Real-time 3D movement correction for two-photon imaging in behaving animals

Neurophotonics beyond the surface: unmasking the brain's complexity exploiting optical scattering

The intricate nature of the brain necessitates the application of advanced probing techniques to comprehensively study and understand its working mechanisms. Neurophotonics offers minimally invasive methods to probe the brain using optics at cellular and even molecular levels. However, multiple challenges persist, especially concerning imaging depth, field of view, speed, and biocompatibility. A major hindrance to solving these challenges in optics is the scattering nature of the brain. This perspective highlights the potential of complex media optics, a specialized area of study focused on light propagation in materials with intricate heterogeneous optical properties, in advancing and improving neuronal readouts for structural imaging and optical recordings of neuronal activity. Key strategies include wavefront shaping techniques and computational imaging and sensing techniques that exploit scattering properties for enhanced performance. We discuss the potential merger of the two fields as well as potential challenges and perspectives toward longer term in vivo applications.

Closed-loop experiments and brain machine interfaces with multiphoton microscopy

In the field of neuroscience, the importance of constructing closed-loop experimental systems has increased in conjunction with technological advances in measuring and controlling neural activity in live animals. We provide an overview of recent technological advances in the field, focusing on closed-loop experimental systems where multiphoton microscopy-the only method capable of recording and controlling targeted population activity of neurons at a single-cell resolution in vivo-works through real-time feedback. Specifically, we present some examples of brain machine interfaces (BMIs) using in vivo two-photon calcium imaging and discuss applications of two-photon optogenetic stimulation and adaptive optics to real-time BMIs. We also consider conditions for realizing future optical BMIs at the synaptic level, and their possible roles in understanding the computational principles of the brain.

Acousto-optic holography for pseudo-two-dimensional dynamic light patterning

Optical systems use acousto-optic deflectors (AODs) mostly for fast angular scanning and spectral filtering of laser beams. However, AODs may transform laser light in much broader ways. When time-locked to the pulsing of low repetition rate laser amplifiers, AODs permit the holographic reconstruction of 1D and pseudo-two-dimensional (ps2D) intensity objects of rectangular shape by controlling the amplitude and phase of the light field at high (20-200 kHz) rates for microscopic light patterning. Using iterative Fourier transformations (IFTs), we searched for AOD-compatible holograms to reconstruct the given ps2D target patterns through either phase-only or complex light field modulation. We previously showed that phase-only holograms can adequately render grid-like patterns of diffraction-limited points with non-overlapping diffraction orders, while side lobes to the target pattern can be cured with an apodization mask. Dense target patterns, in contrast, are typically encumbered by apodization-resistant speckle noise. Here, we show the denoised rendering of dense ps2D objects by complex acousto-optic holograms deriving from simultaneous optimization of the amplitude and phase of the light field. Target patterns lacking ps2D symmetry, although not translatable into single holograms, were accessed by serial holography based on a segregation into ps2D-compatible components. The holograms retrieved under different regularizations were experimentally validated in an AOD random-access microscope. IFT regularizations characterized in this work extend the versatility of acousto-optic holography for fast dynamic light patterning.

Neurophotonics beyond the Surface: Unmasking the Brain's Complexity Exploiting Optical Scattering

The intricate nature of the brain necessitates the application of advanced probing techniques to comprehensively study and understand its working mechanisms. Neurophotonics offers minimally invasive methods to probe the brain using optics at cellular and even molecular levels. However, multiple challenges persist, especially concerning imaging depth, field of view, speed, and biocompatibility. A major hindrance to solving these challenges in optics is the scattering nature of the brain. This perspective highlights the potential of complex media optics, a specialized area of study focused on light propagation in materials with intricate heterogeneous optical properties, in advancing and improving neuronal readouts for structural imaging and optical recordings of neuronal activity. Key strategies include wavefront shaping techniques and computational imaging and sensing techniques that exploit scattering properties for enhanced performance. We discuss the potential merger of the two fields as well as potential challenges and perspectives toward longer term in vivo applications.

Unravelling Immune-Inflammatory Responses and Lysosomal Adaptation: Insights from Two-Photon Excited Delayed Fluorescence Imaging

Two-photon excitation (TPE) microscopy with near-infrared (NIR) emission has emerged as a promising technique for deep-tissue optical imaging. Recent developments in fluorescence lifetime imaging with long-lived emission probes have further enhanced the spatial resolution and precision of fluorescence imaging, especially in complex systems with short-lived background signals. In this study, two innovative lysosome-targeting probes, Cz-NA and tCz-NA, are introduced. These probes offer a combination of advantages, including TPE (λex = 880 nm), NIR emission (λem = 650 nm), and thermally activated delayed fluorescence (TADF) with long-lived lifetimes (1.05 and 1.71 µs, respectively). These characteristics significantly improve the resolution and signal-to-noise ratio in deep-tissue imaging. By integrating an acousto-optic modulator (AOM) device with TPE microscopy, the authors successfully applied Cz-NA in two-photon excited delayed fluorescence (TPEDF) imaging to track lysosomal adaptation and immune responses to inflammation in mice. This study sheds light on the relationship between lysosome tubulation, innate immune responses, and inflammation in vivo, providing valuable insights for the development of autofluorescence-free molecular probes in the future.

