Choosing a camera and optimizing system parameters for speckle contrast optical spectroscopy

Speckle contrast optical spectroscopy (SCOS) is an emerging camera-based technique that can measure human cerebral blood flow (CBF) with high signal-to-noise ratio (SNR). At low photon flux levels typically encountered in human CBF measurements, camera noise and nonidealities could significantly impact SCOS measurement SNR and accuracy. Thus, a guide for characterizing, selecting, and optimizing a camera for SCOS measurements is crucial for the development of next-generation optical devices for monitoring human CBF and brain function. Here, we provide such a guide and illustrate it by evaluating three commercially available complementary metal-oxide-semiconductor cameras, considering a variety of factors including linearity, read noise, and quantization distortion. We show that some cameras that are well-suited for general intensity imaging could be challenged in accurately quantifying spatial contrast for SCOS. We then determine the optimal operating parameters for the preferred camera among the three and demonstrate measurement of human CBF with this selected low-cost camera. This work establishes a guideline for characterizing and selecting cameras as well as for determining optimal parameters for SCOS systems.

Enhanced Multiscale Human Brain Imaging by Semi-supervised Digital Staining and Serial Sectioning Optical Coherence Tomography

A major challenge in neuroscience is to visualize the structure of the human brain at different scales. Traditional histology reveals micro- and meso-scale brain features, but suffers from staining variability, tissue damage and distortion that impedes accurate 3D reconstructions. Here, we present a new 3D imaging framework that combines serial sectioning optical coherence tomography (S-OCT) with a deep-learning digital staining (DS) model. We develop a novel semi-supervised learning technique to facilitate DS model training on weakly paired images. The DS model performs translation from S-OCT to Gallyas silver staining. We demonstrate DS on various human cerebral cortex samples with consistent staining quality. Additionally, we show that DS enhances contrast across cortical layer boundaries. Furthermore, we showcase geometry-preserving 3D DS on cubic-centimeter tissue blocks and visualization of meso-scale vessel networks in the white matter. We believe that our technique offers the potential for high-throughput, multiscale imaging of brain tissues and may facilitate studies of brain structures.

Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior

Neural population dynamics relevant to behavior vary over multiple spatial and temporal scales across three-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice, enabling the investigation of cell-type- and neurotransmitter-specific signals over arbitrary 3D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum, revealing distinct, modality-specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and the spatial localization of behavioral function across large circuits.

Widefield in vivo imaging system with two fluorescence and two reflectance channels, a single sCMOS detector, and shielded illumination

SIGNIFICANCE

Widefield microscopy of the entire dorsal part of mouse cerebral cortex enables large-scale (mesoscopic) imaging of neuronal activity with fluorescent indicators as well as hemodynamics via oxy- and deoxyhemoglobin absorption. Versatile and cost-effective imaging systems are needed for large-scale, color-multiplexed imaging of multiple fluorescent and intrinsic contrasts.

AIM

Develop a system for mesoscopic imaging of two fluorescent and two reflectance channels.

APPROACH

Excitation of red and green fluorescence is achieved through epi-illumination. Hemoglobin absorption imaging is achieved using 525- and 625nm LEDs positioned around the objective lens. An aluminum hemisphere placed between objective and cranial window provides diffuse illumination of the brain. Signals are recorded sequentially by a single sCMOS detector.

RESULTS

We demonstrate performance of our imaging system by recording large-scale spontaneous and stimulus-evoked neuronal, cholinergic, and hemodynamic activity in awake head-fixed mice with a curved crystal skull window expressing the red calcium indicator jRGECO1a and the green acetylcholine sensor GRABACh3.0 . Shielding of illumination light through the aluminum hemisphere enables concurrent recording of pupil diameter changes.

CONCLUSIONS

Our widefield microscope design with single camera can be used to acquire multiple aspects of brain physiology and is compatible with behavioral readouts of pupil diameter.

Dynamic light scattering and laser speckle contrast imaging of the brain: theory of the spatial and temporal statistics of speckle pattern evolution

Dynamic light scattering (DLS) and laser speckle contrast imaging (LSCI) are closely related techniques that exploit the statistics of speckle patterns, which can be utilized to measure cerebral blood flow (CBF). Conventionally, the temporal speckle intensity auto-correlation function g 2 t ( τ ) is calculated in DLS, while the spatial speckle contrast Ks is calculated in LSCI measurements. Due to the rapid development of CMOS detection technology with increased camera frame rates while still maintaining a large number of pixels, the ensemble or spatial average of g 2 s ( τ ) as well as the temporal contrast Kt can be easily calculated and utilized to quantify CBF. Although many models have been established, a proper summary is still lacking to fully characterize DLS and LSCI measurements for spatial and temporal statistics, laser coherence properties, various motion types, etc. As a result, there are many instances where theoretical models are misused. For instance, mathematical formulas derived in the diffusive regime or for ergodic systems are sometimes applied to small animal brain measurements, e.g., mice brains, where the assumptions are not valid. Therefore, we aim to provide a review of the speckle theory for both DLS and LSCI measurements with detailed derivations from first principles, taking into account non-ergodicity, spatial and temporal statistics of speckles, scatterer motion types, and laser coherence properties. From these calculations, we elaborate on the differences between spatial and temporal averaging for DLS and LSCI measurements that are typically ignored but can result in inaccurate measurements of blood flow, particularly the spatially varying nature of the static component in g 2 t ( τ ) and Kt. We also obtained g 2 s ( τ ) maps in in vivo mouse brain measurements using high frame rate CMOS cameras which have not been demonstrated before, and compared with g 2 t ( τ ) and Ks,t. This work provides a useful guide for choosing the correct model to analyze spatial and temporal speckle statistics in in-vivo DLS and LSCI measurements.

