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.

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.

Simulation of oxygen transport and estimation of tissue perfusion in extensive microvascular networks: Application to cerebral cortex

Advanced imaging techniques have made available extensive three-dimensional microvascular network structures. Simulation of oxygen transport by such networks requires information on blood flow rates and oxygen levels in vessels crossing boundaries of the imaged region, which is difficult to obtain experimentally. Here, a computational method is presented for estimating blood flow rates, oxygen levels, tissue perfusion and oxygen extraction, based on incomplete boundary conditions. Flow rates in all segments are estimated using a previously published method. Vessels crossing the region boundary are classified as arterioles, capillaries or venules. Oxygen levels in inflowing capillaries are assigned based on values in outflowing capillaries, and similarly for venules. Convective and diffusive oxygen transport is simulated. Contributions of each vessel to perfusion are computed in proportion to the decline in oxygen concentration along that vessel. For a vascular network in the mouse cerebral cortex, predicted tissue oxygen levels show a broad distribution, with 99% of tissue in the range of 20 to 80 mmHg under reference conditions, and steep gradients near arterioles. Perfusion and extraction estimates are consistent with experimental values. A 30% reduction in perfusion or a 30% increase in oxygen demand, relative to reference levels, is predicted to result in tissue hypoxia.

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.

Dynamic capillary stalls in reperfused ischemic penumbra contribute to injury: A hyperacute role for neutrophils in persistent traffic jams

Ever since the introduction of thrombolysis and the subsequent expansion of endovascular treatments for acute ischemic stroke, it remains to be identified why the actual outcomes are less favorable despite recanalization. Here, by high spatio-temporal resolution imaging of capillary circulation in mice, we introduce the pathological phenomenon of dynamic flow stalls in cerebral capillaries, occurring persistently in salvageable penumbra after reperfusion. These stalls, which are different from permanent cellular plugs of no-reflow, were temporarily and repetitively occurring in the capillary network, impairing the overall circulation like small focal traffic jams. In vivo microscopy in the ischemic penumbra revealed leukocytes traveling slowly through capillary lumen or getting stuck, while red blood cell flow was being disturbed in the neighboring segments under reperfused conditions. Stall dynamics could be modulated, by injection of an anti-Ly6G antibody specifically targeting neutrophils. Decreased number and duration of stalls were associated with improvement in penumbral blood flow within 2-24 h after reperfusion along with increased capillary oxygenation, decreased cellular damage and improved functional outcome. Thereby, dynamic microcirculatory stall phenomenon can be a contributing factor to ongoing penumbral injury and is a potential hyperacute mechanism adding on previous observations of detrimental effects of activated neutrophils in ischemic stroke.

Improved Color Doppler for Cerebral Blood Flow Axial Velocity Imaging

Conventional color Doppler ultrasound imaging suffers from mutual frequency cancellation when applied to quantify axial blood flow velocities in the rodent brain where inverse flows exist within an ultrasound measurement voxel. Here, we report an improved color Doppler-based functional ultrasound imaging method (iCD-fUS) for axial blood flow velocity imaging of the rodent brain. By applying a directional filter and high frequency noise thresholding, iCD-fUS is able to accurately quantify blood flow velocities within the brain as validated with the ultrasound localization microscopy velocimetry method. We show that iCD-fUS is able to image and resolve the directional axial blood flow velocity throughout the entire coronal section of the brain at a temporal frame rate of up to 10 Hz with a spatial resolution of ~100 [Formula: see text]. We further applied iCD-fUS to image the axial blood flow velocity change in response to whisker stimulation in an awake mouse, showing its potential for studying brain activation. With these capabilities, iCD-fUS provides a powerful, quantitative tool for in vivo chronic research.

Chronic Cranial Windows for Long Term Multimodal Neurovascular Imaging in Mice

Chronic cranial windows allow for longitudinal brain imaging experiments in awake, behaving mice. Different imaging technologies have their unique advantages and combining multiple imaging modalities offers measurements of a wide spectrum of neuronal, glial, vascular, and metabolic parameters needed for comprehensive investigation of physiological and pathophysiological mechanisms. Here, we detail a suite of surgical techniques for installation of different cranial windows targeted for specific imaging technologies and their combination. Following these techniques and practices will yield higher experimental success and reproducibility of results.