Deep-brain optical recording of neural dynamics during behavior

In vivo fluorescence recording techniques have produced landmark discoveries in neuroscience, providing insight into how single cell and circuit-level computations mediate sensory processing and generate complex behaviors. While much attention has been given to recording from cortical brain regions, deep-brain fluorescence recording is more complex because it requires additional measures to gain optical access to harder to reach brain nuclei. Here we discuss detailed considerations and tradeoffs regarding deep-brain fluorescence recording techniques and provide a comprehensive guide for all major steps involved, from project planning to data analysis. The goal is to impart guidance for new and experienced investigators seeking to use in vivo deep fluorescence optical recordings in awake, behaving rodent models.

Two-photon microscopy: application advantages and latest progress for in vivo imaging of neurons and blood vessels after ischemic stroke

Two-photon microscopy (TPM) plays an important role in the study of the changes of the two important components of neurovascular units (NVU) - neurons and blood vessels after ischemic stroke (IS). IS refers to sudden neurological dysfunction caused by focal cerebral ischemia, which is one of the leading causes of death and disability worldwide. TPM is a new and rapidly developing high-resolution real-time imaging technique used in vivo that has attracted increasing attention from scientists in the neuroscience field. Neurons and blood vessels are important components of neurovascular units, and they undergo great changes after IS to respond to and compensate for ischemic injury. Here, we introduce the characteristics and pre-imaging preparations of TPM, and review the common methods and latest progress of TPM in the neuronal and vascular research for injury and recovery of IS in recent years. With the review, we clearly recognized that the most important advantage of TPM in the study of ischemic stroke is the ability to perform chronic longitudinal imaging of different tissues at a high resolution in vivo. Finally, we discuss the limitations of TPM and the technological advances in recent years.

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.

High-speed low-light in vivo two-photon voltage imaging of large neuronal populations

Monitoring spiking activity across large neuronal populations at behaviorally relevant timescales is critical for understanding neural circuit function. Unlike calcium imaging, voltage imaging requires kilohertz sampling rates that reduce fluorescence detection to near shot-noise levels. High-photon flux excitation can overcome photon-limited shot noise, but photobleaching and photodamage restrict the number and duration of simultaneously imaged neurons. We investigated an alternative approach aimed at low two-photon flux, which is voltage imaging below the shot-noise limit. This framework involved developing positive-going voltage indicators with improved spike detection (SpikeyGi and SpikeyGi2); a two-photon microscope ('SMURF') for kilohertz frame rate imaging across a 0.4 mm × 0.4 mm field of view; and a self-supervised denoising algorithm (DeepVID) for inferring fluorescence from shot-noise-limited signals. Through these combined advances, we achieved simultaneous high-speed deep-tissue imaging of more than 100 densely labeled neurons over 1 hour in awake behaving mice. This demonstrates a scalable approach for voltage imaging across increasing neuronal populations.

Multi-neuronal recording in unrestrained animals with all acousto-optic random-access line-scanning two-photon microscopy

To understand how neural activity encodes and coordinates behavior, it is desirable to record multi-neuronal activity in freely behaving animals. Imaging in unrestrained animals is challenging, especially for those, like larval Drosophila melanogaster, whose brains are deformed by body motion. A previously demonstrated two-photon tracking microscope recorded from individual neurons in freely crawling Drosophila larvae but faced limits in multi-neuronal recording. Here we demonstrate a new tracking microscope using acousto-optic deflectors (AODs) and an acoustic GRIN lens (TAG lens) to achieve axially resonant 2D random access scanning, sampling along arbitrarily located axial lines at a line rate of 70 kHz. With a tracking latency of 0.1 ms, this microscope recorded activities of various neurons in moving larval Drosophila CNS and VNC including premotor neurons, bilateral visual interneurons, and descending command neurons. This technique can be applied to the existing two-photon microscope to allow for fast 3D tracking and scanning.

Parallel functional architectures within a single dendritic tree

The input-output transformation of individual neurons is a key building block of neural circuit dynamics. While previous models of this transformation vary widely in their complexity, they all describe the underlying functional architecture as unitary, such that each synaptic input makes a single contribution to the neuronal response. Here, we show that the input-output transformation of CA1 pyramidal cells is instead best captured by two distinct functional architectures operating in parallel. We used statistically principled methods to fit flexible, yet interpretable, models of the transformation of input spikes into the somatic "output" voltage and to automatically select among alternative functional architectures. With dendritic Na+ channels blocked, responses are accurately captured by a single static and global nonlinearity. In contrast, dendritic Na+-dependent integration requires a functional architecture with multiple dynamic nonlinearities and clustered connectivity. These two architectures incorporate distinct morphological and biophysical properties of the neuron and its synaptic organization.

A cranial implant for stabilizing whole-cell patch-clamp recordings in behaving rodents

BACKGROUND

In vivo patch-clamp recording techniques provide access to the sub- and suprathreshold membrane potential dynamics of individual neurons during behavior. However, maintaining recording stability throughout behavior is a significant challenge, and while methods for head restraint are commonly used to enhance stability, behaviorally related brain movement relative to the skull can severely impact the success rate and duration of whole-cell patch-clamp recordings.

