Baseline oxygen consumption decreases with cortical depth.

The cerebral cortex is organized in cortical layers that differ in their cellular density, composition, and wiring. Cortical laminar architecture is also readily revealed by staining for cytochrome oxidase-the last enzyme in the respiratory electron transport chain located in the inner mitochondrial membrane. It has been hypothesized that a high-density band of cytochrome oxidase in cortical layer IV reflects higher oxygen consumption under baseline (unstimulated) conditions. Here, we tested the above hypothesis using direct measurements of the partial pressure of O2 (pO2) in cortical tissue by means of 2-photon phosphorescence lifetime microscopy (2PLM). We revisited our previously developed method for extraction of the cerebral metabolic rate of O2 (CMRO2) based on 2-photon pO2 measurements around diving arterioles and applied this method to estimate baseline CMRO2 in awake mice across cortical layers. To our surprise, our results revealed a decrease in baseline CMRO2 from layer I to layer IV. This decrease of CMRO2 with cortical depth was paralleled by an increase in tissue oxygenation. Higher baseline oxygenation and cytochrome density in layer IV may serve as an O2 reserve during surges of neuronal activity or certain metabolically active brain states rather than reflecting baseline energy needs. Our study provides to our knowledge the first quantification of microscopically resolved CMRO2 across cortical layers as a step towards better understanding of brain energy metabolism.

Optical coherence tomography-based design for a real-time motion corrected scanning microscope.

While two-photon fluorescence microscopy is a powerful platform for the study of functional dynamics in living cells and tissues, the bulk motion inherent to these applications causes distortions. We have designed a motion tracking module based on spectral domain optical coherence tomography which compliments a laser scanning two-photon microscope with real-time corrective feedback. The module can be added to fluorescent imaging microscopes using a single dichroic and without additional contrast agents. We demonstrate that the system can track lateral displacements as large as 10 µm at 5 Hz with latency under 14 ms and propose a scheme to extend the system to 3D correction with the addition of a remote focusing module. We also propose several ways to improve the module's performance by reducing the feedback latency. We anticipate that this design can be adapted to other imaging modalities, enabling the study of samples subject to motion artifacts at higher resolution.

Rho-Kinase Inhibition Improves the Outcome of Focal Subcortical White Matter Lesions.

BACKGROUND: Subcortical white matter lesions are exceedingly common in cerebral small vessel disease and lead to significant cumulative disability without an available treatment. Here, we tested a rho-kinase inhibitor on functional recovery after focal white matter injury. METHODS: A focal corpus callosum lesion was induced by stereotactic injection of N5-(1-iminoethyl)-L-ornithine in mice. Fasudil (10 mg/kg) or vehicle was administered daily for 2 weeks, starting one day after lesion induction. Resting-state functional connectivity and grid walk performance were studied longitudinally, and lesion volumes were determined at one month. RESULTS: Resting-state interhemispheric functional connectivity significantly recovered between days 1 and 14 in the fasudil group (P<0.001), despite worse initial connectivity loss than vehicle before treatment onset. Grid walk test revealed an increased number of foot faults in the vehicle group compared with baseline, which persisted for at least 4 weeks. In contrast, the fasudil arm did not show an increase in foot faults and had smaller lesions at 4 weeks. Immunohistochemical examination of reactive astrocytosis, synaptic density, and mature oligodendrocytes did not reveal a significant difference between treatment arms. CONCLUSIONS: These data show that delayed fasudil posttreatment improves functional outcomes after a focal subcortical white matter lesion in mice. Future work will aim to elucidate the mechanisms.

A novel algorithm for multiplicative speckle noise reduction in ex vivo human brain OCT images.

Optical coherence tomography (OCT) images of ex vivo human brain tissue are corrupted by multiplicative speckle noise that degrades the contrast to noise ratio (CNR) of microstructural compartments. This work proposes a novel algorithm to reduce noise corruption in OCT images that minimizes the penalized negative log likelihood of gamma distributed speckle noise. The proposed method is formulated as a majorize-minimize problem that reduces to solving an iterative regularized least squares optimization. We demonstrate the usefulness of the proposed method by removing speckle in simulated data, phantom data and real OCT images of human brain tissue. We compare the proposed method with state of the art filtering and non-local means based denoising methods. We demonstrate that our approach removes speckle accurately, improves CNR between different tissue types and better preserves small features and edges in human brain tissue.

