In this Outlook paper, we explain why an accurate physiological interpretation of functional near-infrared spectroscopy (fNIRS) neuroimaging signals is facilitated when systemic physiological activity (e.g., cardiorespiratory and autonomic activity) is measured simultaneously by employing systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS). The rationale for SPA-fNIRS is twofold: (i) SPA-fNIRS enables a more complete interpretation and understanding of the fNIRS signals measured at the head since they contain components originating from neurovascular coupling and from systemic physiological sources. The systemic physiology signals measured with SPA-fNIRS can be used for regressing out physiological confounding components in fNIRS signals. Misinterpretations can thus be minimized. (ii) SPA-fNIRS enables to study the embodied brain by linking the brain with the physiological state of the entire body, allowing novel insights into their complex interplay. We envisage the SPA-fNIRS approach will become increasingly important in the future.

The guest editorial provides an introduction to Parts 1 and 2 of the Neurophotonics Special Section on Imaging Neuroimmune, Neuroglial, and Neurovascular Interfaces.

Significance: Three-photon (3P) microscopy significantly increases the depth and resolution of in vivo imaging due to decreased scattering and nonlinear optical sectioning. Simultaneous excitation of multiple fluorescent proteins is essential to studying multicellular interactions and dynamics in the intact brain.

Aim: We characterized the excitation laser pulses at a range of wavelengths for 3P microscopy, and then explored the application of tdTomato or mScarlet and EGFP for dual-color single-excitation structural 3P imaging deep in the living mouse brain.

Approach: We used frequency-resolved optical gating to measure the spectral intensity, phase, and retrieved pulse widths at a range of wavelengths. Then, we performed in vivo single wavelength-excitation 3P imaging in the 1225- to 1360-nm range deep in the mouse cerebral cortex to evaluate the performance of tdTomato or mScarlet in combination with EGFP.

Results: We find that tdTomato and mScarlet, expressed in oligodendrocytes and neurons respectively, have a high signal-to-background ratio in the 1300- to 1360-nm range, consistent with enhanced 3P cross-sections.

Conclusions: These results suggest that a single excitation wavelength source is advantageous for multiple applications of dual-color brain imaging and highlight the importance of empirical characterization of individual fluorophores for 3P microscopy.

Significance: Neurovascular coupling (NVC) is the process that increases cerebral blood flow in response to neuronal activity. NVC is orchestrated by signaling between neurons, glia, and vascular cells. Elucidating the mechanisms underlying NVC at different vascular segments and in different brain regions is imperative for understanding of brain function and mechanisms of dysfunction.

Aim: Our goal is to describe a protocol for concurrently monitoring stimulation-evoked neuronal activity and resultant vascular responses in acute brain slices.

Approach: We describe a step-by-step protocol that allows the study of endogenous NVC mechanisms engaged by neuronal activity in a controlled, reduced preparation.

Results: This ex vivo NVC assay allows researchers to disentangle the mechanisms regulating the contractile responses of different vascular segments in response to neuronal firing independent of flow and pressure mediated effects from connected vessels. It also enables easy pharmacological manipulations in a simplified, reduced system and can be combined with Ca^2  + imaging or broader electrophysiology techniques to obtain multimodal data during NVC.

Conclusions: The ex vivo NVC assay will facilitate investigations of cellular and molecular mechanisms that give rise to NVC and should serve as a valuable complement to in vivo imaging methods.