NEW METHOD

We developed a low-cost, biocompatible, and 3D-printable cranial implant capable of locally stabilizing brain movement, while permitting equivalent access to the brain when compared to a conventional craniotomy.

RESULTS

Experiments in head-restrained behaving mice demonstrate that the cranial implant can reliably reduce the amplitude and speed of brain displacements, significantly improving the success rate of recordings across repeated bouts of motor behavior.

COMPARISON WITH EXISTING METHOD(S)

Our solution offers an improvement on currently available strategies for brain stabilization. Due to its small size, the implant can be retrofitted to most in vivo electrophysiology recording setups, providing a low cost, easily implementable solution for increasing intracellular recording stability in vivo.

CONCLUSIONS

By facilitating stable whole-cell patch-clamp recordings in vivo, biocompatible 3D printed implants should accelerate the investigation of single neuron computations underlying behavior.

Review on data analysis methods for mesoscale neural imaging in vivo

Significance: Mesoscale neural imaging in vivo has gained extreme popularity in neuroscience for its capacity of recording large-scale neurons in action. Optical imaging with single-cell resolution and millimeter-level field of view in vivo has been providing an accumulated database of neuron-behavior correspondence. Meanwhile, optical detection of neuron signals is easily contaminated by noises, background, crosstalk, and motion artifacts, while neural-level signal processing and network-level coordinate are extremely complicated, leading to laborious and challenging signal processing demands. The existing data analysis procedure remains unstandardized, which could be daunting to neophytes or neuroscientists without computational background. Aim: We hope to provide a general data analysis pipeline of mesoscale neural imaging shared between imaging modalities and systems. Approach: We divide the pipeline into two main stages. The first stage focuses on extracting high-fidelity neural responses at single-cell level from raw images, including motion registration, image denoising, neuron segmentation, and signal extraction. The second stage focuses on data mining, including neural functional mapping, clustering, and brain-wide network deduction. Results: Here, we introduce the general pipeline of processing the mesoscale neural images. We explain the principles of these procedures and compare different approaches and their application scopes with detailed discussions about the shortcomings and remaining challenges. Conclusions: There are great challenges and opportunities brought by the large-scale mesoscale data, such as the balance between fidelity and efficiency, increasing computational load, and neural network interpretability. We believe that global circuits on single-neuron level will be more extensively explored in the future.

Software for non-parametric image registration of 2-photon imaging data

Functional 2-photon microscopy is a key technology for imaging neuronal activity. The recorded image sequences, however, can contain non-rigid movement artifacts which requires high-accuracy movement correction. Variational optical flow (OF) estimation is a group of methods for motion analysis with established performance in many computer vision areas. However, it has yet to be adapted to the statistics of 2-photon neuroimaging data. In this work, we present the motion compensation method Flow-Registration that outperforms previous alignment tools and allows to align and reconstruct even low signal-to-noise ratio 2-photon imaging data and is able to compensate high-divergence displacements during local drug injections. The method is based on statistics of such data and integrates previous advances in variational OF estimation. Our method is available as an easy-to-use ImageJ/FIJI plugin as well as a MATLAB toolbox with modular, object oriented file IO, native multi-channel support and compatibility with existing 2-photon imaging suites.

An Open-Source Real-Time Motion Correction Plug-In for Single-Photon Calcium Imaging of Head-Mounted Microscopy

Single-photon-based head-mounted microscopy is widely used to record the brain activities of freely-moving animals. However, during data acquisition, the free movement of animals will cause shaking in the field of view, which deteriorates subsequent neural signal analyses. Existing motion correction methods applied to calcium imaging data either focus on offline analyses or lack sufficient accuracy in real-time processing for single-photon data. In this study, we proposed an open-source real-time motion correction (RTMC) plug-in for single-photon calcium imaging data acquisition. The RTMC plug-in is a real-time subpixel registration algorithm that can run GPUs in UCLA Miniscope data acquisition software. When used with the UCLA Miniscope, the RTMC algorithm satisfies real-time processing requirements in terms of speed, memory, and accuracy. We tested the RTMC algorithm by extending a manual neuron labeling function to extract calcium signals in a real experimental setting. The results demonstrated that the neural calcium dynamics and calcium events can be restored with high accuracy from the calcium data that were collected by the UCLA Miniscope system embedded with our RTMC plug-in. Our method could become an essential component in brain science research, where real-time brain activity is needed for closed-loop experiments.

Smart imaging to empower brain-wide neuroscience at single-cell levels

A deep understanding of the neuronal connectivity and networks with detailed cell typing across brain regions is necessary to unravel the mechanisms behind the emotional and memorial functions as well as to find the treatment of brain impairment. Brain-wide imaging with single-cell resolution provides unique advantages to access morphological features of a neuron and to investigate the connectivity of neuron networks, which has led to exciting discoveries over the past years based on animal models, such as rodents. Nonetheless, high-throughput systems are in urgent demand to support studies of neural morphologies at larger scale and more detailed level, as well as to enable research on non-human primates (NHP) and human brains. The advances in artificial intelligence (AI) and computational resources bring great opportunity to 'smart' imaging systems, i.e., to automate, speed up, optimize and upgrade the imaging systems with AI and computational strategies. In this light, we review the important computational techniques that can support smart systems in brain-wide imaging at single-cell resolution.

