Limitations in existing tools have hindered neuroscientists from achieving a deeper understanding of complex behaviors and diseases. The recent development and optimization of genetically encoded sensors offer a powerful solution for investigating intricate dynamics such as calcium influx, membrane potential, and the release of neurotransmitters and neuromodulators. In contrast, traditional methods are constrained by insufficient spatial and/or temporal resolution, low sensitivity, and stringent application conditions. Genetically encoded sensors have gained widespread popularity due to their advantageous features, which stem from their genetic encoding and optical imaging capabilities. These include broad applicability, tissue specificity, and non-invasive operation. When combined with advanced microscopic techniques, optogenetics, and machine learning approaches, these sensors have become versatile tools for studying neuronal circuits in intact living systems, providing millisecond-scale temporal resolution and spatial resolution ranging from nanometers to micrometers. In this review, we highlight the advantages of genetically encoded sensors over traditional methods in the study of neurotransmission. We also discuss their recent advancements, diverse applications, and optimization strategies.

Monitoring neural activity in individual neurons is crucial for understanding neural circuits and brain functions. The emergence of optical imaging technologies has dramatically transformed the field of neuroscience, enabling detailed observation of large-scale neuronal populations with both cellular and subcellular resolution. This transformation will be further accelerated by the integration of these imaging technologies and advanced big data analysis. Genetically encoded fluorescent indicators to detect neural activity with high signal-to-noise ratios are pivotal in this advancement. In recent years, these indicators have undergone significant developments, greatly enhancing the understanding of neural dynamics and networks. This review highlights the recent progress in genetically encoded calcium and voltage indicators and discusses the future direction of imaging techniques with big data analysis that deepens our understanding of the complexities of the brain.

Fluorescent protein-based biosensors are indispensable molecular tools in cell biology and biomedical research, providing non-invasive dynamic measurements of metabolite concentrations and other cellular signals. Traditional methods for developing these biosensors rely on rational design, but directed evolution methods offer a more efficient alternative. This review discusses recent advancements in the development of biosensors using directed evolution, including methods for optimizing domain fusions, sequence optimization, and new screening and selection systems. Additionally, the incorporation of machine learning into the directed evolution process is explored, highlighting its potential to enhance the efficiency and cost reduction of biosensor development. Finally, emerging trends in the development of near-infrared biosensors and photochromic sensors are discussed, along with the opportunities presented by de novo design of sensing domains and biosensors.

Voltage imaging is a promising technique for high-speed recording of neuronal population activity. However, tissue scattering severely limits its application in dense neuronal populations. Here we adopt the principle of localization microscopy, a technique that enables super-resolution imaging of single molecules, to resolve dense neuronal activities in vivo. Leveraging the sparse activation of neurons during action potentials (APs), we precisely localize the fluorescence changes associated with each AP, creating a super-resolution image of neuronal activity. This approach, termed activity localization imaging (ALI), identifies overlapping neurons and separates their activities with over tenfold greater precision than what tissue scattering permits. We applied ALI to widefield, targeted illumination and light sheet microscopy data, resolving neurons that cannot be distinguished by existing signal extraction pipelines. In the mouse hippocampus, ALI generates a cellular resolution map of theta oscillations, revealing the diversity of neuronal phase locking within a dense local network.

A tool to map changes in synaptic strength during a defined time window could provide powerful insights into the mechanisms of learning and memory. Here we developed a technique, Extracellular Protein Surface Labeling in Neurons (EPSILON), to map α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) exocytosis in vivo by sequential pulse-chase labeling of surface AMPARs with membrane-impermeable dyes. This approach yields synaptic-resolution maps of AMPAR exocytosis, a proxy for synaptic potentiation, in genetically targeted neurons during memory formation. In mice undergoing contextual fear conditioning, we investigated the relationship between synapse-level AMPAR exocytosis in CA1 pyramidal neurons and cell-level expression of the immediate early gene product cFos, a frequently used marker of engram neurons. We observed a strong correlation between AMPAR exocytosis and cFos expression, suggesting a synaptic mechanism for the association of cFos expression with memory engrams. The EPSILON technique is a useful tool for mapping synaptic plasticity and may be extended to investigate trafficking of other transmembrane proteins.