Focal Subcortical White Matter Lesions Disrupt Resting State Cortical Interhemispheric Functional Connectivity in Mice.

The corpus callosum is the largest white matter tract and critical for interhemispheric connectivity. Unfortunately, neurocognitive deficits after experimental white matter lesions are subtle and variable, limiting their translational utility. We examined resting state functional connectivity (RSFC) as a surrogate after a focal lesion in the lateral corpus callosum induced by stereotaxic injection of L-NIO in mice. RSFC was performed via optical intrinsic signal imaging through intact skull before and on days 1 and 14 after injection, using interhemispheric homotopic and seed-based temporal correlation maps. We measured the lesion volumes at 1 month in the same cohort. L-NIO induced focal lesions in the corpus callosum. Interhemispheric homotopic connectivity decreased by up to 50% 24 h after L-NIO, partially sparing the visual cortex. All seeds showed loss of connectivity to the contralateral hemisphere. Moreover, ipsilesional motor and visual cortices lost connectivity within the same hemisphere. Sham-operated mice did not show any lesion or connectivity changes. RSFC imaging reliably detects acute disruption of long interhemispheric and intrahemispheric connectivity after a corpus callosum lesion in mice. This noninvasive method can be a functional surrogate to complement neurocognitive testing in both therapeutic and recovery studies after white matter injury.

Mathematical synthesis of the cortical circulation for the whole mouse brain-part II: Microcirculatory closure.

Recent advancements in multiphoton imaging and vascular reconstruction algorithms have increased the amount of data on cerebrovascular circulation for statistical analysis and hemodynamic simulations. Experimental observations offer fundamental insights into capillary network topology but mainly within a narrow field of view typically spanning a small fraction of the cortical surface (less than 2%). In contrast, larger-resolution imaging modalities, such as computed tomography (CT) or magnetic resonance imaging (MRI), have whole-brain coverage but capture only larger blood vessels, overlooking the microscopic capillary bed. To integrate data acquired at multiple length scales with different neuroimaging modalities and to reconcile brain-wide macroscale information with microscale multiphoton data, we developed a method for synthesizing hemodynamically equivalent vascular networks for the entire cerebral circulation. This computational approach is intended to aid in the quantification of patterns of cerebral blood flow and metabolism for the entire brain. In part I, we described the mathematical framework for image-guided generation of synthetic vascular networks covering the large cerebral arteries from the circle of Willis through the pial surface network leading back to the venous sinuses. Here in part II, we introduce novel procedures for creating microcirculatory closure that mimics a realistic capillary bed. We demonstrate our capability to synthesize synthetic vascular networks whose morphometrics match empirical network graphs from three independent state-of-the-art imaging laboratories using different image acquisition and reconstruction protocols. We also successfully synthesized twelve vascular networks of a complete mouse brain hemisphere suitable for performing whole-brain blood flow simulations. Synthetic arterial and venous networks with microvascular closure allow whole-brain hemodynamic predictions. Simulations across all length scales will potentially illuminate organ-wide supply and metabolic functions that are inaccessible to models reconstructed from image data with limited spatial coverage.

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.

Imaging localized fast optical signals of neural activation with optical coherence tomography in awake mice.

We report optical coherence tomography (OCT) imaging of localized fast optical signals (FOSs) arising from whisker stimulation in awake mice. The activated voxels were identified by fitting the OCT intensity signal time course with a response function over a time scale of a few hundred milliseconds after the whisker stimulation. The significantly activated voxels were shown to be localized to the expected brain region for whisker stimulation. The ability to detect functional stimulus-evoked, depth-resolved FOS with intrinsic contrast from the cortex provides a new tool for neural activity studies.

Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis.