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.

fNIRS Dataset During Complex Scene Analysis

When analyzing complex scenes, humans often focus their attention on an object at a particular spatial location. The ability to decode the attended spatial location would facilitate brain computer interfaces for complex scene analysis (CSA). Here, we investigated capability of functional near-infrared spectroscopy (fNIRS) to decode audio-visual spatial attention in the presence of competing stimuli from multiple locations. We targeted dorsal frontoparietal network including frontal eye field (FEF) and intra-parietal sulcus (IPS) as well as superior temporal gyrus/planum temporal (STG/PT). They all were shown in previous functional magnetic resonance imaging (fMRI) studies to be activated by auditory, visual, or audio-visual spatial tasks. To date, fNIRS has not been applied to decode auditory and visual-spatial attention during CSA, and thus, no such dataset exists yet. This report provides an open-access fNIRS dataset that can be used to develop, test, and compare machine learning algorithms for classifying attended locations based on the fNIRS signals on a single trial basis.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

Significance

The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique.

Aim

We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.

Approach

Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy.

Results

Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow.

Conclusion

We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

Multi-Scale Label-Free Human Brain Imaging with Integrated Serial Sectioning Polarization Sensitive Optical Coherence Tomography and Two-Photon Microscopy

The study of aging and neurodegenerative processes in the human brain requires a comprehensive understanding of cytoarchitectonic, myeloarchitectonic, and vascular structures. Recent computational advances have enabled volumetric reconstruction of the human brain using thousands of stained slices, however, tissue distortions and loss resulting from standard histological processing have hindered deformation-free reconstruction. Here, the authors describe an integrated serial sectioning polarization-sensitive optical coherence tomography (PSOCT) and two photon microscopy (2PM) system to provide label-free multi-contrast imaging of intact brain structures, including scattering, birefringence, and autofluorescence of human brain tissue. The authors demonstrate high-throughput reconstruction of 4 × 4 × 2cm3 sample blocks and simple registration between PSOCT and 2PM images that enable comprehensive analysis of myelin content, vascular structure, and cellular information. The high-resolution 2PM images provide microscopic validation and enrichment of the cellular information provided by the PSOCT optical properties on the same sample, revealing the densely packed fibers, capillaries, and lipofuscin-filled cell bodies in the cortex and white matter. It is  shown that the imaging system enables quantitative characterization of various pathological features in aging process, including myelin degradation, lipofuscin accumulation, and microvascular changes, which opens up numerous opportunities in the study of neurodegenerative diseases in the future.

Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior

Neural population dynamics relevant for behavior vary over multiple spatial and temporal scales across 3-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array and imaging approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice. We developed a semi-automated micro-CT based strategy to precisely localize positions of each optical fiber. This highly-customizable approach enables investigation of multi-scale spatial and temporal patterns of cell-type and neurotransmitter specific signals over arbitrary 3-D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum volume which revealed distinct, modality specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics through our fiber arrays enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and spatial localization of behavioral function across large circuits.

Multiscale label-free imaging of myelin in human brain tissue with polarization-sensitive optical coherence tomography and birefringence microscopy

The combination of polarization-sensitive optical coherence tomography (PS-OCT) and birefringence microscopy (BRM) enables multiscale assessment of myelinated axons in postmortem brain tissue, and these tools are promising for the study of brain connectivity and organization. We demonstrate label-free imaging of myelin structure across the mesoscopic and microscopic spatial scales by performing serial-sectioning PS-OCT of a block of human brain tissue and periodically sampling thin sections for high-resolution imaging with BRM. In co-registered birefringence parameter maps, we observe good correspondence and demonstrate that BRM enables detailed validation of myelin (hence, axonal) organization, thus complementing the volumetric information content of PS-OCT.

Optimizing the precision of laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is a rapidly developing technology broadly applied for the full-field characterization of tissue perfusion. Over the recent years, significant advancements have been made in interpreting LSCI measurements and improving the technique's accuracy. On the other hand, the method's precision has yet to be studied in detail, despite being as important as accuracy for many biomedical applications. Here we combine simulation, theory and animal experiments to systematically evaluate and re-analyze the role of key factors defining LSCI precision-speckle-to-pixel size ratio, polarisation, exposure time and camera-related noise. We show that contrary to the established assumptions, smaller speckle size and shorter exposure time can improve the precision, while the camera choice is less critical and does not affect the signal-to-noise ratio significantly.

B - 61 Increased Cortical Efficiency in the Absence of Behavioral Improvement on Working Memory Task Revealed by Functional Near-Infrared Spectroscopy

OBJECTIVE

Functional near-infrared spectroscopy (fNIRS) is a non-invasive functional neuroimaging method that indirectly measures cortical activation via task-related changes in oxygenated hemoglobin (HbO). We used fNIRS during a working memory task to assess learning effect over time by assessing brain activity (fNIRS signal) and task performance. We hypothesized that in later blocks of the task, learning (better accuracy) would be correlated to less increase in HbO in prefrontal regions, indicating improved cognitive efficiency.

METHOD

Eighteen healthy adults [mean age = 24.9 (SD = 4.2); 14 female] engaged in 8 blocks of serial-3 subtraction for 30 seconds each followed by 20 seconds of rest. fNIRS data were collected in 8 cortical regions of interest (ROI) broadly covering the frontal lobe. fNIRS signal in each ROI and task-performance data were compared for the first 4 and last 4 blocks to examine learning.

RESULTS

fNIRS signal was significantly greater for the first 4 than last 4 blocks (z = -2.1, p < 0.05) in only the right dorsolateral prefrontal cortex ROI. No learning effects appeared for any task-performance variables.

CONCLUSIONS

These results indicate a dissociation between brain activity and task performance during a working memory task in healthy adults. There was less activity in the right dorsolateral prefrontal cortex during later than earlier trials, indicating an increase in this region's efficiency, without a change in task performance. The results suggest that fNIRS may be sensitive to change in brain activity before it appears clinically, which may be useful in studying people with conditions such as preclinical Alzheimer's disease, and in assessing subtle effects of interventions.

A cellular resolution atlas of Broca's area

Brain cells are arranged in laminar, nuclear, or columnar structures, spanning a range of scales. Here, we construct a reliable cell census in the frontal lobe of human cerebral cortex at micrometer resolution in a magnetic resonance imaging (MRI)-referenced system using innovative imaging and analysis methodologies. MRI establishes a macroscopic reference coordinate system of laminar and cytoarchitectural boundaries. Cell counting is obtained with a digital stereological approach on the 3D reconstruction at cellular resolution from a custom-made inverted confocal light-sheet fluorescence microscope (LSFM). Mesoscale optical coherence tomography enables the registration of the distorted histological cell typing obtained with LSFM to the MRI-based atlas coordinate system. The outcome is an integrated high-resolution cellular census of Broca's area in a human postmortem specimen, within a whole-brain reference space atlas.