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement. Segmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here, we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. Introduction. Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms. Methods. We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network’s output. Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808×808×702 μm. Results. To demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10× faster computation in terms of voxels-segmented-per-second and 3× larger depth compared to the state-of-the-art. Conclusion. Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning-based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before.

Stroke core revealed by tissue scattering using spatial frequency domain imaging

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We present OCT and SFDI as methods to measure the spatial extent of stroke in mice.

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OCT was a reliable predictor of the stroke core in a photothrombosis stroke model.

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SFDI scattering coefficient spatially overlaps with OCT attenuation after stroke.

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Scattering increases following stroke reliably predict ischemic injury.

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SFDI provides a wide-field optical approach to map the stroke core.

Ischemic stroke leads to a reduction or complete loss of blood supply causing injury to brain tissue, which ultimately leads to behavioral impairment. Optical techniques are widely used to study the structural and functional changes that result as a consequence of ischemic stroke both in the acute and chronic phases of stroke recovery. It is currently a challenge to accurately estimate the spatial extent of the infarct without the use of histological parameters however, and in order to follow recovery mechanisms longitudinally at the mesoscopic scale it is essential to know the spatial extent of the stroke core. In this paper we first establish optical coherence tomography (OCT) as a reliable indicator of the stroke core by analyzing signal attenuation and spatially correlating it with the infarct, determined by staining with triphenyl-tetrazolium chloride (TTC). We then introduce spatial frequency domain imaging (SFDI) as a mesoscopic optical technique that can be used to accurately measure the infarct spatial extent by exploiting changes in optical scattering that occur as a consequence of ischemic stroke. Additionally, we follow the progression of ischemia through the acute and sub-acute phases of stroke recovery using both OCT and SFDI and show a consistently high spatial overlap in estimating infarct location. The use of SFDI in assessing infarct location will allow longitudinal studies targeted at following functional recovery mechanisms on a mesoscopic level without having to sacrifice the mouse acutely.

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement. Segmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here, we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. Introduction. Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms. Methods. We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network's output. Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808 × 808 × 702   μ m . Results. To demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10× faster computation in terms of voxels-segmented-per-second and 3× larger depth compared to the state-of-the-art. Conclusion. Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning-based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before.

Quantification of Capillary Perfusion in an Animal Model of Acute Intracranial Hypertension

Intracranial hypertension (IH) is a common feature of many pathologies, including brain edema. In the brain, the extended network of capillaries ensures blood flow to meet local metabolic demands. Capillary circulation may be severely affected by IH, but no studies have quantified the effect of intracranial pressure (ICP) and cerebral perfusion pressure (CPP) on capillary perfusion during the development of brain edema. We used optical coherence tomography angiography to quantify relative changes of fractional perfused volume (FPV) in cortical capillaries and simultaneously monitored ICP and blood pressure (BP) in anesthetized male C57Bl/6NTac mice during development of brain edema induced by water intoxication (WI) within 30 min. WI induced severe IH and brain herniation. ICP and CPP reached 90.2 mm Hg and 38.4 mm Hg, respectively. FPV was significantly affected already at normal ICP (ICP <15 mm Hg, slope ≈ -1.46, p < 0.001) and, at the onset of IH (ICP = 20-22 mm Hg), FPV was 17.9 ± 13.3% lower than baseline. A decreasing trend was observed until the ICP peak (Δ%FPV = -43.6 ± 19.2%). In the ICP range of 7-42 mm Hg, relative changes in FPV were significantly correlated with ICP, BP, and CPP (p < 0.001), with ICP and CPP being the best predictors. In conclusion, elevated ICP induces a gradual collapse of the cerebral microvasculature, which is initiated before the clinical threshold of IH. In summary, the estimate of capillary perfusion might be essential in patients with IH to assess the state of the brain microcirculation and to improve the availability of oxygen and nutrients to the brain.