Brain barriers are crucial sites for cerebral energy supply, waste removal, immune cell migration, and solute exchange, all of which maintain an appropriate environment for neuronal activity. At the capillary level, where the largest area of brain–vascular interface occurs, pericytes adjust cerebral blood flow (CBF) by regulating capillary diameter and maintain the blood–brain barrier (BBB) by suppressing endothelial cell (EC) transcytosis and inducing tight junction expression between ECs. Pericytes also limit the infiltration of circulating leukocytes into the brain where resident microglia confine brain injury and provide the first line of defence against invading pathogens. Brain “waste” is cleared across the BBB into the blood, phagocytosed by microglia and astrocytes, or removed by the flow of cerebrospinal fluid (CSF) through perivascular routes—a process driven by respiratory motion and the pulsation of the heart, arteriolar smooth muscle, and possibly pericytes. “Dirty” CSF exits the brain and is probably drained around olfactory nerve rootlets and via the dural meningeal lymphatic vessels and possibly the skull bone marrow. The brain is widely regarded as an immune-privileged organ because it is accessible to few antigen-primed leukocytes. Leukocytes enter the brain via the meninges, the BBB, and the blood-CSF barrier. Advances in genetic and imaging tools have revealed that neurological diseases significantly alter immune–brain barrier interactions in at least three ways: (1) the brain’s immune-privileged status is compromised when pericytes are lost or lymphatic vessels are dysregulated; (2) immune cells release vasoactive molecules to regulate CBF, modulate arteriole stiffness, and can plug and eliminate capillaries which impairs CBF and possibly waste clearance; and (3) immune–vascular interactions can make the BBB leaky via multiple mechanisms, thus aggravating the influx of undesirable substances and cells. Here, we review developments in these three areas and briefly discuss potential therapeutic avenues for restoring brain barrier functions.

Significance: The glymphatic system has been described recently as a series of perivascular channels that facilitate fluid exchange and solute clearance in the brain. Glymphatic dysfunction has been implicated in numerous pathological conditions, including Alzheimer’s disease, traumatic brain injury, and stroke. Existing methods for assessing glymphatic function have been challenging: dynamic methods, such as two-photon microscopy and contrast-enhanced magnetic resonance imaging require expensive instrumentation and specific technical skills; slice-based fluorescent imaging is more readily implemented but lacks temporal resolution.

Aim: To develop a straightforward and adaptable dynamic imaging approach for assessing glymphatic function in vivo in mice.

Approach: Using a widely available small animal infrared (IR) imaging system (LICOR Pearl), visualization of IR cerebrospinal fluid tracer distribution over the cortical surface enables time-resolved measurement of the dynamics of glymphatic exchange. Using co-injection of IR and conventional fixable fluorescent tracers, dynamic imaging can be paired with whole-slice fluorescence imaging, permitting the quantification of glymphatic function throughout the brain as well as subsequent histological assessment.

Results: These techniques were validated against one another, comparing differences between animals anesthetized with ketamine/xylazine and isoflurane.

Conclusions: This technique permits sensitive dynamic imaging of glymphatic function, with the concurrent visualization of resolution of deeper structures.

Significance: A growing body of research supports the significant role of cerebrovascular abnormalities in neurological disorders. As these insights develop, standardized tools for unbiased and high-throughput quantification of cerebrovascular structure are needed.

Aim: We provide a detailed protocol for performing immunofluorescent labeling of mouse brain vessels, using thin (25  μm) or thick (50 to 150  μm) tissue sections, followed respectively by two- or three-dimensional (2D or 3D) unbiased quantification of vessel density, branching, and tortuosity using digital image processing algorithms.

Approach: Mouse brain sections were immunofluorescently labeled using a highly selective antibody raised against mouse Cluster of Differentiation-31 (CD31), and 2D or 3D microscopy images of the mouse brain vasculature were obtained using optical sectioning. An open-source toolbox, called Pyvane, was developed for analyzing the imaged vascular networks. The toolbox can be used to identify the vasculature, generate the medial axes of blood vessels, represent the vascular network as a graph, and calculate relevant measurements regarding vascular morphology.

Results: Using Pyvane, vascular parameters such as endothelial network density, number of branching points, and tortuosity are quantified from 2D and 3D immunofluorescence micrographs.

Conclusions: The steps described in this protocol are simple to follow and allow for reproducible and unbiased analysis of mouse brain vascular structure. Such a procedure can be applied to the broader field of vascular biology.

Significance: To study leukocyte-endothelial interactions in a living system, robust and specific leukocyte labeling techniques are needed for in vivo two-photon microscopy of the cerebral microvasculature.

Aim: We tested fluorophore-conjugated anti-CD45.2 monoclonal antibodies (mAb) to optimize dosing and two-photon imaging parameters for leukocyte labeling in healthy mice and a venous microstroke model.

Approach: We retro-orbitally injected anti-CD45.2 mAb at 0.04, 0.4, and 2  mg  /  kg into BALB/c mice and used flow cytometry to analyze antibody saturation. Leukocyte labeling in the cortical microvasculature was examined by two-photon imaging. We also tested the application of CD45.2 mAb in a pathological leukocyte-endothelial adhesion model by photothrombotically occluding cortical penetrating venules.