Measurements of slow tissue dynamics with short-separation speckle contrast optical spectroscopy

Laser speckle contrast imaging (LSCI) measures 2D maps of cerebral blood flow (CBF) in small animal brains such as mice. The contrast measured in LSCI also includes the static and slow-varying components that contain information about brain tissue dynamics. But these components are less studied as compared to the fast dynamics of CBF. In traditional wide-field LSCI, the contrast measured in the tissue is largely contaminated by neighboring blood vessels, which reduces the sensitivity to these static and slow components. Our goal is to enhance the sensitivity of the contrast to static and slow tissue dynamics and test models to quantify the characteristics of these components. To achieve this, we have developed a short-separation speckle contrast optical spectroscopy (ss-SCOS) system by implementing point illumination and point detection using multi-mode fiber arrays to enhance the static and slow components in speckle contrast measurements as compared to traditional wide-field LSCI (WF-LSCI). We observed larger fractions of the static and slow components when measured in the tissue using ss-SCOS than in traditional LSCI for the same animal and region of interest. We have also established models to obtain the fractions of the static and slow components and quantify the decorrelation time constants of the intensity auto-correlation function for both fast blood flow and slower tissue dynamics. Using ss-SCOS, we demonstrate the variations of fast and slow brain dynamics in animals before and post-stroke, as well as within an hour post-euthanasia. This technique establishes the foundation to measure brain tissue dynamics other than CBF, such as intracellular motility.

Measuring human cerebral blood flow and brain function with fiber-based speckle contrast optical spectroscopy system

Cerebral blood flow (CBF) is crucial for brain health. Speckle contrast optical spectroscopy (SCOS) is a technique that has been recently developed to measure CBF, but the use of SCOS to measure human brain function at large source-detector separations with comparable or greater sensitivity to cerebral rather than extracerebral blood flow has not been demonstrated. We describe a fiber-based SCOS system capable of measuring human brain activation induced CBF changes at 33 mm source detector separations using CMOS detectors. The system implements a pulsing strategy to improve the photon flux and uses a data processing pipeline to improve measurement accuracy. We show that SCOS outperforms the current leading optical modality for measuring CBF, i.e. diffuse correlation spectroscopy (DCS), achieving more than 10x SNR improvement at a similar financial cost. Fiber-based SCOS provides an alternative approach to functional neuroimaging for cognitive neuroscience and health science applications.

The Role of the Dorsolateral Prefrontal Cortex in the Production and Comprehension of Phonologically and Semantically Related Words

Previous studies suggest that producing and comprehending semantically related words relies on inhibitory control over competitive lexical selection which results in the recruitment of the left inferior frontal gyrus (IFG). Few studies, however, have examined the involvement of other regions of the frontal cortex, such as the dorsolateral prefrontal cortex (DLPFC), despite its role in cognitive control related to lexical processing. The primary objective of this study was to elucidate the role of the DLPFC in the production and comprehension of semantically and phonologically related words in blocked cyclic naming and picture-word matching paradigms. Twenty-one adults participated in neuroimaging with functional near-infrared spectroscopy to measure changes in oxygenated and deoxygenated hemoglobin concentrations across the bilateral frontal cortex during blocked cyclic picture naming and blocked cyclic picture-word-matching tasks. After preprocessing, oxygenated and deoxygenated hemoglobin concentrations were obtained for each task (production, comprehension), condition (semantic, phonological) and region (DLPFC, IFG). The results of pairwise t-tests adjusted for multiple comparisons showed significant increases in oxygenated hemoglobin concentration over baseline in the bilateral DLPFC during picture naming for phonologically related words. For picture-word matching, we found significant increases in oxygenated hemoglobin concentration over baseline in the right DLPFC for semantically related words and in the right IFG for phonologically related words. We discuss the results in light of the inhibitory attentional control over competitive lexical access theory in contrast to alternative potential explanations for the findings.

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.

Cortical microvascular blood flow velocity mapping by combining dynamic light scattering optical coherence tomography and two-photon microscopy

Significance

The accurate large-scale mapping of cerebral microvascular blood flow velocity is crucial for a better understanding of cerebral blood flow (CBF) regulation. Although optical imaging techniques enable both high-resolution microvascular angiography and fast absolute CBF velocity measurements in the mouse cortex, they usually require different imaging techniques with independent system configurations to maximize their performances. Consequently, it is still a challenge to accurately combine functional and morphological measurements to co-register CBF speed distribution from hundreds of microvessels with high-resolution microvascular angiograms.

Aim

We propose a data acquisition and processing framework to co-register a large set of microvascular blood flow velocity measurements from dynamic light scattering optical coherence tomography (DLS-OCT) with the corresponding microvascular angiogram obtained using two-photon microscopy (2PM).

Approach

We used DLS-OCT to first rapidly acquire a large set of microvascular velocities through a sealed cranial window in mice and then to acquire high-resolution microvascular angiograms using 2PM. The acquired data were processed in three steps: (i) 2PM angiogram coregistration with the DLS-OCT angiogram, (ii) 2PM angiogram segmentation and graphing, and (iii) mapping of the CBF velocities to the graph representation of the 2PM angiogram.

Results

We implemented the developed framework on the three datasets acquired from the mice cortices to facilitate the coregistration of the large sets of DLS-OCT flow velocity measurements with 2PM angiograms. We retrieved the distributions of red blood cell velocities in arterioles, venules, and capillaries as a function of the branching order from precapillary arterioles and postcapillary venules from more than 1000 microvascular segments.

Conclusions

The proposed framework may serve as a useful tool for quantitative analysis of large microvascular datasets obtained by OCT and 2PM in studies involving normal brain functioning, progression of various diseases, and numerical modeling of the oxygen advection and diffusion in the realistic microvascular networks.