For the robust estimation of evoked brain activity from functional Near-Infrared Spectroscopy (fNIRS) signals, it is crucial to reduce nuisance signals from systemic physiology and motion. The current best practice incorporates short-separation (SS) fNIRS measurements as regressors in a General Linear Model (GLM). However, several challenging signal characteristics such as non-instantaneous and non-constant coupling are not yet addressed by this approach and additional auxiliary signals are not optimally exploited. We have recently introduced a new methodological framework for the unsupervised multivariate analysis of fNIRS signals using Blind Source Separation (BSS) methods. Building onto the framework, in this manuscript we show how to incorporate the advantages of regularized temporally embedded Canonical Correlation Analysis (tCCA) into the supervised GLM. This approach allows flexible integration of any number of auxiliary modalities and signals. We provide guidance for the selection of optimal parameters and auxiliary signals for the proposed GLM extension. Its performance in the recovery of evoked HRFs is then evaluated using both simulated ground truth data and real experimental data and compared with the GLM with short-separation regression. Our results show that the GLM with tCCA significantly improves upon the current best practice, yielding significantly better results across all applied metrics: Correlation (HbO max. +45%), Root Mean Squared Error (HbO max. -55%), F-Score (HbO up to 3.25-fold) and p-value as well as power spectral density of the noise floor. The proposed method can be incorporated into the GLM in an easily applicable way that flexibly combines any available auxiliary signals into optimal nuisance regressors. This work has potential significance both for conventional neuroscientific fNIRS experiments as well as for emerging applications of fNIRS in everyday environments, medicine and BCI, where high Contrast to Noise Ratio is of importance for single trial analysis.

Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain.

In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 â€‹mm or smaller but degrades at 2 â€‹mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques.

Comparing the fundamental imaging depth limit of two-photon, three-photon, and non-degenerate two-photon microscopy.

We have systematically characterized the degradation of imaging quality with depth in deep brain multi-photon microscopy, utilizing our recently developed numerical model that computes wave propagation in scattering media. The signal-to-background ratio (SBR) and the resolution determined by the width of the point spread function are obtained as functions of depth. We compare the imaging quality of two-photon (2PM), three-photon (3PM), and non-degenerate two-photon microscopy (ND-2PM) for mouse brain imaging. We show that the imaging depth of 2PM and ND-2PM are fundamentally limited by the SBR, while the SBR remains approximately invariant with imaging depth for 3PM. Instead, the imaging depth of 3PM is limited by the degradation of the resolution, if there is sufficient laser power to maintain the signal level at large depth. The roles of the concentration of dye molecules, the numerical aperture of the input light, the anisotropy factor g, noise level, input laser power, and the effect of temporal broadening are also discussed.

Dependence of the MR signal on the magnetic susceptibility of blood studied with models based on real microvascular networks.

PURPOSE: The primary goal of this study was to estimate the value of ß , the exponent in the power law relating changes of the transverse relaxation rate and intra-extravascular local magnetic susceptibility differences as ΔR2∗∝(Δχ)ß . The secondary objective was to evaluate any differences that might exist in the value of ß obtained using a deoxyhemoglobin-weighted Δχ distribution versus a constant Δχ distribution assumed in earlier computations. The third objective was to estimate the value of ß that is relevant for methods based on susceptibility contrast agents with a concentration of Δχ higher than that used for BOLD fMRI calculations. METHODS: Our recently developed model of real microvascular anatomical networks is used to extend the original simplified Monte-Carlo simulations to compute ß from the first principles. RESULTS: Our results show that ß=1 for most BOLD fMRI measurements of real vascular networks, as opposed to earlier predictions of ß=1 .5 using uniform Δχ distributions. For perfusion or fMRI methods based on contrast agents, which generate larger values for Δχ , ß=1 for B0≤ 9.4 T, whereas at 14 T ß can drop below 1 and the variation across subjects is large, indicating that a lower concentration of contrast agent with a lower value of Δχ is desired for experiments at high B0 . CONCLUSION: These results improve our understanding of the relationship between R2* and the underlying microvascular properties. The findings will help to infer the cerebral metabolic rate of oxygen and cerebral blood volume from BOLD and perfusion MRI, respectively.

Efficient non-degenerate two-photon excitation for fluorescence microscopy.

