal complex and secondary and tertiary visual areas (V2 and V3), and discuss what we have learned regarding the spatial specificity of BOLD fMRI. Finally, I will offer some of my personal thoughts on how functional architectures may be organized in relation to underlying microvasculature and how such functional architectures may be experimentally explored. [ABSTRACT FROM AUTHOR]

Abstract: Micro-computed tomography (micro-CT) is an X-ray imaging technique that can produce detailed 3D images of cerebral vasculature. This paper describes the development of a novel method for using micro-CT to measure cerebral blood volume (CBV) in the mouse brain. As an application of the methodology, we test the hypotheses that differences in CBV exist over anatomical brain regions and that high energy demanding primary sensory regions of the cortex have locally elevated CBV, which may reflect a vascular specialization. CBV was measured as the percentage of tissue space occupied by a radio-opaque silicon rubber that fills the vasculature. To ensure accuracy of the CBV measurements, several innovative refinements were made to standard micro-CT specimen preparation and analysis procedures. Key features of the described method are vascular perfusion under controlled pressure, registration of the micro-CT images to an MRI anatomical brain atlas and re-scaling of micro-CT intensities to CBV units with selectable exclusion of major vessels. Histological validation of the vascular perfusion showed that the average percentage of vessels filled was 93±3%. Comparison of thirteen brain regions in nine mice revealed significant differences in CBV between regions (p <0.0001) while cortical maps showed that primary visual and auditory areas have higher CBV than primary somatosensory areas. [Copyright &y& Elsevier]

Abstract: Recently, we demonstrated that vessel geometry is a significant determinant of susceptibility-induced contrast in MRI. This is especially relevant for susceptibility-contrast enhanced MRI of tumors with their characteristically abnormal vessel morphology. In order to better understand the biophysics of this contrast mechanism, it is of interest to model how various factors, including microvessel morphology contribute to the measured MR signal, and was the primary motivation for developing a novel computer modeling approach called the Finite Perturber Method (FPM). The FPM circumvents the limitations of traditional fixed-geometry approaches, and enables us to study susceptibility-induced contrast arising from arbitrary microvascular morphologies in 3D, such as those typically observed with brain tumor angiogenesis. Here we describe this new modeling methodology and some of its applications. The excellent agreement of the FPM with theory and the extant susceptibility modeling data, coupled with its computational efficiency demonstrates its potential to transform our understanding of the factors that engender susceptibility contrast in MRI. [Copyright &y& Elsevier]

Abstract: There is a wide range of diseases and normal physiological processes that are associated with alterations of the vascular system in organs. Ex vivo imaging of large vascular networks became feasible with recent developments in microcomputed tomography (μCT). Current methods permit to visualize only limited numbers of physically excised regions of interests (ROIs) from larger samples. We developed a method based on modified vascular corrosion casting (VCC), scanning electron microscopy (SEM), and desktop and synchrotron radiation μCT (SRμCT) technologies to image vasculature at increasing levels of resolution, also referred to as hierarchical imaging. This novel approach allows nondestructive 3D visualization and quantification of large microvascular networks, while retaining a precise anatomical context for ROIs scanned at very high resolution. Scans of entire mouse brain VCCs were performed at 16-μm resolution with a desktop μCT system. Custom-made navigation software with a ROI selection tool enabled the identification of anatomical brain structures and precise placement of multiple ROIs. These were then scanned at 1.4-μm voxel size using SRμCT and a local tomography setup. A framework was developed for fast sample positioning, precise selection of ROIs, and sequential high-throughput scanning of a large numbers of brain VCCs. Despite the use of local tomography, exceptional image quality was achieved with SRμCT. This method enables qualitative and quantitative assessment of vasculature at unprecedented resolution and volume with relatively high throughput, opening new possibilities to study vessel architecture and vascular alterations in models of disease. [Copyright &y& Elsevier]

Abstract: The coupling between neurotransmitter-induced changes in neuronal activity and the resultant hemodynamic response is central to the interpretation of neuroimaging techniques. In the present study, MRI experiments showed that dopamine transporter blockers such as cocaine and dopamine releasers such as amphetamine and D1 receptor agonists induced large positive increases in relative cerebral blood volume (rCBV) that were not sensitive to nitric oxide synthase inhibition. However, D1/D5 receptor antagonism with SCH-23390 prevented or blocked the hemodynamic response without any concomitant effect on dopamine release. Dopamine D2/D3 receptor agonists, in contrast, induced negative changes in rCBV in brain regions corresponding largely to those endowed with these receptors. D1 and D5 receptor mRNAs were expressed in microvessels of responsive brain areas, while D2 and D3 receptors were not consistently associated with the microvascular bed. D3 receptors had an astroglial localization. Together, these experiments show that direct effects of dopamine upon the vasculature cannot be ignored in measuring the hemodynamic coupling associated with dopaminergic drugs. These results further suggest that this coupling is partially mediated through D1/D5 receptors on the microvasculature leading to increased rCBV and through astroglial D3 receptors leading to decreased rCBV. These data provide additional support for the role of local post-synaptic events in neurovascular coupling and emphasize that the interpretation of fMRI signals exclusively in terms of neuronal activity may be incomplete. [Copyright &y& Elsevier]