Results: We found that 0.4  mg  /  kg of anti-CD45.2 antibody intravenously was sufficient to label 95% of circulating leukocytes. There was no depletion of circulating leukocytes after 24 h at the dosages tested. Labeled leukocytes could be observed as deep as 550  μm from the cortical surface. The antibody reliably labeled rolling, crawling, and adherent leukocytes in venules around the stroke-affected tissues.

Conclusion: We show that the anti-CD45.2 mAb is a robust reagent for acute labeling of leukocytes during in vivo two-photon microscopy of the cortical microvasculature.

Significance: Two-photon microscopy is a powerful tool for in vivo imaging of the mammalian brain at cellular to subcellular resolution. However, resources that describe methods for imaging live newborn mice have remained sparse.

Aim: We describe a non-invasive cranial window procedure for longitudinal imaging of neonatal mice.

Approach: We demonstrate construction of the cranial window by iterative shaving of the calvarium of P0 to P12 mouse pups. We use the edge of a syringe needle and scalpel blades to thin the bone to ∼15-μm thickness. The window is then reinforced with cyanoacrylate glue and a coverslip to promote stability and optical access for at least a week. The head cap also includes a light-weight aluminum flange for head-fixation during imaging.

Results: The resulting chronic thinned-skull window enables in vivo imaging to a typical cortical depth of   ∼  200  μm without disruption of the intracranial environment. We highlight techniques to measure vascular structure and blood flow during development, including use of intravenous tracers and transgenic mice to label the blood plasma and vascular cell types, respectively.

Conclusions: This protocol enables direct visualization of the developing neurogliovascular unit in the live neonatal brain during both normal and pathological states.

Significance: Vascular mural cells, defined as smooth muscle cells (SMCs) and pericytes, influence brain microcirculation, but how they contribute is not fully understood. Most approaches used to investigate pericyte and capillary interactions include ex vivo retinal/slice preparations or in vivo two-photon microscopy. However, neither method adequately captures mural cell behavior without interfering neuronal tissue. Thus, there is a need to isolate vessels with their respective mural cells to study functional and pathological changes.

Aim: The aim of our work was to implement an ex vivo method that recapitulates vessel dynamics in the brain.

Approach: Expanding upon our established ex vivo capillary-parenchymal arteriole (CaPA) preparation, we isolated and pressurized arteriole-capillary branches. Using Alexa Fluor™ 633 Hydrazide, we distinguished arterioles (containing elastin) versus capillaries (lacking elastin). In addition, our transgenic SMMHC-GCaMP6f mice allowed for us to visualize mural cell morphology and Ca^{2 +} signals. Lastly, isolated microvasculature was cultured in DMEM media (up to 72 h), mounted, and pressurized using our CaPA preparation.

Results: U46619 induced a decrease in capillary lumen diameter using both a bath perfusion and local application. In addition, U46619 increased Ca^{2 +} signaling both globally and locally in contractile pericytes. In our SMMHC-GCaMP6f mice, we saw that thin strand pericytes had sparse processes while contractile pericytes had long, thick processes that wrapped around the lumen of the capillary. Fresh and cultured pericytes constricted in response to U46619 to the same level, and upstream arteriolar dilation induced by capillary stimulation with 10 mM K ⁺ remained unchanged by culture conditions adding another application of longer treatment to our approach.

Conclusion: Our ex vivo CaPA methodology facilitates observation of arteriolar SMC and pericyte dynamic changes in real-time without environmental factors. This method will help to better understand how mural cells differ based on microvasculature location.

Significance: rPySight brings a flexible and highly customizable open-software platform built around a powerful multichannel digitizer; combined, it enables performing complex photon counting-based experiments. We exploited advanced programming technology to share the photon counting stream with the graphical processing unit (GPU), making possible real-time display of two-dimensional (2D) and three-dimensional (3D) experiments and paving the road for other real-time applications.