High throughput detection of capillary stalling events with Bessel beam two-photon microscopy

Significance

Brief disruptions in capillary flow, commonly referred to as capillary "stalling," have gained interest recently for their potential role in disrupting cerebral blood flow and oxygen delivery. Approaches to studying this phenomenon have been hindered by limited volumetric imaging rates and cumbersome manual analysis. The ability to precisely and efficiently quantify the dynamics of these events will be key in understanding their potential role in stroke and neurodegenerative diseases, such as Alzheimer's disease.

Aim

Our study aimed to demonstrate that the fast volumetric imaging rates offered by Bessel beam two-photon microscopy combined with improved data analysis throughput allows for faster and more precise measurement of capillary stall dynamics.

Results

We found that while our analysis approach was unable to achieve full automation, we were able to cut analysis time in half while also finding stalling events that were missed in traditional blind manual analysis. The resulting data showed that our Bessel beam system was captured more stalling events compared to optical coherence tomography, particularly shorter stalling events. We then compare differences in stall dynamics between a young and old group of mice as well as a demonstrate changes in stalling before and after photothrombotic model of stroke. Finally, we also demonstrate the ability to monitor arteriole dynamics alongside stall dynamics.

Conclusions

Bessel beam two-photon microscopy combined with high throughput analysis is a powerful tool for studying capillary stalling due to its ability to monitor hundreds of capillaries simultaneously at high frame rates.

Neurovascular Uncoupling Is Linked to Microcirculatory Dysfunction in Regions Outside the Ischemic Core Following Ischemic Stroke

Background Normal brain function depends on the ability of the vasculature to increase blood flow to regions with high metabolic demands. Impaired neurovascular coupling, such as the local hyperemic response to neuronal activity, may contribute to poor neurological outcome after stroke despite successful recanalization, that is, futile recanalization. Methods and Results Mice implanted with chronic cranial windows were trained for awake head-fixation before experiments. One-hour occlusion of the anterior middle cerebral artery branch was induced using single-vessel photothrombosis. Cerebral perfusion and neurovascular coupling were assessed by optical coherence tomography and laser speckle contrast imaging. Capillaries and pericytes were studied in perfusion-fixed tissue by labeling lectin and platelet-derived growth factor receptor β. Arterial occlusion induced multiple spreading depolarizations over 1 hour associated with substantially reduced blood flow in the peri-ischemic cortex. Approximately half of the capillaries in the peri-ischemic area were no longer perfused at the 3- and 24-hour follow-up (45% [95% CI, 33%-58%] and 53% [95% CI, 39%-66%] reduction, respectively; P<0.0001), which was associated with contraction of an equivalent proportion of peri-ischemic capillary pericytes. The capillaries in the peri-ischemic cortex that remained perfused showed increased point prevalence of dynamic flow stalling (0.5% [95% CI, 0.2%-0.7%] at baseline, 5.1% [95% CI, 3.2%-6.5%] and 3.2% [95% CI, 1.1%-5.3%] at 3- and 24-hour follow-up, respectively; P=0.001). Whisker stimulation at the 3- and 24-hour follow-up led to reduced neurovascular coupling responses in the sensory cortex corresponding to the peri-ischemic region compared with that observed at baseline. Conclusions Arterial occlusion led to contraction of capillary pericytes and capillary flow stalling in the peri-ischemic cortex. Capillary dysfunction was associated with neurovascular uncoupling. Neurovascular coupling impairment associated with capillary dysfunction may be a mechanism that contributes to futile recanalization. Hence, the results from this study suggest a novel treatment target to improve neurological outcome after stroke.

Measurements of cerebral microvascular blood flow, oxygenation, and morphology in a mouse model of whole-brain irradiation-induced cognitive impairment by two-photon microscopy and optical coherence tomography: evidence for microvascular injury in the cerebral white matter

Whole-brain irradiation (WBI, also known as whole-brain radiation therapy) is a mainstay treatment modality for patients with multiple brain metastases. It is also used as a prophylactic treatment for microscopic tumors that cannot be detected by magnetic resonance imaging. WBI induces a progressive cognitive decline in ~ 50% of the patients surviving over 6 months, significantly compromising the quality of life. There is increasing preclinical evidence that radiation-induced injury to the cerebral microvasculature and accelerated neurovascular senescence plays a central role in this side effect of WBI. To better understand this side effect, male C57BL/6 mice were first subjected to a clinically relevant protocol of fractionated WBI (5 Gy, two doses per week, for 4 weeks). Nine months post the WBI treatment, we applied two-photon microscopy and Doppler optical coherence tomography to measure capillary red-blood-cell (RBC) flux, capillary morphology, and microvascular oxygen partial pressure (PO2) in the cerebral somatosensory cortex in the awake, head-restrained, WPI-treated mice and their age-matched controls, through a cover-glass-sealed chronic cranial window. Thanks to the extended penetration depth with the fluorophore - Alexa680, measurements of capillary blood flow properties (e.g., RBC flux, speed, and linear density) in the cerebral subcortical white matter were enabled. We found that the WBI-treated mice exhibited a significantly decreased capillary RBC flux in the white matter. WBI also caused a significant reduction in capillary diameter, as well as a large (although insignificant) reduction in segment density at the deeper cortical layers (e.g., 600-700 μm), while the other morphological properties (e.g., segment length and tortuosity) were not obviously affected. In addition, we found that PO2 measured in the arterioles and venules, as well as the calculated oxygen saturation and oxygen extraction fraction, were not obviously affected by WBI. Lastly, WBI was associated with a significant increase in the erythrocyte-associated transients of PO2, while the changes of other cerebral capillary PO2 properties (e.g., capillary mean-PO2, RBC-PO2, and InterRBC-PO2) were not significant. Collectively, our findings support the notion that WBI results in persistent cerebral white matter microvascular impairment, which likely contributes to the WBI-induced brain injury and cognitive decline. Further studies are warranted to assess the WBI-induced changes in brain tissue oxygenation and malfunction of the white matter microvasculature as well.

