Neurophotonics最新文献

Optical imaging has increasingly become the go-to technique for studying brain activity. The advancement of such approaches, which typically assess brain activity by monitoring the release or activity of second messengers, neurotransmitters, or electrical signals, has been entirely dependent on the development of sensors. Given advances in the field, a review of sensor development, including the latest sensors, is both timely and important for understanding their application in optical imaging. We seek to provide an overview of the sensors most commonly used by investigators to study brain function through optical imaging, including ${\mathrm{Ca}}^{2+}$ , voltage, and cAMP sensors, highlighting their developmental trajectory, applications, and relative strengths and weaknesses. We systematically reviewed the most recent publications that describe either the development or use of optical sensors in the context of brain imaging. We evaluated technical specifications and performance in real-life applications of these biosensors. We identified and highlighted sensors that have been characterized and widely adopted in various applications. We discussed their utility, kinetics, and practical advantages and disadvantages. Because of their more advanced development, ${\mathrm{Ca}}^{2+}$ sensors receive more extensive consideration in our discussion. Overall, we reveal a plethora of available sensors that allow investigators to examine brain activity based on ${\mathrm{Ca}}^{2+}$ dynamics, cAMP activity, and electrical activity. Although further development is needed, the substantial progress in optical imaging, which is critically enabled by advances in sensor technology, is evident. These tools collectively provide researchers with powerful new capabilities to visualize and dissect the complex dynamics of brain function.

Significance: Pyruvate is a nodal intermediate in cellular metabolism, positioned at the crossroads between glycolysis and fermentative metabolism. It is exchanged between the intracellular and extracellular compartments through the proton-coupled monocarboxylate transporters and between the cytosol and mitochondria through the mitochondrial pyruvate carrier, where it serves as a primary carbon source for respiration.

Aim: Our goal is to present a detailed protocol for quantifying cytosolic pyruvate concentration in neurons at single-cell resolution using a minimally invasive, two-point calibration approach with the Förster Resonance Energy Transfer (FRET)-based genetically encoded fluorescent indicator Pyronic.

Approach: This protocol is based on a noninvasive pharmacological two-point calibration approach, where Pyronic's dynamic range ( $\Delta R_{\mathrm{MAX}}$ ) is established by withdrawing all extracellular substrates to deplete intracellular pyruvate ( $R_{\mathrm{MIN}}$ ) and by inducing Pyronic saturation ( $R_{\mathrm{MAX}}$ ) through the combination of inhibition of pyruvate export, stimulation of its production, and blockade of its mitochondrial consumption. The protocol also incorporates the previously published $K_D$ values for Pyronic obtained from in vitro experiments. This procedure does not require the use of detergents to permeabilize the cells.

Results: Implementing this protocol enables the measurement of absolute cytosolic pyruvate concentrations. This quantitative parameter facilitates comparisons of pyruvate metabolism across different cells, samples, and experimental batches, thereby enabling the comparison between a plethora of experimental conditions.

Conclusion: The FRET-based fluorescent indicator Pyronic can be reliably calibrated using a minimally invasive, pharmacology-based two-point calibration protocol in neurons, thus providing a robust and quantitative method to study pyruvate metabolism under various physiological and pathological scenarios.

The brain depends on highly regulated moment-to-moment changes in regional blood supply to support its energetically demanding cognitive function with a limited energy budget. To efficiently match energetic supply to demand, neural activity rapidly increases regional blood flow. This process, known as neurovascular coupling (NVC), represents a particularly sophisticated form of functional hyperemia in the central nervous system, distinguished by its exceptional spatial precision. This feature of the cerebral vasculature generates a spatial and temporal relationship between neuronal activity and vasomotion. Although NVC is widely accepted to be essential for normal brain function and health, it remains poorly understood how NVC supports neuronal function and cognition. This review describes the current understanding of molecular and cellular mechanisms underlying NVC. We will also discuss the potential physiological functions of neurovascular coupling in normal brain function with a focus on energy supply to neural cells. Finally, the impact of neurovascular dysregulation on neurological disorders and the future outlook will be discussed.

Significance: Investigating blood microcirculation is important to better understand cardiovascular, metabolic, and neurodegenerative diseases. Although visualization of microcirculation has traditionally relied on the injection of short-lived fluorescent tracers, this approach poses challenges for experiments in awake animals or long-term imaging. To address these limitations, we previously developed a genetically encoded fluorescent plasma label that enables stable, minimally invasive in vivo visualization of vascular dynamics. Further optimizing its versatility and delivery will expand its utility in neuroscience and across diverse areas of biomedical research.

Aim: We aim to extend the utility of genetically encoded plasma labeling by testing brighter, more photostable fluorescent proteins and evaluating strategies to enhance adeno-associated viral (AAV)-mediated expression.

Approach: AAV8 vectors encoding albumin fused to mNeonGreen or StayGold variants were administered systemically. Expression levels were tracked via blood sampling, and the effects of secondary AAV injection and immunomodulation were tested.

Results: Alb-mStayGold showed improved photostability but lower brightness than Alb-mNeonGreen. Secondary intraperitoneal AAV delivery successfully induced transgene expression even after prior AAV exposure. Moreover, higher AAV8-induced plasma label expression in males is confirmed. Immunosuppressant treatment increased plasma fluorescence, whereas neonatal AAV injection failed to induce tolerance.