Aim: Photon counting improves multiphoton imaging by providing better signal-to-noise ratio in photon-deprived applications and is becoming more widely implemented, as indicated by its increasing presence in many microscopy vendor portfolios. Despite the relatively easy access to this technology offered in commercial systems, these remain limited to one or two channels of data and might not enable highly tailored experiments, forcing most researchers to develop their own electronics and code. We set to develop a flexible and open-source interface to a cutting-edge multichannel fast digitizer that can be easily integrated into existing imaging systems.

Approach: We selected an advanced multichannel digitizer capable of generating 70M tags/s and wrote an open software application, based on Rust and Python languages, to share the stream of detected events with the GPU, enabling real-time data processing.

Results: rPySight functionality was showcased in real-time monitoring of 2D imaging, improved calcium imaging, multiplexing, and 3D imaging through a varifocal lens. We provide a detailed protocol for implementing out-of-the-box rPySight and its related hardware.

Conclusions: Applying photon-counting approaches is becoming a fundamental component in recent technical developments that push well beyond existing acquisition speed limitations of classical multiphoton approaches. Given the performance of rPySight, we foresee its use to capture, among others, the joint dynamics of hundreds (if not thousands) of neuronal and vascular elements across volumes, as is likely required to uncover in a much broader sense the hemodynamic transform function.

The article introduces the Special Section on Hybrid Photonic/X Neurointerfaces for Neurophotonics Volume 9 Issue 3.

Brain organization is evident across spatiotemporal scales as well as from structural and functional data. Yet, translating from micro- to macroscale (vice versa) as well as between different measures is difficult. Reconciling disparate observations from different modes is challenging because each specializes within a restricted spatiotemporal milieu, usually has bounded organ coverage, and has access to different contrasts. True intersubject biological heterogeneity, variation in experiment implementation (e.g., use of anesthesia), and true moment-to-moment variations in brain activity (maybe attributable to different brain states) also contribute to variability between studies. Ultimately, for a deeper and more actionable understanding of brain organization, an ability to translate across scales, measures, and species is needed. Simultaneous multimodal methods can contribute to bettering this understanding. We consider four modes, three optically based: multiphoton imaging, single-photon (wide-field) imaging, and fiber photometry, as well as magnetic resonance imaging. We discuss each mode as well as their pairwise combinations with regard to the definition and study of brain networks.

Significance: Ultrasound has recently received considerable attention in neuroscience because it provides noninvasive control of deep brain activity. Although the feasibility of ultrasound stimulation has been reported in preclinical and clinical settings, its mechanistic understanding remains limited. While optical microscopy has become the “gold standard” tool for investigating population-level neural functions in vivo, its application for ultrasound neuromodulation has been technically challenging, as most conventional ultrasonic transducers are not designed to be compatible with optical microscopy.

Aim: We aimed to develop a transparent acoustic transducer based on a glass coverslip called the acousto-optic window (AOW), which simultaneously provides ultrasound neuromodulation and microscopic monitoring of neural responses in vivo.

Approach: The AOW was fabricated by the serial deposition of transparent acoustic stacks on a circular glass coverslip, comprising a piezoelectric material, polyvinylidene fluoride-trifluoroethylene, and indium-tin-oxide electrodes. The fabricated AOW was implanted into a transgenic neural-activity reporter mouse after open craniotomy. Two-photon microscopy was used to observe neuronal activity in response to ultrasonic stimulation through the AOW.

Results: The AOW allowed microscopic imaging of calcium activity in cortical neurons in response to ultrasound stimulation. The optical transparency was ∼40 % over the visible and near-infrared spectra, and the ultrasonic pressure was 0.035 MPa at 10 MHz corresponding to 10 mW / cm². In anesthetized Gad2-GCaMP6-tdTomato mice, we observed robust ultrasound-evoked activation of inhibitory cortical neurons at depths up to 200 μm.

Conclusions: The AOW is an implantable ultrasonic transducer that is broadly compatible with optical imaging modalities. The AOW will facilitate our understanding of ultrasound neuromodulation in vivo.

Significance: Electrophysiological recording and optical imaging are two prevalent neurotechnologies with complementary strengths, the combined application of which can significantly improve our capacity in deciphering neural circuits. Flexible electrode arrays can support longitudinal optical imaging in the same brain region, but their mechanical flexibility makes surgical preparation challenging. Here, we provide a step-by-step protocol by which an ultraflexible nanoelectronic thread is co-implanted with a cranial window in a single surgery to enable chronic, dual-modal measurements.