Imaging whole-brain activity to understand behavior

The brain evolved to produce behaviors that help an animal inhabit the natural world. During natural behaviors, the brain is engaged in many levels of activity from the detection of sensory inputs to decision-making to motor planning and execution. To date, most brain studies have focused on small numbers of neurons that interact in limited circuits. This allows analyzing individual computations or steps of neural processing. During behavior, however, brain activity must integrate multiple circuits in different brain regions. The activities of different brain regions are not isolated, but may be contingent on one another. Coordinated and concurrent activity within and across brain areas is organized by (1) sensory information from the environment, (2) the animal's internal behavioral state, and (3) recurrent networks of synaptic and non-synaptic connectivity. Whole-brain recording with cellular resolution provides a new opportunity to dissect the neural basis of behavior, but whole-brain activity is also mutually contingent on behavior itself. This is especially true for natural behaviors like navigation, mating, or hunting, which require dynamic interaction between the animal, its environment, and other animals. In such behaviors, the sensory experience of an unrestrained animal is actively shaped by its movements and decisions. Many of the signaling and feedback pathways that an animal uses to guide behavior only occur in freely moving animals. Recent technological advances have enabled whole-brain recording in small behaving animals including nematodes, flies, and zebrafish. These whole-brain experiments capture neural activity with cellular resolution spanning sensory, decision-making, and motor circuits, and thereby demand new theoretical approaches that integrate brain dynamics with behavioral dynamics. Here, we review the experimental and theoretical methods that are being employed to understand animal behavior and whole-brain activity, and the opportunities for physics to contribute to this emerging field of systems neuroscience.

Fast and Accurate Motion Correction for Two-Photon Ca2+ Imaging in Behaving Mice

Two-photon Ca2+ imaging is a widely used technique for investigating brain functions across multiple spatial scales. However, the recording of neuronal activities is affected by movement of the brain during tasks in which the animal is behaving normally. Although post-hoc image registration is the commonly used approach, the recent developments of online neuroscience experiments require real-time image processing with efficient motion correction performance, posing new challenges in neuroinformatics. We propose a fast and accurate image density feature-based motion correction method to address the problem of imaging animal during behaviors. This method is implemented by first robustly estimating and clustering the density features from two-photon images. Then, it takes advantage of the temporal correlation in imaging data to update features of consecutive imaging frames with efficient calculations. Thus, motion artifacts can be quickly and accurately corrected by matching the features and obtaining the transformation parameters for the raw images. Based on this efficient motion correction strategy, our algorithm yields promising computational efficiency on imaging datasets with scales ranging from dendritic spines to neuronal populations. Furthermore, we show that the proposed motion correction method outperforms other methods by evaluating not only computational speed but also the quality of the correction performance. Specifically, we provide a powerful tool to perform motion correction for two-photon Ca2+ imaging data, which may facilitate online imaging experiments in the future.

A Model of Discovery: The Role of Imaging Established and Emerging Non-mammalian Models in Neuroscience

Rodents have been the dominant animal models in neurobiology and neurological disease research over the past 60 years. The prevalent use of rats and mice in neuroscience research has been driven by several key attributes including their organ physiology being more similar to humans, the availability of a broad variety of behavioral tests and genetic tools, and widely accessible reagents. However, despite the many advances in understanding neurobiology that have been achieved using rodent models, there remain key limitations in the questions that can be addressed in these and other mammalian models. In particular, in vivo imaging in mammals at the cell-resolution level remains technically difficult and demands large investments in time and cost. The simpler nervous systems of many non-mammalian models allow for precise mapping of circuits and even the whole brain with impressive subcellular resolution. The types of non-mammalian neuroscience models available spans vertebrates and non-vertebrates, so that an appropriate model for most cell biological questions in neurodegenerative disease likely exists. A push to diversify the models used in neuroscience research could help address current gaps in knowledge, complement existing rodent-based bodies of work, and bring new insight into our understanding of human disease. Moreover, there are inherent aspects of many non-mammalian models such as lifespan and tissue transparency that can make them specifically advantageous for neuroscience studies. Crispr/Cas9 gene editing and decreased cost of genome sequencing combined with advances in optical microscopy enhances the utility of new animal models to address specific questions. This review seeks to synthesize current knowledge of established and emerging non-mammalian model organisms with advances in cellular-resolution in vivo imaging techniques to suggest new approaches to understand neurodegeneration and neurobiological processes. We will summarize current tools and in vivo imaging approaches at the single cell scale that could help lead to increased consideration of non-mammalian models in neuroscience research.

Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging

Two-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion-related intensity changes or motion artifacts can typically not be separated from neural activity-induced signals. While lateral motion, within the focal plane, can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected. Here, we developed an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using temporally multiplexed beams, recording simultaneously from at least two focal planes at different z positions, and recording a z-stack for each beam as a calibration step, the algorithm separates motion-related and neural activity-induced changes in fluorescence intensity. The algorithm is based on a maximum likelihood optimisation approach; it assumes (as a first order approximation) that no distortions of the sample occurs during axial motion and that neural activity increases uniformly along the optical axis in each region of interest. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.