Near-lifespan longitudinal tracking of brain microvascular morphology, topology, and flow in male mice

In age-related neurodegenerative diseases, pathology often develops slowly across the lifespan. As one example, in diseases such as Alzheimer's, vascular decline is believed to onset decades ahead of symptomology. However, challenges inherent in current microscopic methods make longitudinal tracking of such vascular decline difficult. Here, we describe a suite of methods for measuring brain vascular dynamics and anatomy in mice for over seven months in the same field of view. This approach is enabled by advances in optical coherence tomography (OCT) and image processing algorithms including deep learning. These integrated methods enabled us to simultaneously monitor distinct vascular properties spanning morphology, topology, and function of the microvasculature across all scales: large pial vessels, penetrating cortical vessels, and capillaries. We have demonstrated this technical capability in wild-type and 3xTg male mice. The capability will allow comprehensive and longitudinal study of a broad range of progressive vascular diseases, and normal aging, in key model systems.

Multi-Scale Label-free Human Brain Imaging with Integrated Serial Sectioning Polarization Sensitive Optical Coherence Tomography and Two-Photon Microscopy

The study of neurodegenerative processes in the human brain requires a comprehensive understanding of cytoarchitectonic, myeloarchitectonic, and vascular structures. Recent computational advances have enabled volumetric reconstruction of the human brain using thousands of stained slices, however, tissue distortions and loss resulting from standard histological processing have hindered deformation-free reconstruction of the human brain. The development of a multi-scale and volumetric human brain imaging technique that can measure intact brain structure would be a major technical advance. Here, we describe the development of integrated serial sectioning Polarization Sensitive Optical Coherence Tomography (PSOCT) and Two Photon Microscopy (2PM) to provide label-free multi-contrast imaging, including scattering, birefringence and autofluorescence of human brain tissue. We demonstrate that high-throughput reconstruction of 4×4×2cm3 sample blocks and simple registration of PSOCT and 2PM images enable comprehensive analysis of myelin content, vascular structure, and cellular information. We show that 2μm in-plane resolution 2PM images provide microscopic validation and enrichment of the cellular information provided by the PSOCT optical property maps on the same sample, revealing the sophisticated capillary networks and lipofuscin filled cell bodies across the cortical layers. Our method is applicable to the study of a variety of pathological processes, including demyelination, cell loss, and microvascular changes in neurodegenerative diseases such as Alzheimer's disease (AD) and Chronic Traumatic Encephalopathy (CTE).

Simultaneous photoplethysmography and blood flow measurements towards the estimation of blood pressure using speckle contrast optical spectroscopy

Non-invasive continuous blood pressure monitoring remains elusive. There has been extensive research using the photoplethysmographic (PPG) waveform for blood pressure estimation, but improvements in accuracy are still needed before clinical use. Here we explored the use of an emerging technique, speckle contrast optical spectroscopy (SCOS), for blood pressure estimation. SCOS provides measurements of both blood volume changes (PPG) and blood flow index (BFi) changes during the cardiac cycle, and thus provides a richer set of parameters compared to traditional PPG. SCOS measurements were taken on the finger and wrists of 13 subjects. We investigated the correlations between features extracted from both the PPG and BFi waveforms with blood pressure. Features from the BFi waveforms were more significantly correlated with blood pressure than PPG features ( R = - 0.55, p = 1.1 × 10^-4 for the top BFi feature versus R = - 0.53, p = 8.4 × 10^-4 for the top PPG feature). Importantly, we also found that features combining BFi and PPG data were highly correlated with changes in blood pressure ( R = - 0.59, p  = 1.7 × 10^-4 ). These results suggest that the incorporation of BFi measurements should be further explored as a means to improve blood pressure estimation using non-invasive optical techniques.

Short-separation regression incorporated diffuse optical tomography image reconstruction modeling for high-density functional near-infrared spectroscopy

Significance

Short-separation (SS) regression and diffuse optical tomography (DOT) image reconstruction, two widely adopted methods in functional near-infrared spectroscopy (fNIRS), were demonstrated to individually facilitate the separation of brain activation and physiological signals, with further improvement using both sequentially. We hypothesized that doing both simultaneously would further improve the performance.

Aim

Motivated by the success of these two approaches, we propose a method, SS-DOT, which applies SS and DOT simultaneously.

Approach

The method, which employs spatial and temporal basis functions to represent the hemoglobin concentration changes, enables us to incorporate SS regressors into the time series DOT model. To benchmark the performance of the SS-DOT model against conventional sequential models, we use fNIRS resting state data augmented with synthetic brain response as well as data acquired during a ball squeezing task. The conventional sequential models comprise performing SS regression and DOT.

Results

The results show that the SS-DOT model improves the image quality by increasing the contrast-to-background ratio by a threefold improvement. The benefits are marginal at small brain activation.

Conclusions

The SS-DOT model improves the fNIRS image reconstruction quality.

Measuring capillary flow dynamics using interlaced two-photon volumetric scanning

Two photon microscopy and optical coherence tomography (OCT) are two standard methods for measuring flow speeds of red blood cells in microvessels, particularly in animal models. However, traditional two photon microscopy lacks the depth of field to adequately capture the full volumetric complexity of the cerebral microvasculature and OCT lacks the specificity offered by fluorescent labeling. In addition, the traditional raster scanning technique utilized in both modalities requires a balance of image frame rate and field of view, which severely limits the study of RBC velocities in the microvascular network. Here, we overcome this by using a custom two photon system with an axicon based Bessel beam to obtain volumetric images of the microvascular network with fluorescent specificity. We combine this with a novel scan pattern that generates pairs of frames with short time delay sufficient for tracking red blood cell flow in capillaries. We track RBC flow speeds in 10 or more capillaries simultaneously at 1 Hz in a 237 µm × 237 µm × 120 µm volume and quantified both their spatial and temporal variability in speed. We also demonstrate the ability to track flow speed changes around stalls in capillary flow and measure to 300 µm in depth.