Bidirectional microscopy (BDM) combines simultaneous targeted optical perturbation and imaging of biophysical or biochemical signals (e.g. membrane voltage, Ca2+, or signaling molecules). A core challenge in BDM is precise spatial and temporal alignment of stimulation, imaging, and other experimental parameters. Here we present Luminos, an open-source MATLAB library for modular and precisely synchronized control of BDM experiments. The system supports hardware-triggered synchronization across stimulation, recording, and imaging channels with microsecond accuracy. Source code and documentation for Luminos are available online at https://www.luminosmicroscopy.com and https://github.com/adamcohenlab/luminos-microscopy. This library will facilitate development of bidirectional microscopy methods across the biological sciences.

We present versatile tools for intersectional optical and chemical tagging of live cells. Photocaged tetrazines serve as "photo-click" adapters between recognition groups on the cell surface and diverse chemical payloads. We describe two new functionalized photocaged tetrazine structures which add a light-gating step to three common cell-targeting chemical methods: HaloTag/chloroalkane labeling, nonspecific primary amine labeling, and antibody labeling. We demonstrate light-gated versions of these three techniques in live cultured cells. We then explore two applications: monitoring tissue flows on the surface of developing zebrafish embryos, and combinatorial multicolor labeling and sorting of optically defined groups of cells. Photoclick adapters add optical control to cell tagging schemes, with modularity in both tag and cell attachment chemistry.

Genetically encoded voltage indicators (GEVIs) allow for the cell-type-specific real-time imaging of neuronal membrane potential dynamics, which is essential to understanding neuronal information processing at both cellular and circuit levels. Among GEVIs, near-infrared-shifted GEVIs offer faster kinetics, better tissue penetration, and compatibility with optogenetic tools, enabling all-optical electrophysiology in complex biological contexts. In our previous work, we employed the directed molecular evolution of microbial rhodopsin Archaerhodopsin-3 (Arch-3) in mammalian cells to develop a voltage sensor called Archon1. Archon1 demonstrated excellent membrane localization, signal-to-noise ratio (SNR), sensitivity, kinetics, and photostability, and full compatibility with optogenetic tools. However, Archon1 suffers from low brightness and requires high illumination intensities, which leads to tissue heating and phototoxicity during prolonged imaging. In this study, we aim to improve the brightness of this voltage sensor. We performed random mutation on a bright Archon derivative and identified a novel variant, monArch, which exhibits satisfactory voltage sensitivity (4~5% ΔF/FAP) and a 9-fold increase in basal brightness compared with Archon1. However, it is hindered by suboptimal membrane localization and compromised voltage sensitivity. These challenges underscore the need for continued optimization to achieve an optimal balance of brightness, stability, and functionality in rhodopsin-based voltage sensors.

Calcium signaling in blood vessels regulates their growth1,2, immune response3, and vascular tone4. Vascular endothelial cells are known to be mechanosensitive5-7, and it has been assumed that this mechanosensation mediates calcium responses to pulsatile blood flow8-10. Here we show that in larval zebrafish, the dominant trigger for vascular endothelial Ca2+ events comes from body motion, not heartbeat-driven blood flow. Through a series of pharmacological and mechanical perturbations, we showed that body motion is necessary and sufficient to induce endothelial Ca2+ events, while neither neural activity nor blood circulation is either necessary or sufficient. Knockout and temporally restricted knockdown of piezo1 eliminated the motion-induced Ca2+ events. Our results demonstrate that swimming-induced tissue motion is an important driver of endothelial Ca2+ dynamics in larval zebrafish.

Microbial rhodopsin-derived genetically encoded voltage indicators (GEVIs) are powerful tools for mapping bioelectrical dynamics in cell culture and in live animals. Förster resonance energy transfer (FRET)-opsin GEVIs use voltage-dependent quenching of an attached fluorophore, achieving high brightness, speed, and voltage sensitivity. However, the voltage sensitivity of most FRET-opsin GEVIs has been reported to decrease or vanish under two-photon (2P) excitation. Here, we investigated the photophysics of the FRET-opsin GEVIs Voltron1 and Voltron2. We found that the previously reported negative-going voltage sensitivities of both GEVIs came from photocycle intermediates, not from the opsin ground states. The voltage sensitivities of both GEVIs were nonlinear functions of illumination intensity; for Voltron1, the sensitivity reversed the sign under low-intensity illumination. Using photocycle-optimized 2P illumination protocols, we demonstrate 2P voltage imaging with Voltron2 in the barrel cortex of a live mouse. These results open the door to high-speed 2P voltage imaging of FRET-opsin GEVIs in vivo.