Aim: The method uses 1-μm-thick polymer neural electrodes which conform to the site of implantation. The mechanical flexibility of the probe allows bending without breaking and enables long-lasting electrophysiological recordings of single-unit activities and concurrent, high-resolution optical imaging through the cranial window.

Approach: The protocol describes methods and procedures to co-implant an ultraflexible electrode array and a glass cranial window in the mouse neocortex. The implantation strategy includes temporary attachment of flexible electrodes to a retractable tungsten-microwire insertion shuttle, craniotomy, stereotaxic insertion of the electrode array, skull fixation of the cranial window and electrode, and installation of a head plate.

Results: The resultant implant allows simultaneous interrogation of brain activity both electrophysiologically and optically for several months. Importantly, a variety of optical imaging modalities, including wide-field fluorescent imaging, two-photon microscopy, and functional optical imaging, can be readily applied to the specific brain region where ultraflexible electrodes record from.

Conclusions: The protocol describes a method for co-implantation of ultraflexible neural electrodes and a cranial window for chronic, multimodal measurements of brain activity in mice. Device preparation and surgical implantation are described in detail to guide the adaptation of these methods for other flexible neural implants and cranial windows.

Significance: Although emerging evidence suggests that the hemodynamic response function (HRF) can vary by brain region and species, a single, canonical, human-based HRF is widely used in animal studies. Therefore, the development of flexible, accessible, brain-region specific HRF calculation approaches is paramount as hemodynamic animal studies become increasingly popular.

Aim: To establish an fMRI-compatible, spectral, fiber-photometry platform for HRF calculation and validation in any rat brain region.

Approach: We used our platform to simultaneously measure (a) neuronal activity via genetically encoded calcium indicators (GCaMP6f), (b) local cerebral blood volume (CBV) from intravenous Rhodamine B dye, and (c) whole brain CBV via fMRI with the Feraheme contrast agent. Empirical HRFs were calculated with GCaMP6f and Rhodamine B recordings from rat brain regions during resting-state and task-based paradigms.

Results: We calculated empirical HRFs for the rat primary somatosensory, anterior cingulate, prelimbic, retrosplenial, and anterior insular cortical areas. Each HRF was faster and narrower than the canonical HRF and no significant difference was observed between these cortical regions. When used in general linear model analyses of corresponding fMRI data, the empirical HRFs showed better detection performance than the canonical HRF.

Conclusions: Our findings demonstrate the viability and utility of fiber-photometry-based HRF calculations. This platform is readily scalable to multiple simultaneous recording sites, and adaptable to study transfer functions between stimulation events, neuronal activity, neurotransmitter release, and hemodynamic responses.

Significance: Multiscale imaging holds particular relevance to neuroscience, where it helps integrate the cellular and molecular biological scale, which is most accessible to interventions, with holistic organ-level evaluations, most relevant with respect to function. Being inextricably interdisciplinary, multiscale imaging benefits substantially from incremental technology adoption, and a detailed overview of the state-of-the-art is vital to an informed application of imaging methods.

Aim: In this article, we lay out the background and methodological aspects of multimodal approaches combining functional magnetic resonance imaging (fMRI) with simultaneous optical measurement or stimulation.

Approach: We focus on optical techniques as these allow, in conjunction with genetically encoded proteins (e.g. calcium indicators or optical signal transducers), unprecedented read-out and control specificity for individual cell-types during fMRI experiments, while leveraging non-interfering modalities.

Results: A variety of different solutions for optical/fMRI methods has been reported ranging from bulk fluorescence recordings via fiber photometry to high resolution microscopy. In particular, the plethora of optogenetic tools has enabled the transformation of stimulus-evoked fMRI into a cell biological interrogation method. We discuss the capabilities and limitations of these genetically encoded molecular tools in the study of brain phenomena of great methodological and neuropsychiatric interest—such as neurovascular coupling (NVC) and neuronal network mapping. We provide a methodological description of this interdisciplinary field of study, and focus in particular on the limitations of the widely used blood oxygen level dependent (BOLD) signal and how multimodal readouts can shed light on the contributions arising from neurons, astrocytes, or the vasculature.