Microvascular blood volume pulsations due to the cardiac and respiratory cycles induce brain tissue deformation and, as such, are considered to drive the brain's waste clearance system. We have developed a high-field magnetic resonance imaging (MRI) technique to quantify both cardiac and respiration-induced tissue deformations, which could not be assessed noninvasively before. The technique acquires motion encoded snapshot images in which various forms of motion and confounders are entangled. First, we optimized the motion sensitivity for application in the human brain. Next, we isolated the heartbeat and respiration-related deformations, by introducing a linear model that fits the snapshot series to the recorded physiological information. As a result, we obtained maps of the physiological tissue deformation with 3mm isotropic spatial resolution. Heartbeat and respiration-induced volumetric strain were significantly different from zero in the basal ganglia (median (25–75% interquartile range): 0.85·10−3 (0.39·10−3–1.05·10−3), p ​= ​0.0008 and −0.28·10−3 (−0.41·10−3–0.06·10−3), p ​= ​0.047, respectively. Smaller volumetric strains were observed in the white matter of the centrum semi ovale (0.28·10−3 (0–0.59·10−3) and −0.06·10−3 (−0.17·10−3–0.20·10−3)), which was only significant for the heartbeat (p ​= ​0.02 and p ​= ​0.7, respectively). Furthermore, heartbeat-induced volumetric strain was about three times larger than respiration-induced volumetric strain. This technique opens a window on the driving forces of the human brain clearance system. • Cardiac and respiration-induced brain deformations simultaneously measured with MRI. • Single-shot 2D DENSE is suitable to unravel cardiac and respiration induced brain tissue strain. • Tissue deformation of the brain is mainly driven by the cardiac cycle. • Inspiration induces tissue compression, probably due to venous outflow. [ABSTRACT FROM AUTHOR]

Displacement Encoding with Stimulated Echoes (DENSE) has recently shown potential for measuring cardiac-induced cerebral volumetric strain in the human brain. As such, it may provide a powerful tool for investigating the cerebral small vessels. However, further development and validation are necessary. This study aims, first, to validate a retrospectively-gated implementation of the DENSE method for assessing brain tissue pulsations as a physiological marker, and second, to use the acquired measurements to explore intracranial volume dynamics. We acquired repeated measurements of cerebral volumetric strain in 8 healthy subjects, and internally validated these measurements by comparing them to spinal CSF stroke volumes obtained in the same scan session. Peak volumetric strain was found to be highly repeatable between scan sessions. First/second measured peak volumetric strains were: (6.4 ​± ​1.7)x10−4/(6.7 ​± ​1.6)x10−4 for whole brain, (9.5 ​± ​2.5)x10−4/(9.6 ​± ​2.4)x10−4 for grey matter, and (4.4 ​± ​1.7)x10−4/(4.1 ​± ​0.8)x10−4 for white matter. Grey matter showed significantly higher peak strain (p ​< ​0.001) and earlier time-to-peak strain (p ​< ​0.02) than white matter. An approximately linear relationship was found between CSF and brain tissue volume pulsations over the cardiac cycle (mean slope and R2 of 0.88 ​± ​0.23 and 0.89 ​± ​0.07, respectively). The close similarity between CSF and brain tissue volume pulsations implies limited contributions from large intracranial vessel pulsations, providing further evidence for venous compression as an additional mechanism for maintaining stable intracranial pressures over the cardiac cycle. Cerebral pulsatility showed consistent inter-subject peak values in healthy subjects, and was strongly correlated to CSF stroke volumes. These results strengthen the potential of brain tissue volumetric strain as a means for investigating the intracranial dynamics of the ageing brain in normal or diseased states. Image 1 • Retrospectively-gated DENSE suitable for acquiring whole brain tissue displacement measurements over the entire cardiac-cycle. • Peak cerebral microvascular blood pulsations has high repeatability in healthy subjects. • Grey matter has a significantly higher peak volumetric strain, and earlier time-to-peak than white matter. • CSF and brain tissue cardiac-induced volume changes are strongly correlated. • Limited contribution of the large intracranial, extracerebral vessels to spinal CSF stroke volumes. [ABSTRACT FROM AUTHOR]