Dynamic light scattering imaging

We introduce dynamic light scattering imaging (DLSI) to enable the wide-field measurement of the speckle temporal intensity autocorrelation function. DLSI uses the full temporal sampling of speckle fluctuations and a comprehensive model to identify the dynamic scattering regime and obtain a quantitative image of the scatterer dynamics. It reveals errors in the traditional theory of laser Doppler flowmetry and laser speckle contrast imaging and provides guidance on the best model to use in cerebral blood flow imaging.

Improving the characterization of ex vivo human brain optical properties using high numerical aperture optical coherence tomography by spatially constraining the confocal parameters

Significance: The optical properties of biological samples provide information about the structural characteristics of the tissue and any changes arising from pathological conditions. Optical coherence tomography (OCT) has proven to be capable of extracting tissue's optical properties using a model that combines the exponential decay due to tissue scattering and the axial point spread function that arises from the confocal nature of the detection system, particularly for higher numerical aperture (NA) measurements. A weakness in estimating the optical properties is the inter-parameter cross-talk between tissue scattering and the confocal parameters defined by the Rayleigh range and the focus depth. Aim: In this study, we develop a systematic method to improve the characterization of optical properties with high-NA OCT. Approach: We developed a method that spatially parameterizes the confocal parameters in a previously established model for estimating the optical properties from the depth profiles of high-NA OCT. Results: The proposed parametrization model was first evaluated on a set of intralipid phantoms and then validated using a low-NA objective in which cross-talk from the confocal parameters is negligible. We then utilize our spatially parameterized model to characterize optical property changes introduced by a tissue index matching process using a simple immersion agent, 2,2'-thiodiethonal. Conclusions: Our approach improves the confidence of parameter estimation by reducing the degrees of freedom in the non-linear fitting model.

Single-shot 3D wide-field fluorescence imaging with a Computational Miniature Mesoscope

Fluorescence microscopes are indispensable to biology and neuroscience. The need for recording in freely behaving animals has further driven the development in miniaturized microscopes (miniscopes). However, conventional microscopes/miniscopes are inherently constrained by their limited space-bandwidth product, shallow depth of field (DOF), and inability to resolve three-dimensional (3D) distributed emitters. Here, we present a Computational Miniature Mesoscope (CM2) that overcomes these bottlenecks and enables single-shot 3D imaging across an 8 mm by 7 mm field of view and 2.5-mm DOF, achieving 7-μm lateral resolution and better than 200-μm axial resolution. The CM2 features a compact lightweight design that integrates a microlens array for imaging and a light-emitting diode array for excitation. Its expanded imaging capability is enabled by computational imaging that augments the optics by algorithms. We experimentally validate the mesoscopic imaging capability on 3D fluorescent samples. We further quantify the effects of scattering and background fluorescence on phantom experiments.

Functional Ultrasound Speckle Decorrelation-Based Velocimetry of the Brain

A high-speed, contrast-free, quantitative ultrasound velocimetry (vUS) for blood flow velocity imaging throughout the rodent brain is developed based on the normalized first-order temporal autocorrelation function of the ultrasound field signal. vUS is able to quantify blood flow velocity in both transverse and axial directions, and is validated with numerical simulation, phantom experiments, and in vivo measurements. The functional imaging ability of vUS is demonstrated by monitoring the blood flow velocity changes during whisker stimulation in awake mice. Compared to existing Power-Doppler- and Color-Doppler-based functional ultrasound imaging techniques, vUS shows quantitative accuracy in estimating both axial and transverse flow speeds and resistance to acoustic attenuation and high-frequency noise.

Chronic Imaging of Mouse Brain: From Optical Systems to Functional Ultrasound

Utilization of functional ultrasound (fUS) in cerebral vascular imaging is gaining popularity among neuroscientists. In this article, we describe a chronic surgical preparation method that allows longitudinal studies and therefore is applicable to a wide range of studies, especially on aging, stroke, and neurodegenerative diseases. This method can also be used with awake mice; hence, the deleterious effects of anesthesia on neurovascular responses can be avoided. In addition to fUS imaging, this surgical preparation allows researchers to take advantage of common optical imaging methods to acquire complementary datasets to help increase the technical rigor of studies. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Surgical preparation of mouse chronic cranial windows using polymethylpentene Basic Protocol 2: Imaging of mice with chronic cranial windows.