Neurovascular coupling is preserved in chronic stroke recovery after targeted photothrombosis

Functional neuroimaging, which measures hemodynamic responses to brain activity, has great potential for monitoring recovery in stroke patients and guiding rehabilitation during recovery. However, hemodynamic responses after stroke are almost always altered relative to responses in healthy subjects and it is still unclear if these alterations reflect the underlying brain physiology or if the alterations are purely due to vascular injury. In other words, we do not know the effect of stroke on neurovascular coupling and are therefore limited in our ability to use functional neuroimaging to accurately interpret stroke pathophysiology. To address this challenge, we simultaneously captured neural activity, through fluorescence calcium imaging, and hemodynamics, through intrinsic optical signal imaging, during longitudinal stroke recovery. Our data suggest that neurovascular coupling was preserved in the chronic phase of recovery (2 weeks and 4 weeks post-stoke) and resembled pre-stroke neurovascular coupling. This indicates that functional neuroimaging faithfully represents the underlying neural activity in chronic stroke. Further, neurovascular coupling in the sub-acute phase of stroke recovery was predictive of long-term behavioral outcomes. Stroke also resulted in increases in global brain oscillations, which showed distinct patterns between neural activity and hemodynamics. Increased neural excitability in the contralesional hemisphere was associated with increased contralesional intrahemispheric connectivity. Additionally, sub-acute increases in hemodynamic oscillations were associated with improved sensorimotor outcomes. Collectively, these results support the use of hemodynamic measures of brain activity post-stroke for predicting functional and behavioral outcomes.

How much do time-domain functional near-infrared spectroscopy (fNIRS) moments improve estimation of brain activity over traditional fNIRS?

SIGNIFICANCE

Advances in electronics have allowed the recent development of compact, high channel count time domain functional near-infrared spectroscopy (TD-fNIRS) systems. Temporal moment analysis has been proposed for increased brain sensitivity due to the depth selectivity of higher order temporal moments. We propose a general linear model (GLM) incorporating TD moment data and auxiliary physiological measurements, such as short separation channels, to improve the recovery of the HRF.

AIMS

We compare the performance of previously reported multi-distance TD moment techniques to commonly used techniques for continuous wave (CW) fNIRS hemodynamic response function (HRF) recovery, namely block averaging and CW GLM. Additionally, we compare the multi-distance TD moment technique to TD moment GLM.

APPROACH

We augmented resting TD-fNIRS moment data (six subjects) with known synthetic HRFs. We then employed block averaging and GLM techniques with "short-separation regression" designed both for CW and TD to recover the HRFs. We calculated the root mean square error (RMSE) and the correlation of the recovered HRF to the ground truth. We compared the performance of equivalent CW and TD techniques with paired t-tests.

RESULTS

We found that, on average, TD moment HRF recovery improves correlations by 98% and 48% for HbO and HbR respectively, over CW GLM. The improvement on the correlation for TD GLM over TD moment is 12% (HbO) and 27% (HbR). RMSE decreases 56% and 52% (HbO and HbR) for TD moment compared to CW GLM. We found no statistically significant improvement in the RMSE for TD GLM compared to TD moment.

CONCLUSIONS

Properly covariance-scaled TD moment techniques outperform their CW equivalents in both RMSE and correlation in the recovery of the synthetic HRFs. Furthermore, our proposed TD GLM based on moments outperforms regular TD moment analysis, while allowing the incorporation of auxiliary measurements of the confounding physiological signals from the scalp.

Volumetric Characterization of Microvasculature in Ex Vivo Human Brain Samples By Serial Sectioning Optical Coherence Tomography

OBJECTIVE

Serial sectioning optical coherence tomography (OCT) enables accurate volumetric reconstruction of several cubic centimeters of human brain samples. We aimed to identify anatomical features of the ex vivo human brain, such as intraparenchymal blood vessels and axonal fiber bundles, from the OCT data in 3D, using intrinsic optical contrast.

METHODS

We developed an automatic processing pipeline to enable characterization of the intraparenchymal microvascular network in human brain samples.

RESULTS

We demonstrated the automatic extraction of the vessels down to a 20 μm in diameter using a filtering strategy followed by a graphing representation and characterization of the geometrical properties of microvascular network in 3D. We also showed the ability to extend this processing strategy to extract axonal fiber bundles from the volumetric OCT image.

CONCLUSION

This method provides a viable tool for quantitative characterization of volumetric microvascular network as well as the axonal bundle properties in normal and pathological tissues of the ex vivo human brain.

Model of dynamic speckle evolution for evaluating laser speckle contrast measurements of tissue dynamics

We introduce a dynamic speckle model (DSM) to simulate the temporal evolution of fully developed speckle patterns arising from the interference of scattered light reemitted from dynamic tissue. Using this numerical tool, the performance of laser speckle contrast imaging (LSCI) or speckle contrast optical spectroscopy (SCOS) systems which quantify tissue dynamics using the spatial contrast of the speckle patterns with a certain camera exposure time is evaluated. We have investigated noise sources arising from the fundamental speckle statistics due to the finite sampling of the speckle patterns as well as those induced by experimental measurement conditions including shot noise, camera dark and read noise, and calibrated the parameters of an analytical noise model initially developed in the fundamental or shot noise regime that quantifies the performance of SCOS systems using the number of independent observables (NIO). Our analysis is particularly focused on the low photon flux regime relevant for human brain measurements, where the impact of shot noise and camera read noise can become significant. Our numerical model is also validated experimentally using a novel fiber based SCOS (fb-SCOS) system for a dynamic sample. We have found that the signal-to-noise ratio (SNR) of fb-SCOS measurements plateaus at a camera exposure time, which marks the regime where shot and fundamental noise dominates over camera read noise. For a fixed total measurement time, there exists an optimized camera exposure time if temporal averaging is utilized to improve SNR. For a certain camera exposure time, photon flux value, and camera noise properties, there exists an optimized speckle-to-pixel size ratio (s/p) at which SNR is maximized. Our work provides the design principles for any LSCI or SCOS systems given the detected photon flux and properties of the instruments, which will guide the experimental development of a high-quality, low-cost fb-SCOS system that monitors human brain blood flow and functions.

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.

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.

Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

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.