An Easily Compatible Eye-tracking System for Freely-moving Small Animals

Measuring eye movement is a fundamental approach in cognitive science as it provides a variety of insightful parameters that reflect brain states such as visual attention and emotions. Combining eye-tracking with multimodal neural recordings or manipulation techniques is beneficial for understanding the neural substrates of cognitive function. Many commercially-available and custom-built systems have been widely applied to awake, head-fixed small animals. However, the existing eye-tracking systems used in freely-moving animals are still limited in terms of their compatibility with other devices and of the algorithm used to detect eye movements. Here, we report a novel system that integrates a general-purpose, easily compatible eye-tracking hardware with a robust eye feature-detection algorithm. With ultra-light hardware and a detachable design, the system allows for more implants to be added to the animal's exposed head and has a precise synchronization module to coordinate with other neural implants. Moreover, we systematically compared the performance of existing commonly-used pupil-detection approaches, and demonstrated that the proposed adaptive pupil feature-detection algorithm allows the analysis of more complex and dynamic eye-tracking data in free-moving animals. Synchronized eye-tracking and electroencephalogram recordings, as well as algorithm validation under five noise conditions, suggested that our system is flexibly adaptable and can be combined with a wide range of neural manipulation and recording technologies.

Advanced high resolution three-dimensional imaging to visualize the cerebral neurovascular network in stroke

As an important method to accurately and timely diagnose stroke and study physiological characteristics and pathological mechanism in it, imaging technology has gone through more than a century of iteration. The interaction of cells densely packed in the brain is three-dimensional (3D), but the flat images brought by traditional visualization methods show only a few cells and ignore connections outside the slices. The increased resolution allows for a more microscopic and underlying view. Today's intuitive 3D imagings of micron or even nanometer scale are showing its essentiality in stroke. In recent years, 3D imaging technology has gained rapid development. With the overhaul of imaging mediums and the innovation of imaging mode, the resolution has been significantly improved, endowing researchers with the capability of holistic observation of a large volume, real-time monitoring of tiny voxels, and quantitative measurement of spatial parameters. In this review, we will summarize the current methods of high-resolution 3D imaging applied in stroke.

Fluorescence imaging of large-scale neural ensemble dynamics

Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca²⁺ imaging studies of neural activity can track brain area interactions and distributed information processing at cellular resolution. Across smaller spatial scales, high-speed voltage imaging reveals the distinctive spiking patterns and coding properties of targeted neuron types. Collectively, these innovations will propel studies of brain function and dovetail with ongoing neuroscience initiatives to identify new neuron types and develop widely applicable, non-human primate models. The optical toolkit's growing sophistication also suggests that "brain observatory" facilities would be useful open resources for future brain-imaging studies.

Fast optical recording of neuronal activity by three-dimensional custom-access serial holography

Optical recording of neuronal activity in three-dimensional (3D) brain circuits at cellular and millisecond resolution in vivo is essential for probing information flow in the brain. While random-access multiphoton microscopy permits fast optical access to neuronal targets in three dimensions, the method is challenged by motion artifacts when recording from behaving animals. Therefore, we developed three-dimensional custom-access serial holography (3D-CASH). Built on a fast acousto-optic light modulator, 3D-CASH performs serial sampling at 40 kHz from neurons at freely selectable 3D locations. Motion artifacts are eliminated by targeting each neuron with a size-optimized pattern of excitation light covering the cell body and its anticipated displacement field. Spike rates inferred from GCaMP6f recordings in visual cortex of awake mice tracked the phase of a moving bar stimulus with higher spike correlation between intra compared to interlaminar neuron pairs. 3D-CASH offers access to the millisecond correlation structure of in vivo neuronal activity in 3D microcircuits.

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.

Quantitative Pulmonary Neutrophil Dynamics Using Computer-Vision Stabilized Intravital Imaging

In vivo intravital imaging in animal models in the lung remains challenging owing to respiratory motion artifacts. Here we describe a novel intravital imaging approach based on the computer-vision stabilization algorithm, Computer-Vision Stabilized Intravital Imaging. This method corrects lung movements and deformations at submicron precision in respiring mouse lungs. The precision enables high-throughput quantitative analysis of intravital pulmonary polymorphonuclear neutrophil (PMN) dynamics in lungs. We quantified real-time PMN patrolling dynamics of microvessels in the basal state and PMN recruitment resulting from sequestration in a model of endotoxemia in mice. We focused on determining the marginated pool of PMNs in the lung. Direct visualization of marginated PMNs revealed that they are not static but highly dynamic and undergo repeated cycles of "catch and release." PMNs briefly arrest in larger diameter capillary junction (∼10 μm) and then squeeze into narrower, approximately 5-μm diameter vessels through PMN deformation. We also observed that the sequestered PMNs in lung microvessels lost their migratory capabilities in association with cell morphological change following prolonged endotoxemia. These observations underscore the value of direct visualization and quantitative analysis of PMN dynamics in lungs to study PMN physiology and pathophysiology and role in inflammatory lung injury.