Conclusion: We conclude that information from multiple signaling pathways must be incorporated in future forward models of the BOLD response to prevent erroneous conclusions when using fMRI as a surrogate measure for neural activity. Further, we highlight the potential of direct neuronal stimulation via genetically defined brain networks towards advancing neurophysiological understanding and better estimating effective connectivity.

Neuromodulation poses an invaluable role in deciphering neural circuits and exploring clinical treatment of neurological diseases. Optoacoustic neuromodulation is an emerging modality benefiting from the merits of ultrasound with high penetration depth as well as the merits of photons with high spatial precision. We summarize recent development in a variety of optoacoustic platforms for neural modulation, including fiber, film, and nanotransducer-based devices, highlighting the key advantages of each platform. The possible mechanisms and main barriers for optoacoustics as a viable neuromodulation tool are discussed. Future directions in fundamental and translational research are proposed.

Simultaneously manipulating and monitoring both microscopic and macroscopic brain activity in vivo and identifying the linkage to behavior are powerful tools in neuroscience research. These capabilities have been realized with the recent technical advances of optogenetics and its combination with fMRI, here termed “opto-fMRI.” Opto-fMRI allows for targeted brain region-, cell-type-, or projection-specific manipulation and targeted Ca^2  + activity measurement to be linked with global brain signaling and behavior. We cover the history, technical advances, applications, and important considerations of opto-fMRI in anesthetized and awake rodents and the future directions of the combined techniques in neuroscience and neuroimaging.

The brain exists in a state of constant activity in the absence of any external sensory input. The spatiotemporal patterns of this spontaneous brain activity have been studied using various recording and imaging techniques. This has enabled considerable progress to be made in elucidating the cellular and network mechanisms that are involved in the observed spatiotemporal dynamics. This mini-review outlines different spatiotemporal dynamic patterns that have been identified in four commonly used modalities: electrophysiological recordings, optical imaging, functional magnetic resonance imaging, and electroencephalography. Signal sources for each modality, possible sources of the observed dynamics, and future directions are also discussed.

Diffusion of substances in the brain extracellular space (ECS) is important for extrasynaptic communication, extracellular ionic homeostasis, drug delivery, and metabolic waste clearance. However, substance diffusion is largely constrained by the geometry of brain ECS and the extracellular matrix. Investigating the diffusion properties of substances not only reveals the structural information of the brain ECS but also advances the understanding of intercellular signaling of brain cells. Among different techniques for substance diffusion measurement, the optical imaging method is sensitive and straightforward for measuring the dynamics and distribution of fluorescent molecules or sensors and has been used for molecular diffusion measurement in the brain. We mainly discuss recent advances of optical imaging-enabled measurements toward dynamic, anisotropic, high-resolution, and functional aspects of the brain ECS diffusion within the last 5 to 10 years. These developments are made possible by advanced imaging, such as light-sheet microscopy and single-particle tracking in tissue, and new fluorescent biosensors for neurotransmitters. We envision future efforts to map the ECS diffusivity across the brain under healthy and diseased conditions to guide the therapeutic delivery and better understand neurochemical transmissions that are relevant to physiological signaling and functions in brain circuits.

Brain functional connectivity based on the measure of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals has become one of the most widely used measurements in human neuroimaging. However, the nature of the functional networks revealed by BOLD fMRI can be ambiguous, as highlighted by a recent series of experiments that have suggested that typical resting-state networks can be replicated from purely vascular or physiologically driven BOLD signals. After going through a brief review of the key concepts of brain network analysis, we explore how the vascular and neuronal systems interact to give rise to the brain functional networks measured with BOLD fMRI. This leads us to emphasize a view of the vascular network not only as a confounding element in fMRI but also as a functionally relevant system that is entangled with the neuronal network. To study the vascular and neuronal underpinnings of BOLD functional connectivity, we consider a combination of methodological avenues based on multiscale and multimodal optical imaging in mice, used in combination with computational models that allow the integration of vascular information to explain functional connectivity.

Significance: Fluorescence resonance energy transfer (FRET) sensors offer enormous benefits when studying neurophysiology through confocal microscopy. Yet, their use for fiber-based in vivo recordings is hampered by massive confounding effects and has therefore been scarcely reported.