Non-degenerate two-photon excitation (ND-TPE) has been explored in two-photon excitation microscopy. However, a systematic study of the efficiency of ND-TPE to guide the selection of fluorophore excitation wavelengths is missing. We measured the relative non-degenerate two-photon absorption cross-section (ND-TPACS) of several commonly used fluorophores (two fluorescent proteins and three small-molecule dyes) and generated 2-dimensional ND-TPACS spectra. We observed that the shape of a ND-TPACS spectrum follows that of the corresponding degenerate two-photon absorption cross-section (D-TPACS) spectrum, but is higher in magnitude. We found that the observed enhancements are higher than theoretical predictions.

Development of a beam propagation method to simulate the point spread function degradation in scattering media.

Scattering is one of the main issues that limit the imaging depth in deep tissue optical imaging. To characterize the role of scattering, we have developed a forward model based on the beam propagation method and established the link between the macroscopic optical properties of the media and the statistical parameters of the phase masks applied to the wavefront. Using this model, we have analyzed the degradation of the point-spread function of the illumination beam in the transition regime from ballistic to diffusive light transport. Our method provides a wave-optic simulation toolkit to analyze the effects of scattering on image quality degradation in scanning microscopy. Our open-source implementation is available at https://github.com/BUNPC/Beam-Propagation-Method.

as-PSOCT: Volumetric microscopic imaging of human brain architecture and connectivity.

Polarization sensitive optical coherence tomography (PSOCT) with serial sectioning has enabled the investigation of 3D structures in mouse and human brain tissue samples. By using intrinsic optical properties of back-scattering and birefringence, PSOCT reliably images cytoarchitecture, myeloarchitecture and fiber orientations. In this study, we developed a fully automatic serial sectioning polarization sensitive optical coherence tomography (as-PSOCT) system to enable volumetric reconstruction of human brain samples with unprecedented sample size and resolution. The 3.5 µm in-plane resolution and 50 µm through-plane voxel size allow inspection of cortical layers that are a single-cell in width, as well as small crossing fibers. We show the abilities of as-PSOCT in quantifying layer thicknesses of the cerebellar cortex and creating microscopic tractography of intricate fiber networks in the subcortical nuclei and internal capsule regions, all based on volumetric reconstructions. as-PSOCT provides a viable tool for studying quantitative cytoarchitecture and myeloarchitecture and mapping connectivity with microscopic resolution in the human brain.

Time domain diffuse correlation spectroscopy: modeling the effects of laser coherence length and instrument response function.

Diffuse correlation spectroscopy (DCS) is an optical technique that non-invasively quantifies an index of blood flow (BFi) by measuring the temporal autocorrelation function of the intensity fluctuations of light diffusely remitted from the tissue. Traditional DCS measurements use continuous wave (CW) lasers with coherence lengths longer than the photon path lengths in the sample to ensure that the diffusely remitted light is coherent and generates a speckle pattern. Recently, we proposed time domain DCS (TD-DCS) to allow measurements of the speckle fluctuations for specific path lengths of light through the tissue, which has the distinct advantage of permitting an analysis of selected long path lengths of light to improve the depth sensitivity of the measurement. However, compared to CW-DCS, factors including the instrument response function (IRF), the detection gate width, and the finite coherence length need to be considered in the model analysis of the experimental data. Here we present a TD-DCS model describing how the intensity autocorrelation functions measured for different path lengths of light depend on the coherence length, pulse width of the laser, detection gate width, IRF, BFi, and optical properties of the scattering sample. Predictions of the model are compared with experimental results using a homogeneous liquid phantom sample that mimics human tissue optical properties. The BFis obtained from the TD-DCS model for different path lengths of light agree with the BFi obtained from CW-DCS measurements, while the standard simplified model underestimates the BFi by a factor of ∼2. This Letter establishes the theoretical foundation of the TD-DCS technique and provides guidance for future BFi measurements in tissue.

Magnetic resonance fingerprinting based on realistic vasculature in mice.