Cross-modal coherent registration of whole mouse brains

Recent whole-brain mapping projects are collecting large-scale three-dimensional images using modalities such as serial two-photon tomography, fluorescence micro-optical sectioning tomography, light-sheet fluorescence microscopy, volumetric imaging with synchronous on-the-fly scan and readout or magnetic resonance imaging. Registration of these multi-dimensional whole-brain images onto a standard atlas is essential for characterizing neuron types and constructing brain wiring diagrams. However, cross-modal image registration is challenging due to intrinsic variations of brain anatomy and artifacts resulting from different sample preparation methods and imaging modalities. We introduce a cross-modal registration method, mBrainAligner, which uses coherent landmark mapping and deep neural networks to align whole mouse brain images to the standard Allen Common Coordinate Framework atlas. We build a brain atlas for the fluorescence micro-optical sectioning tomography modality to facilitate single-cell mapping, and used our method to generate a whole-brain map of three-dimensional single-neuron morphology and neuron cell types.

Large-scale voltage imaging in behaving mice using targeted illumination

Recent improvements in genetically encoded voltage indicators enabled optical imaging of action potentials and subthreshold transmembrane voltage in vivo. To perform high-speed voltage imaging of many neurons simultaneously over a large anatomical area, widefield microscopy remains an essential tool. However, the lack of optical sectioning makes widefield microscopy prone to background cross-contamination. We implemented a digital-micromirror-device-based targeted illumination strategy to restrict illumination to the cells of interest and quantified the resulting improvement both theoretically and experimentally with SomArchon expressing neurons. We found that targeted illumination increased SomArchon signal contrast, decreased photobleaching, and reduced background cross-contamination. With the use of a high-speed, large-area sCMOS camera, we routinely imaged tens of spiking neurons simultaneously over minutes in behaving mice. Thus, the targeted illumination strategy described here offers a simple solution for widefield voltage imaging of many neurons over a large field of view in behaving animals.

High-resolution structural and functional deep brain imaging using adaptive optics three-photon microscopy

Multiphoton microscopy has become a powerful tool with which to visualize the morphology and function of neural cells and circuits in the intact mammalian brain. However, tissue scattering, optical aberrations and motion artifacts degrade the imaging performance at depth. Here we describe a minimally invasive intravital imaging methodology based on three-photon excitation, indirect adaptive optics (AO) and active electrocardiogram gating to advance deep-tissue imaging. Our modal-based, sensorless AO approach is robust to low signal-to-noise ratios as commonly encountered in deep scattering tissues such as the mouse brain, and permits AO correction over large axial fields of view. We demonstrate near-diffraction-limited imaging of deep cortical spines and (sub)cortical dendrites up to a depth of 1.4 mm (the edge of the mouse CA1 hippocampus). In addition, we show applications to deep-layer calcium imaging of astrocytes, including fibrous astrocytes that reside in the highly scattering corpus callosum.

A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging

Inference of action potentials ('spikes') from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals ('ground truth'). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation.

Cerebellar granule cell axons support high-dimensional representations

In classical theories of cerebellar cortex, high-dimensional sensorimotor representations are used to separate neuronal activity patterns, improving associative learning and motor performance. Recent experimental studies suggest that cerebellar granule cell (GrC) population activity is low-dimensional. To examine sensorimotor representations from the point of view of downstream Purkinje cell 'decoders', we used three-dimensional acousto-optic lens two-photon microscopy to record from hundreds of GrC axons. Here we show that GrC axon population activity is high dimensional and distributed with little fine-scale spatial structure during spontaneous behaviors. Moreover, distinct behavioral states are represented along orthogonal dimensions in neuronal activity space. These results suggest that the cerebellar cortex supports high-dimensional representations and segregates behavioral state-dependent computations into orthogonal subspaces, as reported in the neocortex. Our findings match the predictions of cerebellar pattern separation theories and suggest that the cerebellum and neocortex use population codes with common features, despite their vastly different circuit structures.

Eavesdropping wires: Recording activity in axons using genetically encoded calcium indicators

Neurons broadcast electrical signals to distal brain regions through extensive axonal arbors. Genetically encoded calcium sensors permit the direct observation of action potential activity at axonal terminals, providing unique insights on the organization and function of neural projections. Here, we consider what information can be gleaned from axonal recordings made at scales ranging from the summed activity extracted from multi-cell axon projections to single boutons. In particular, we discuss the application of different recently developed multi photon and fiber photometry methods for recording neural activity in axons of rodents. We define experimental difficulties associated with imaging approaches in the axonal compartment and highlight the latest methodological advances for addressing these issues. Finally, we reflect on ways in which new technologies can be used in conjunction with axon calcium imaging to address current questions in neurobiology.

Active dendrites enable strong but sparse inputs to determine orientation selectivity

The dendrites of neocortical pyramidal neurons are excitable. However, it is unknown how synaptic inputs engage nonlinear dendritic mechanisms during sensory processing in vivo, and how they in turn influence action potential output. Here, we provide a quantitative account of the relationship between synaptic inputs, nonlinear dendritic events, and action potential output. We developed a detailed pyramidal neuron model constrained by in vivo dendritic recordings. We drive this model with realistic input patterns constrained by sensory responses measured in vivo and connectivity measured in vitro. We show mechanistically that under realistic conditions, dendritic Na+ and NMDA spikes are the major determinants of neuronal output in vivo. We demonstrate that these dendritic spikes can be triggered by a surprisingly small number of strong synaptic inputs, in some cases even by single synapses. We predict that dendritic excitability allows the 1% strongest synaptic inputs of a neuron to control the tuning of its output. Active dendrites therefore allow smaller subcircuits consisting of only a few strongly connected neurons to achieve selectivity for specific sensory features.