Multivariate Kalman filter regression of confounding physiological signals for real-time classification of fNIRS data

Significance: Functional near-infrared spectroscopy (fNIRS) is a noninvasive technique for measuring hemodynamic changes in the human cortex related to neural function. Due to its potential for miniaturization and relatively low cost, fNIRS has been proposed for applications, such as brain-computer interfaces (BCIs). The relatively large magnitude of the signals produced by the extracerebral physiology compared with the ones produced by evoked neural activity makes real-time fNIRS signal interpretation challenging. Regression techniques incorporating physiologically relevant auxiliary signals such as short separation channels are typically used to separate the cerebral hemodynamic response from the confounding components in the signal. However, the coupling of the extra-cerebral signals is often noninstantaneous, and it is necessary to find the proper delay to optimize nuisance removal. Aim: We propose an implementation of the Kalman filter with time-embedded canonical correlation analysis for the real-time regression of fNIRS signals with multivariate nuisance regressors that take multiple delays into consideration. Approach: We tested our proposed method on a previously acquired finger tapping dataset with the purpose of classifying the neural responses as left or right. Results: We demonstrate computationally efficient real-time processing of 24-channel fNIRS data (400 samples per second per channel) with a two order of selective magnitude decrease in cardiac signal power and up to sixfold increase in the contrast-to-noise ratio compared with the nonregressed signals. Conclusion: The method provides a way to obtain better distinction of brain from non-brain signals in real time for BCI application with fNIRS.

Optical measurement of microvascular oxygenation and blood flow responses in awake mouse cortex during functional activation

The cerebral cortex has a number of conserved morphological and functional characteristics across brain regions and species. Among them, the laminar differences in microvascular density and mitochondrial cytochrome c oxidase staining suggest potential laminar variability in the baseline O₂ metabolism and/or laminar variability in both O₂ demand and hemodynamic response. Here, we investigate the laminar profile of stimulus-induced intravascular partial pressure of O₂ (pO2) transients to stimulus-induced neuronal activation in fully awake mice using two-photon phosphorescence lifetime microscopy. Our results demonstrate that stimulus-induced changes in intravascular pO₂ are conserved across cortical layers I-IV, suggesting a tightly controlled neurovascular response to provide adequate O₂ supply across cortical depth. In addition, we observed a larger change in venular O₂ saturation (ΔsO₂) compared to arterioles, a gradual increase in venular ΔsO₂ response towards the cortical surface, and absence of the intravascular "initial dip" previously reported under anesthesia. This study paves the way for quantification of layer-specific cerebral O₂ metabolic responses, facilitating investigation of brain energetics in health and disease and informed interpretation of laminar blood oxygen level dependent functional magnetic resonance imaging signals.

Development of a Monte Carlo-wave model to simulate time domain diffuse correlation spectroscopy measurements from first principles

SIGNIFICANCE

Diffuse correlation spectroscopy (DCS) is an optical technique that measures blood flow non-invasively and continuously. The time-domain (TD) variant of DCS, namely, TD-DCS has demonstrated a potential to improve brain depth sensitivity and to distinguish superficial from deeper blood flow by utilizing pulsed laser sources and a gating strategy to select photons with different pathlengths within the scattering tissue using a single source-detector separation. A quantitative tool to predict the performance of TD-DCS that can be compared with traditional continuous wave DCS (CW-DCS) currently does not exist but is crucial to provide guidance for the continued development and application of these DCS systems.

AIMS

We aim to establish a model to simulate TD-DCS measurements from first principles, which enables analysis of the impact of measurement noise that can be utilized to quantify the performance for any particular TD-DCS system and measurement geometry.

APPROACH

We have integrated the Monte Carlo simulation describing photon scattering in biological tissue with the wave model that calculates the speckle intensity fluctuations due to tissue dynamics to simulate TD-DCS measurements from first principles.

RESULTS

Our model is capable of simulating photon counts received at the detector as a function of time for both CW-DCS and TD-DCS measurements. The effects of the laser coherence, instrument response function, detector gate delay, gate width, intrinsic noise arising from speckle statistics, and shot noise are incorporated in the model. We have demonstrated the ability of our model to simulate TD-DCS measurements under different conditions, and the use of our model to compare the performance of TD-DCS and CW-DCS under a few typical measurement conditions.

CONCLUSION

We have established a Monte Carlo-Wave model that is capable of simulating CW-DCS and TD-DCS measurements from first principles. In our exploration of the parameter space, we could not find realistic measurement conditions under which TD-DCS outperformed CW-DCS. However, the parameter space for the optimization of the contrast to noise ratio of TD-DCS is large and complex, so our results do not imply that TD-DCS cannot indeed outperform CW-DCS under different conditions. We made our code available publicly for others in the field to find use cases favorable to TD-DCS. TD-DCS also provides a promising way to measure deep brain tissue dynamics using a short source-detector separation, which will benefit the development of technologies including high density DCS systems and image reconstruction using a limited number of source-detector pairs.

Scalable mapping of myelin and neuron density in the human brain with micrometer resolution

Optical coherence tomography (OCT) is an emerging 3D imaging technique that allows quantification of intrinsic optical properties such as scattering coefficient and back-scattering coefficient, and has proved useful in distinguishing delicate microstructures in the human brain. The origins of scattering in brain tissues are contributed by the myelin content, neuron size and density primarily; however, no quantitative relationships between them have been reported, which hampers the use of OCT in fundamental studies of architectonic areas in the human brain and the pathological evaluations of diseases. Here, we built a generalized linear model based on Mie scattering theory that quantitatively links tissue scattering to myelin content and neuron density in the human brain. We report a strong linear relationship between scattering coefficient and the myelin content that is retained across different regions of the brain. Neuronal cell body turns out to be a secondary contribution to the overall scattering. The optical property of OCT provides a label-free solution for quantifying volumetric myelin content and neuron cells in the human brain.

Refractive-index matching enhanced polarization sensitive optical coherence tomography quantification in human brain tissue

The importance of polarization-sensitive optical coherence tomography (PS-OCT) has been increasingly recognized in human brain imaging. Despite the recent progress of PS-OCT in revealing white matter architecture and orientation, quantification of fine-scale fiber tracts in the human brain cortex has been a challenging problem, due to a low birefringence in the gray matter. In this study, we investigated the effect of refractive index matching by 2,2'-thiodiethanol (TDE) immersion on the improvement of PS-OCT measurements in ex vivo human brain tissue. We show that we can obtain fiber orientation maps of U-fibers that underlie sulci, as well as cortical fibers in the gray matter, including radial fibers in gyri and distinct layers of fibers exhibiting laminar organization. Further analysis shows that index matching reduces the noise in axis orientation measurements by 56% and 39%, in white and gray matter, respectively. Index matching also enables precise measurements of apparent birefringence, which was underestimated in the white matter by 82% but overestimated in the gray matter by 16% prior to TDE immersion. Mathematical simulations show that the improvements are primarily attributed to the reduction in the tissue scattering coefficient, leading to an enhanced signal-to-noise ratio in deeper tissue regions, which could not be achieved by conventional noise reduction methods.