Magnetic resonance fingerprinting (MRF) was recently proposed as a novel strategy for MR data acquisition and analysis. A variant of MRF called vascular MRF (vMRF) followed, that extracted maps of three parameters of physiological importance: cerebral oxygen saturation (SatO2), mean vessel radius and cerebral blood volume (CBV). However, this estimation was based on idealized 2-dimensional simulations of vascular networks using random cylinders and the empirical Bloch equations convolved with a diffusion kernel. Here we focus on studying the vascular MR fingerprint using real mouse angiograms and physiological values as the substrate for the MR simulations. The MR signal is calculated ab initio with a Monte Carlo approximation, by tracking the accumulated phase from a large number of protons diffusing within the angiogram. We first study the identifiability of parameters in simulations, showing that parameters are fully estimable at realistically high signal-to-noise ratios (SNR) when the same angiogram is used for dictionary generation and parameter estimation, but that large biases in the estimates persist when the angiograms are different. Despite these biases, simulations show that differences in parameters remain estimable. We then applied this methodology to data acquired using the GESFIDE sequence with SPIONs injected into 9 young wild type and 9 old atherosclerotic mice. Both the pre injection signal and the ratio of post-to-pre injection signals were modeled, using 5-dimensional dictionaries. The vMRF methodology extracted significant differences in SatO2, mean vessel radius and CBV between the two groups, consistent across brain regions and dictionaries. Further validation work is essential before vMRF can gain wider application.

Model-based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach.

OBJECTIVE: In vivo imaging of the microcirculation and network-oriented modeling have emerged as powerful means of studying microvascular function and understanding its physiological significance. Network-oriented modeling may provide the means of summarizing vast amounts of data produced by high-throughput imaging techniques in terms of key, physiological indices. To estimate such indices with sufficient certainty, however, network-oriented analysis must be robust to the inevitable presence of uncertainty due to measurement errors as well as model errors. METHODS: We propose the Bayesian probabilistic data analysis framework as a means of integrating experimental measurements and network model simulations into a combined and statistically coherent analysis. The framework naturally handles noisy measurements and provides posterior distributions of model parameters as well as physiological indices associated with uncertainty. RESULTS: We applied the analysis framework to experimental data from three rat mesentery networks and one mouse brain cortex network. We inferred distributions for more than 500 unknown pressure and hematocrit boundary conditions. Model predictions were consistent with previous analyses, and remained robust when measurements were omitted from model calibration. CONCLUSION: Our Bayesian probabilistic approach may be suitable for optimizing data acquisition and for analyzing and reporting large data sets acquired as part of microvascular imaging studies.

Capillary red blood cell velocimetry by phase-resolved optical coherence tomography.

We present a phase-resolved optical coherence tomography (OCT) method to extend Doppler OCT for the accurate measurement of the red blood cell (RBC) velocity in cerebral capillaries. OCT data were acquired with an M-mode scanning strategy (repeated A-scans) to account for the single-file passage of RBCs in a capillary, which were then high-pass filtered to remove the stationary component of the signal to ensure an accurate measurement of phase shift of flowing RBCs. The angular frequency of the signal from flowing RBCs was then quantified from the dynamic component of the signal and used to calculate the axial speed of flowing RBCs in capillaries. We validated our measurement by RBC passage velocimetry using the signal magnitude of the same OCT time series data.

Brain Tissue PO2 Measurement During Normoxia and Hypoxia Using Two-Photon Phosphorescence Lifetime Microscopy.

Key to the understanding of the principles of physiological and structural acclimatization to changes in the balance between energy supply (represented by substrate and oxygen delivery, and mitochondrial oxidative phosphorylation) and energy demand (initiated by neuronal activity) is to determine the controlling variables, how they are sensed and the mechanisms initiated to maintain the balance. The mammalian brain depends completely on continuous delivery of oxygen to maintain its function. We hypothesized that tissue oxygen is the primary sensed variable. In this study two-photon phosphorescence lifetime microscopy (2PLM) was used to determine and define the tissue oxygen tension field within the cerebral cortex of mice to a cortical depth of between 200-250 µm under normoxia and acute hypoxia (FiO2 = 0.10). High-resolution images can provide quantitative distributions of oxygen and intercapillary oxygen gradients. The data are best appreciated by quantifying the distribution histogram that can then be used for analysis. For example, in the brain cortex of a mouse, at a depth of 200 µm, tissue oxygen tension was mapped and the distribution histogram was compared under normoxic and mild hypoxic conditions. This powerful method can provide for the first time a description of the delivery and availability of brain oxygen in vivo.