Protocol for constructing an extensive cranial window utilizing a PEO-CYTOP nanosheet for in vivo wide-field imaging of the mouse brain

Large-scale optical measurements have revealed the anatomical and functional connectivity among brain regions underlying brain functions. Here, we describe how to construct a cranial window utilizing a polyethylene-oxide-coated CYTOP (PEO-CYTOP) nanosheet that suppresses bleeding on the brain surface of mice. We demonstrate in vivo two-photon imaging through the PEO-CYTOP nanosheet at the subcellular resolution in the parietal region of the mouse brain. This protocol improves the surgical procedure and expands the optically observable regions, thereby promoting understanding of brain function.

For complete details on the use and execution of this protocol, please refer to Takahashi et al. (2020).

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Detailed protocol for constructing a vast cranial window for in vivo mouse brain imaging

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Preparation and brain-sealing method of PEO-CYTOP nanosheet

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Instruction to make a large cranial hole with a depressant for intracranial pressure

Precompensation of 3D field distortions in remote focus two-photon microscopy

Remote focusing is widely used in 3D two-photon microscopy and 3D photostimulation because it enables fast axial scanning without moving the objective lens or specimen. However, due to the design constraints of microscope optics, remote focus units are often located in non-telecentric positions in the optical path, leading to significant depth-dependent 3D field distortions in the imaging volume. To address this limitation, we characterized 3D field distortions arising from non-telecentric remote focusing and present a method for distortion precompensation. We demonstrate its applicability for a 3D two-photon microscope that uses an acousto-optic lens (AOL) for remote focusing and scanning. We show that the distortion precompensation method improves the pointing precision of the AOL microscope to < 0.5 µm throughout the 400 × 400 × 400 µm imaging volume.

Multidimensional population activity in an electrically coupled inhibitory circuit in the cerebellar cortex

Inhibitory neurons orchestrate the activity of excitatory neurons and play key roles in circuit function. Although individual interneurons have been studied extensively, little is known about their properties at the population level. Using random-access 3D two-photon microscopy, we imaged local populations of cerebellar Golgi cells (GoCs), which deliver inhibition to granule cells. We show that population activity is organized into multiple modes during spontaneous behaviors. A slow, network-wide common modulation of GoC activity correlates with the level of whisking and locomotion, while faster (<1 s) differential population activity, arising from spatially mixed heterogeneous GoC responses, encodes more precise information. A biologically detailed GoC circuit model reproduced the common population mode and the dimensionality observed experimentally, but these properties disappeared when electrical coupling was removed. Our results establish that local GoC circuits exhibit multidimensional activity patterns that could be used for inhibition-mediated adaptive gain control and spatiotemporal patterning of downstream granule cells.

Photoactivated voltage imaging in tissue with an archaerhodopsin-derived reporter

Photoactivated genetically encoded voltage indicators (GEVIs) have the potential to enable optically sectioned voltage imaging at the intersection of a photoactivation beam and an imaging beam. We developed a pooled high-throughput screen to identify archaerhodopsin mutants with enhanced photoactivation. After screening ~10⁵ cells, we identified a novel GEVI, NovArch, whose one-photon near-infrared fluorescence is reversibly enhanced by weak one-photon blue or two-photon near-infrared excitation. Because the photoactivation leads to fluorescent signals catalytically rather than stoichiometrically, high fluorescence signals, optical sectioning, and high time resolution are achieved simultaneously at modest blue or two-photon laser power. We demonstrate applications of the combined molecular and optical tools to optical mapping of membrane voltage in distal dendrites in acute mouse brain slices and in spontaneously active neurons in vivo.

Compact and adjustable compensator for AOD spatial and temporal dispersion using off-the-shelf components

Random access multiphoton microscopy using two orthogonal acousto-optic deflectors (AODs) allows sampling only particular regions of interest within a plane, greatly speeding up the sampling rate. AODs introduce spatial and temporal dispersions, which distort the point spread function and decrease the peak intensity of the pulse. Both of these effects can be compensated for with a single dispersive element placed a distance before the AODs. An additional acousto-optic modulator, a custom cut prism, and a standard prism used with additional cylindrical optics have been demonstrated. All of these introduce additional cost or complexity and require an extended path length to achieve the needed negative group delay dispersion (GDD). By introducing a telescope between a transmission grating and the AODs, we correct for spatial and temporal dispersions in a compact design using only off-the-shelf components, and we show that the GDD can be tuned by translation of the telescope without adjustment of any other elements.

Accounting for uncertainty: inhibition for neural inference in the cerebellum

Sensorimotor coordination is thought to rely on cerebellar-based internal models for state estimation, but the underlying neural mechanisms and specific contribution of the cerebellar components is unknown. A central aspect of any inferential process is the representation of uncertainty or conversely precision characterizing the ensuing estimates. Here, we discuss the possible contribution of inhibition to the encoding of precision of neural representations in the granular layer of the cerebellar cortex. Within this layer, Golgi cells influence excitatory granule cells, and their action is critical in shaping information transmission downstream to Purkinje cells. In this review, we equate the ensuing excitation-inhibition balance in the granular layer with the outcome of a precision-weighted inferential process, and highlight the physiological characteristics of Golgi cell inhibition that are consistent with such computations.