The mass transfer coefficient for oxygen transport from blood to tissue in cerebral cortex

The functioning of cerebral cortex depends on adequate tissue oxygenation. MRI-based techniques allow estimation of blood oxygen levels, tissue perfusion, and oxygen consumption rate (CMRO₂), but do not directly measure partial pressure of oxygen (PO₂) in tissue. To address the estimation of tissue PO₂, the oxygen mass transfer coefficient (KTO₂) is here defined as the CMRO₂ divided by the difference in spatially averaged PO₂ between blood and tissue, and is estimated by analyzing Krogh-cylinder type models. Resistance to radial diffusion of oxygen from microvessels to tissue is distributed within vessels and in the extravascular tissue. The value of KTO₂ is shown to depend strongly on vascular length density and also on microvessel tube hematocrits and diameters, but to be insensitive to blood flow rate and to transient changes in flow or oxygen consumption. Estimated values of KTO₂ are higher than implied by previous studies, implying smaller declines in PO₂ from blood to tissue. Average tissue PO₂ can be estimated from MRI-based measurements as average blood PO₂ minus the product of KTO₂ and CMRO₂. For oxygen consumption rates and vascular densities typical of mouse cortex, the predicted difference between average blood and tissue PO₂ is about 10 mmHg.

Characterization of continuous wave ultrasound for acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS)

Intra and post-operative blood flow monitoring of tissue has been shown to be effective in the improvement of patient outcomes. Diffuse correlation spectroscopy (DCS) has been shown to be effective in measuring blood flow at the bedside, and is a useful technique in measuring cerebral blood flow (CBF) in many clinical settings. However, DCS suffers from reduced sensitivity to blood flow changes at larger tissue depths, making measurements of CBF in adults difficult. This issue can be addressed with acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS), which is a hybrid technique that combines the sensitivity of DCS to blood flow with ultrasound resolution to allow for improved spatial resolution of the optical signal based on knowledge of the area which is insonified by ultrasound. We present a quantitative model for perfusion estimation based on AOM-DCS in the presence of continuous wave ultrasound, supported by theoretical derivations, Monte Carlo simulations, and phantom and human subject experiments. Quantification of the influence of individual mechanisms that contribute to the temporal fluctuations of the optical intensity due to ultrasound is shown to agree with previously derived results. By using this model, the recovery of blood-flow induced scatterer dynamics based on ultrasound-modulated light is shown to deviate by less than one percent from the standard DCS measurement of scatterer dynamics over a range of optical scattering values and scatterer motion conditions. This work provides an important step towards future implementation of AOM-DCS setups with more complex spatio-temporal distributions of ultrasound pressure, which are needed to enhance the DCS spatial resolution.

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.

Differential effects of anesthetics on resting state functional connectivity in the mouse

Blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard approach to examine resting state functional connectivity (RSFC), but fMRI in animal models is challenging. Recently, functional optical intrinsic signal imaging-which relies on the same hemodynamic signal underlying BOLD fMRI-has been developed as a complementary approach to assess RSFC in mice. Since it is difficult to ensure that an animal is in a truly resting state while awake, RSFC measurements under anesthesia remain an important approach. Therefore, we systematically examined measures of RSFC using non-invasive, widefield optical intrinsic signal imaging under five different anesthetics in male C57BL/6J mice. We find excellent seed-based, global, and interhemispheric connectivity using tribromoethanol (Avertin) and ketamine-xylazine, comparable to results in the literature including awake animals. Urethane anesthesia yielded intermediate results, while chloral hydrate and isoflurane were both associated with poor RSFC. Furthermore, we found a correspondence between the strength of RSFC and the power of low-frequency hemodynamic fluctuations. In conclusion, Avertin and ketamine-xylazine provide robust and reproducible measures of RSFC in mice, whereas chloral hydrate and isoflurane do not.