Neurophotonic tools for microscopic measurements and manipulation: status report

Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.

Investigating Language and Domain-General Processing in Neurotypicals and Individuals With Aphasia - A Functional Near-Infrared Spectroscopy Pilot Study

Brain reorganization patterns associated with language recovery after stroke have long been debated. Studying mechanisms of spontaneous and treatment-induced language recovery in post-stroke aphasia requires a network-based approach given the potential for recruitment of perilesional left hemisphere language regions, homologous right hemisphere language regions, and/or spared bilateral domain-general regions. Recent hardware, software, and methodological advances in functional near-infrared spectroscopy (fNIRS) make it well-suited to examine this question. fNIRS is cost-effective with minimal contraindications, making it a robust option to monitor treatment-related brain activation changes over time. Establishing clear activation patterns in neurotypical adults during language and domain-general cognitive processes via fNIRS is an important first step. Some fNIRS studies have investigated key language processes in healthy adults, yet findings are challenging to interpret in the context of methodological limitations. This pilot study used fNIRS to capture brain activation during language and domain-general processing in neurotypicals and individuals with aphasia. These findings will serve as a reference when interpreting treatment-related changes in brain activation patterns in post-stroke aphasia in the future. Twenty-four young healthy controls, seventeen older healthy controls, and six individuals with left hemisphere stroke-induced aphasia completed two language tasks (i.e., semantic feature, picture naming) and one domain-general cognitive task (i.e., arithmetic) twice during fNIRS. The probe covered bilateral frontal, parietal, and temporal lobes and included short-separation detectors for scalp signal nuisance regression. Younger and older healthy controls activated core language regions during semantic feature processing (e.g., left inferior frontal gyrus pars opercularis) and lexical retrieval (e.g., left inferior frontal gyrus pars triangularis) and domain-general regions (e.g., bilateral middle frontal gyri) during hard versus easy arithmetic as expected. Consistent with theories of post-stroke language recovery, individuals with aphasia activated areas outside the traditional networks: left superior frontal gyrus and left supramarginal gyrus during semantic feature judgment; left superior frontal gyrus and right precentral gyrus during picture naming; and left inferior frontal gyrus pars opercularis during arithmetic processing. The preliminary findings in the stroke group highlight the utility of using fNIRS to study language and domain-general processing in aphasia.

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.

Towards Neuroscience of the Everyday World (NEW) using functional Near-Infrared Spectroscopy

Functional Near-Infrared Spectroscopy (fNIRS) assesses human brain activity by noninvasively measuring changes of cerebral hemoglobin concentrations caused by modulation of neuronal activity. Recent progress in signal processing and advances in system design, such as miniaturization, wearability and system sensitivity, have strengthened fNIRS as a viable and cost-effective complement to functional Magnetic Resonance Imaging (fMRI), expanding the repertoire of experimental studies that can be performed by the neuroscience community. The availability of fNIRS and Electroencephalography (EEG) for routine, increasingly unconstrained, and mobile brain imaging is leading towards a new domain that we term "Neuroscience of the Everyday World" (NEW). In this light, we review recent advances in hardware, study design and signal processing, and discuss challenges and future directions towards achieving NEW.

A Suite of Neurophotonic Tools to Underpin the Contribution of Internal Brain States in fMRI

Recent developments in optical microscopy, applicable for large-scale and longitudinal imaging of cortical activity in behaving animals, open unprecedented opportunities to gain a deeper understanding of neurovascular and neurometabolic coupling during different brain states. Future studies will leverage these tools to deliver foundational knowledge about brain state-dependent regulation of cerebral blood flow and metabolism as well as regulation as a function of brain maturation and aging. This knowledge is of critical importance to interpret hemodynamic signals observed with functional magnetic resonance imaging (fMRI).

Choosing a model for laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is a real-time full-field non-invasive technique, which is broadly applied to visualize blood flow in biomedical applications. In its foundation is the link between the speckle contrast and dynamics of light scattering particles-erythrocytes. The mathematical form describing this relationship, which is critical for accurate blood flow estimation, depends on the sample's light-scattering properties. However, in biological applications, these properties are often unknown, thus requiring assumptions to be made to perform LSCI analysis. Here, we review the most critical assumptions in the LSCI theory and simulate how they affect blood flow estimation accuracy. We show that the most commonly applied model can severely underestimate the flow change, particularly when imaging brain parenchyma or other capillary perfused tissue (e.g. skin) under ischemic conditions. Based on these observations and guided by the recent experimental results, we propose an alternative model that allows measuring blood flow changes with higher accuracy.

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.

Subarachnoid hemorrhage leads to early and persistent functional connectivity and behavioral changes in mice

Aneurysmal subarachnoid hemorrhage (SAH) leads to significant long-term cognitive deficits, which can be associated with alterations in resting state functional connectivity (RSFC). However, modalities such as fMRI-which is commonly used to assess RSFC in humans-have practical limitations in small animals. Therefore, we used non-invasive optical intrinsic signal imaging to determine the effect of SAH on RSFC in mice up to three months after prechiasmatic blood injection. We assessed Morris water maze (MWM), open field test (OFT), Y-maze, and rotarod performance from approximately two weeks to three months after SAH. Compared to sham, we found that SAH reduced motor, retrosplenial, and visual seed-based connectivity indices. These deficits persisted in retrosplenial and visual cortex seeds at three months. Seed-to-seed analysis confirmed early attenuation of correlation coefficients in SAH mice, which persisted in predominantly posterior network connections at later time points. Seed-independent global and interhemispheric indices of connectivity revealed decreased correlations following SAH for at least one month. SAH led to MWM hidden platform and OFT deficits at two weeks, and Y-maze deficits for at least three months, without altering rotarod performance. In conclusion, experimental SAH leads to early and persistent alterations both in hemodynamically derived measures of RSFC and in cognitive performance.

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.