Subcellular Dissection of a Simple Neural Circuit: Functional Domains of the Mauthner-Cell During Habituation

Sensorimotor integration is a pivotal feature of the nervous system for ensuring a coordinated motor response to external stimuli. In essence, such neural circuits can optimize behavioral performance based on the saliency of environmental cues. In zebrafish, habituation of the acoustic startle response (ASR) is a simple behavior integrated into the startle command neurons, called the Mauthner cells. Whereas the essential neuronal components that regulate the startle response have been identified, the principles of how this regulation is integrated at the subcellular regions of the Mauthner cell, which in turn modulate the performance of the behavior, is still not well understood. Here, we reveal mechanistically distinct dynamics of excitatory inputs converging onto the lateral dendrite (LD) and axon initial segment (AIS) of the Mauthner cell by in vivo imaging glutamate release using iGluSnFR, an ultrafast glutamate sensing fluorescent reporter. We find that modulation of glutamate release is dependent on NMDA receptor activity exclusively at the AIS, which is responsible for setting the sensitivity of the startle reflex and inducing a depression of synaptic activity during habituation. In contrast, glutamate-release at the LD is not regulated by NMDA receptors and serves as a baseline component of Mauthner cell activation. Finally, using in vivo calcium imaging at the feed-forward interneuron population component of the startle circuit, we reveal that these cells indeed play pivotal roles in both setting the startle threshold and habituation by modulating the AIS of the Mauthner cell. These results indicate that a command neuron may have several functionally distinct regions to regulate complex aspects of behavior.

Imaging of spine synapses using super-resolution microscopy

Neuronal circuits in the neocortex and hippocampus are essential for higher brain functions such as motor learning and spatial memory. In the mammalian forebrain, most excitatory synapses of pyramidal neurons are formed on spines, which are tiny protrusions extending from the dendritic shaft. The spine contains specialized molecular machinery that regulates synaptic transmission and plasticity. Spine size correlates with the efficacy of synaptic transmission, and spine morphology affects signal transduction at the post-synaptic compartment. Plasticity-related changes in the structural and molecular organization of spine synapses are thought to underlie the cellular basis of learning and memory. Recent advances in super-resolution microscopy have revealed the molecular mechanisms of the nanoscale synaptic structures regulating synaptic transmission and plasticity in living neurons, which are difficult to investigate using electron microscopy alone. In this review, we summarize recent advances in super-resolution imaging of spine synapses and discuss the implications of nanoscale structures in the regulation of synaptic function, learning, and memory.

PEO-CYTOP Fluoropolymer Nanosheets as a Novel Open-Skull Window for Imaging of the Living Mouse Brain

In vivo two-photon deep imaging with a broad field of view has revealed functional connectivity among brain regions. Here, we developed a novel observation method that utilizes a polyethylene-oxide-coated CYTOP (PEO-CYTOP) nanosheet with a thickness of ∼130 nm that exhibited a water retention effect and a hydrophilized adhesive surface. PEO-CYTOP nanosheets firmly adhered to brain surfaces, which suppressed bleeding from superficial veins. By taking advantage of the excellent optical properties of PEO-CYTOP nanosheets, we performed in vivo deep imaging in mouse brains at high resolution. Moreover, PEO-CYTOP nanosheets enabled to prepare large cranial windows, achieving in vivo imaging of neural structure and Ca²⁺ elevation in a large field of view. Furthermore, the PEO-CYTOP nanosheets functioned as a sealing material, even after the removal of the dura. These results indicate that this method would be suitable for the investigation of neural functions that are composed of interactions among multiple regions.

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PEO-CYTOP nanosheet enables in vivo deep brain imaging in a vast field of view

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The 130 nm thickness and the hydrophilized surface realize the strong adhesiveness

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Suppressions of bleeding from the surface and inflammation in long-term are achieved

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The vast and transparent cranial window with natural curvature of the surface

Milestones in the development and implementation of FRET-based sensors of intracellular signals: A biological perspective of the history of FRET

Fӧrster resonance energy transfer (FRET) has been described for more than a century. FRET has become a mainstay for the study of protein localization in living cells and tissues. It has also become widely used in the fields that comprise cellular signaling. FRET-based probes have been developed to monitor second messenger signals, the phosphorylation state of peptides and proteins, and subsequent cellular responses. Here, we discuss the milestones that led to FRET becoming a widely used tool for the study of biological systems: the theoretical description of FRET, the insight to use FRET as a molecular ruler, and the isolation and genetic modification of green fluorescent protein (GFP). Each of these milestones were critical to the development of a myriad of FRET-based probes and reporters in common use today. FRET-probes offer a unique opportunity to interrogate second messenger signals and subsequent protein phosphorylation - and perhaps the most effective approach for study of cAMP/PKA pathways. As such, FRET probes are widely used in the study of intracellular signaling pathways. Yet, somehow, the potential of FRET-based probes to provide windows through which we can visualize complex cellular signaling systems has not been fully reached. Hence we conclude by discussing the technical challenges to be overcome if FRET-based probes are to live up to their potential for the study of complex signaling networks.