Conclusion: Photostable plasma labeling and immune modulation strategies expand the applicability of AAV-based vascular imaging.

Nervous system tissue is the most metabolically active in the body and neurons are the primary consumers of oxygen and metabolites in nervous tissue. Many processes support neuronal metabolism, and dysregulation of these processes or intrinsic neuronal metabolism is often tied to neurodegenerative diseases. While many techniques are available to query metabolic function and disease (e.g. Seahorse XF, histology, immunostaining), almost all of these approaches are destructive and few offer cellular resolution. However, genetically encoded biosensors can optically measure metabolic features in any tissue with optical access. Biosensors represent an approach to non-destructively monitor metabolic components and regulatory signaling repeatedly over time in intact tissues. In this review, we discuss the application of genetically encoded biosensors that measure metabolites and metabolic processes as applied to studies of neurodegeneration.

Significance: In recent years, functional near-infrared spectroscopy (fNIRS) has gained increasing attention in the field of neurofeedback. However, there is a lack of freely accessible tools for research in this area that reflect the state of the art in research and technology.

Aim: To address this need, we introduce Non-commercial Interface for Neuro-Feedback Acquisitions (NINFA), a user-friendly and flexible freely available neurofeedback application for real-time fNIRS, which is also open to other modalities such as electroencephalography (EEG).

Approach: NINFA was developed in MATLAB and the lab streaming layer connection offers maximum flexibility in terms of combination with different fNIRS or EEG acquisition software and hardware.

Results: The user-friendly interface allows measurements without requiring programming expertise. New neurofeedback protocols can be easily created, saved, and retrieved. We provide an example code for real-time data preprocessing and visual feedback; however, users can customize or expand it with appropriate programming skills.

Conclusions: NINFA enables real-time recording, analysis, and feedback of brain signals. We were able to demonstrate the stability and reliability of the computational performance of preprocessing and analysis methods in the current version. NINFA is intended as an application that can, should, and may evolve with the help of contributions from the community.

Significance: In vivo one-photon fluorescence imaging of calcium and voltage indicators expressed in neurons enables noninvasive recordings of neural activity with submillisecond precision. However, data acquisition speed is limited by the frame rate of cameras.

Aim: We developed a compressive streak fluorescence microscope to record fluorescence in individual neurons at high speeds ( $\ge 200$ frames per second) exceeding the nominal frame rate of the camera by trading off spatial pixels for temporal resolution.

Approach: Our microscope leverages a digital micromirror device for targeted illumination, a galvo mirror for temporal scanning, and a ridge regression algorithm for fast computational reconstruction of fluorescence traces with high temporal resolution.

Results: In simulations, the ridge regression algorithm reconstructs traces of high temporal resolution with limited signal loss. Validation experiments with fluorescent beads and experiments in larval zebrafish demonstrate accurate reconstruction with a data compression ratio of 10 and accurate recordings of neural activity with 200- to 400-Hz sampling speeds.

Conclusions: Our compressive microscopy enables new experimental capabilities to monitor activity at a sampling speed that outpaces the nominal frame rate of the camera.

Significance: The highly scattering nature of near-infrared light in human tissue makes it challenging to collect photons using source-detector separations larger than several centimeters. The limits of detectability of light transmitted through the head remain unknown. Detecting photons in the extreme case through an entire adult head explores the limits of photon transport in the brain.

Aim: We explore the physical limits of photon transport in the head in the extreme case wherein the source and detector are diametrically opposite.

Approach: Simulations uncover possible migration pathways of photons from source to detector. We compare simulations with time-resolved photon counting experiments that measure pulsed light transmitted through the head.

Results: We observe good agreement between the peak delay time and width of the time-correlated histograms in experiments and simulations. Analysis of the photon migration pathways indicates sensitivity to regions of the brain well beyond accepted limits. Source repositioning can isolate sensitivity to targeted regions of the brain, including under the cerebrum.

Conclusions: We overcome attenuation of $\sim {10}^{18}$ and detect photons transmitted through an entire adult human head for a subject with fair skin and no hair. Photons measured in this regime explore regions of the brain currently inaccessible with noninvasive optical brain imaging.

Significance: Fiber photometry is a powerful tool for neuroscience. However, measured biosensor signals are contaminated by various artifacts (photobleaching and movement-related noise) that undermine analysis and interpretation. Currently, no universal pipeline exists to deal with these artifacts.

Aim: We aim to evaluate approaches for obtaining artifact-corrected neural dynamic signals from fiber photometry data and provide recommendations for photometry analysis pipelines.

Approach: Using simulated and real photometry data, we tested the effects of three key analytical decisions: choice of regression for fitting isosbestic control signals onto experimental signals [ordinary least squares (OLS) versus iteratively reweighted least squares (IRLS)], low-pass filtering, and dF/F versus dF calculations.

Results: IRLS surpassed OLS regression for fitting isosbestic control signals to experimental signals. We also demonstrate the efficacy of low-pass filtering signals and baseline normalization via dF/F calculations.

Conclusions: We conclude that artifact-correcting experimental signals via low-pass filter, IRLS regression, and dF/F calculations is a superior approach to commonly used alternatives. We suggest these as a new standard for preprocessing signals across photometry analysis pipelines.