Aim: We aim to investigate whether in vivo fiber-based lactate recordings in the rodent brain are feasible with FRET sensors and implement a correction algorithm for the predominant hemodynamic artifact.

Approach: We performed fiber-based FRET recordings of lactate (Laconic) and calcium (Twitch-2B) simultaneously with functional MRI and pharmacological MRI. MR-derived parameters were applied to correct hemodynamic artifacts. Results of FRET measurements were validated by local field potential, magnetic resonance spectroscopy, and blood analysis.

Results: Hemodynamic artifacts dominated fiber-based in vivo FRET measurements with both Laconic and Twitch-2B. Our MR-based correction algorithm enabled to remove the artifacts and detect lactate and calcium changes during sensory stimulation or intravenous lactate injections.

Conclusions: In vivo fiber-based lactate recordings are feasible using FRET-based sensors. However, signal corrections are required. MR-derived hemodynamic parameters can successfully be applied for artifact correction.

Significance: Due to the vascular origin of the fMRI signal, the spatiotemporally precise interpretation of the blood oxygen level-dependent (BOLD) response as brain-wide correlate of neuronal activity is limited. Optical fiber-based neuronal calcium recordings provide a specific and temporally highly resolved signal yet lacking brain-wide coverage. The cross-modal integration of both modalities holds the potential for unique synergies.

Aim: The OPTO-MAgnetic Integration Concept (OPTOMAIC) extracts the very fraction of the BOLD response that reacts to optically recorded neuronal signals-of-interest.

Approach and Results: First, OPTOMAIC identifies the trials containing neuronal signal-of-interest (SoI) in the optical recordings. The long duration of the BOLD response is considered by calculating and thresholding neuronal interevent intervals. The resulting optical regression vector is probed for a positive BOLD response with single-event and single-voxel resolution, generating a BOLD response matrix containing only those events and voxels with both a neuronal SoI and a positive fMRI signal increase. Last, the onset of the BOLD response is being quantified, representing the section of the BOLD response most reliably reporting at least components of the neuronal signal.

Conclusions: The seven OPTOMAIC steps result in a brain-wide BOLD signature reflecting the underlying neuronal SoI with utmost cross-modal integration depth and taking full advantage of the specific strengths of each method.

Significance: Hyperspectral near-infrared spectroscopy (hsNIRS) combined with diffuse correlation spectroscopy (DCS) provides a noninvasive approach for monitoring cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO₂) and the oxidation state of cytochrome-c-oxidase (oxCCO). CMRO₂ is calculated by combining tissue oxygen saturation (S_tO₂) with CBF, whereas oxCCO can be measured directly by hsNIRS. Although both reflect oxygen metabolism, a direct comparison has yet to be studied.

Aim: We aim to investigate the relationship between CMRO₂ and oxCCO during periods of restricted oxygen delivery and lower metabolic demand.

Approach: A hybrid hsNIRS/DCS system was used to measure hemodynamic and metabolic responses in piglets exposed to cerebral ischemia and anesthetic-induced reductions in brain activity.

Results: Although a linear relationship was observed between CMRO₂ and oxCCO during ischemia, both exhibited a nonlinear relationship with respect to CBF. In contrast, linear correlation was sufficient to characterize the relationships between CMRO₂ and CBF and between the two metabolic markers during reduced metabolic demand.

Conclusions: The observed relationship between CMRO₂ and oxCCO during periods of restricted oxygen delivery and lower metabolic demand indicates that the two metabolic markers are strongly correlated.

Significance: Diffuse correlation spectroscopy (DCS) is an emerging noninvasive optical technology for bedside monitoring of cerebral blood flow. However, extracerebral hemodynamics can significantly influence DCS estimations of cerebral perfusion. Advanced analytical models can be used to remove the contribution of extracerebral hemodynamics; however, these models are highly sensitive to measurement noise. There is a need for an empirical determination of the optimal source–detector separation(s) (SDS) that improves the accuracy and reduces sensitivity to noise in the estimation of cerebral blood flow with these models.

Aim: To determine the influence of SDS on solution uniqueness, measurement accuracy, and sensitivity to inaccuracies in model parameters when using the three-layer model to estimate cerebral blood flow with DCS.

Approach: We performed a series of in silico simulations on samples spanning a wide range of physiologically-relevant layer optical properties, thicknesses, and flow. Data were simulated at SDS ranging from 0.5 to 3.0 cm using the three-layer solution to the correlation diffusion equation (with and without noise added) and using three-layer slab Monte Carlo simulations. We quantified the influence of SDS on uniqueness, accuracy, and sensitivity to inaccuracies in model parameters using the three-layer inverse model.

Results: Two SDS are required to ensure a unique solution of cerebral blood flow index (CBFi). Combinations of 0.5/1.0/1.5 and 2.5 cm provide the optimal choice for balancing the depth penetration with signal-to-noise ratio to minimize the error in CBFi across a wide range of samples with varying optical properties, thicknesses, and dynamics.

Conclusions: These results suggest that the choice of SDS is critical for minimizing the estimated error of cerebral blood flow when using the three-layer model to analyze DCS data.

Significance: Resting-state functional connectivity (RSFC) analyses of functional near-infrared spectroscopy (fNIRS) data reveal cortical connections and networks across the brain. Motion artifacts and systemic physiology in evoked fNIRS signals present unique analytical challenges, and methods that control for systemic physiological noise have been explored. Whether these same methods require modification when applied to resting-state fNIRS (RS-fNIRS) data remains unclear.

Aim: We systematically examined the sensitivity and specificity of several RSFC analysis pipelines to identify the best methods for correcting global systemic physiological signals in RS-fNIRS data.

Approach: Using numerically simulated RS-fNIRS data, we compared the rates of true and false positives for several connectivity analysis pipelines. Their performance was scored using receiver operating characteristic analysis. Pipelines included partial correlation and multivariate Granger causality, with and without short-separation measurements, and a modified multivariate causality model that included a non-traditional zeroth-lag cross term. We also examined the effects of pre-whitening and robust statistical estimators on performance.

Results: Consistent with previous work on bivariate correlation models, our results demonstrate that robust statistics and pre-whitening are effective methods to correct for motion artifacts and autocorrelation in the fNIRS time series. Moreover, we found that pre-filtering using principal components extracted from short-separation fNIRS channels as part of a partial correlation model was most effective in reducing spurious correlations due to shared systemic physiology when the two signals of interest fluctuated synchronously. However, when there was a temporal lag between the signals, a multivariate Granger causality test incorporating the short-separation channels was better. Since it is unknown if such a lag exists in experimental data, we propose a modified version of Granger causality that includes the non-traditional zeroth-lag term as a compromising solution.

Conclusions: A combination of pre-whitening, robust statistical methods, and partial correlation in the processing pipeline to reduce autocorrelation, motion artifacts, and global physiology are suggested for obtaining statistically valid connectivity metrics with RS-fNIRS. Further studies should validate the effectiveness of these methods using human data.

Significance: The critical closing pressure (CrCP) of cerebral circulation, as measured by diffuse correlation spectroscopy (DCS), is a promising biomarker of intracranial hypertension. However, CrCP techniques using DCS have not been assessed in gold standard experiments.

Aim: CrCP is typically calculated by examining the variation of cerebral blood flow (CBF) during the cardiac cycle (with normal sinus rhythm). We compare this typical CrCP measurement with a gold standard obtained during the drops in arterial blood pressure (ABP) caused by rapid ventricular pacing (RVP) in patients undergoing invasive electrophysiologic procedures.

Approach: Adults receiving electrophysiology procedures with planned ablation were enrolled for DCS CBF monitoring. CrCP was calculated from CBF and ABP data by three methods: (1) linear extrapolation of data during RVP (CrCP_RVP; the gold standard); (2) linear extrapolation of data during regular heartbeats (CrCP_Linear); and (3) fundamental harmonic Fourier filtering of data during regular heartbeats (CrCP_Fourier).

Results: CBF monitoring was performed prior to and during 55 episodes of RVP in five adults. CrCP_RVP and CrCP_Fourier demonstrated agreement (R = 0.66, slope = 1.05 (95%CI, 0.72 to 1.38). Agreement between CrCP_RVP and CrCP_Linear was worse; CrCP_Linear was 8.2 ± 5.9 mmHg higher than CrCP_RVP (mean ± SD; p < 0.001).

Conclusions: Our results suggest that DCS-measured CrCP can be accurately acquired during normal sinus rhythm.