Cellular function is controlled through intricate networks of signals, which lead to the myriad pathways governing cell fate. Fluorescent biosensors have enabled the study of these signaling pathways in living systems across temporal and spatial scales. Over the years there has been an explosion in the number of fluorescent biosensors, as they have become available for numerous targets, utilized across spectral space, and suited for various imaging techniques. To guide users through this extensive biosensor landscape, we discuss critical aspects of fluorescent proteins for consideration in biosensor development, smart tagging strategies, and the historical and recent biosensors of various types, grouped by target, and with a focus on the design and recent applications of these sensors in living systems.

Genetically encoded voltage indicators (GEVIs) allow optical recording of membrane potential from targeted cells in vivo. However, red GEVIs that are compatible with two-photon microscopy and that can be multiplexed in vivo with green reporters like GCaMP, are currently lacking. To address this gap, we explored diverse rhodopsin proteins as GEVIs and engineered a novel GEVI, 2Photron, based on a rhodopsin from the green algae Klebsormidium nitens. 2Photron, combined with two photon ultrafast local volume excitation (ULoVE), enabled multiplexed readout of spiking and subthreshold voltage simultaneously with GCaMP calcium signals in visual cortical neurons of awake, behaving mice. These recordings revealed the cell-specific relationship of spiking and subthreshold voltage dynamics with GCaMP responses, highlighting the challenges of extracting underlying spike trains from calcium imaging.

Voltage imaging measures neuronal activity directly and holds promise for understanding information processing within individual neurons and across populations. However, imaging voltage over large neuronal populations has been challenging owing to the simultaneous requirements of high imaging speed and signal-to-noise ratio, large volume coverage and low photobleaching rate. Here, to overcome this challenge, we developed a confocal light-field microscope that surpassed the traditional limits in speed and noise performance by incorporating a speed-enhanced camera, a fast and robust scanning mechanism, laser-speckle-noise elimination and optimized light efficiency. With this method, we achieved simultaneous recording from more than 300 spiking neurons within an 800-µm-diameter and 180-µm-thick volume in the mouse cortex, for more than 20 min. By integrating the spatial and voltage activity profiles, we have mapped three-dimensional neural coordination patterns in awake mouse brains. Our method is robust for routine application in volumetric voltage imaging.

Voltage imaging is an important complement to traditional methods for probing cellular physiology, such as electrode-based patch clamp techniques. Unlike the related Ca2+ imaging, voltage imaging provides a direct visualization of bioelectricity changes. We have been exploring the use of sulfonated silicon rhodamine dyes (Berkeley Red Sensor of Transmembrane potential, BeRST) for voltage imaging. In this study, we explore the effect of converting BeRST to diEt BeRST, by replacing the dimethyl aniline of BeRST with a diethyl aniline group. The new dye, diEt BeRST, has a voltage sensitivity of 40% ΔF/F per 100 mV, a 33% increase compared to the original BeRST dye, which has a sensitivity of 30% ΔF/F per 100 mV. In neurons, the cellular brightness of diEt BeRST is about 20% as bright as that of BeRST, which may be due to the lower solubility of diEt BeRST (300 μM) compared to that of BeRST (800 μM). Despite this lower cellular brightness, diEt BeRST is able to record spontaneous and evoked action potentials from multiple neurons simultaneously and in single trials. Far-red excitation and emission profiles enable diEt BeRST to be used alongside existing fluorescent indicators of cellular physiology, like Ca2+-sensitive Oregon Green BAPTA. In hippocampal neurons, simultaneous voltage and Ca2+ imaging reveals neuronal spiking patterns and frequencies that cannot be resolved with traditional Ca2+ imaging methods. This study represents a first step toward describing the structural features that define voltage sensitivity and brightness in silicon rhodamine-based BeRST indicators.

Measuring neuronal activity is important for understanding neuronal function. Ca2+ imaging by genetically encoded calcium indicators (GECIs) is a powerful way to measure neuronal activity. Although it revealed important aspects of neuronal function, measuring the neuronal membrane voltage is important to understand neuronal function as it triggers neuronal activation. Recent progress of genetically encoded voltage indicators (GEVIs) enabled us fast and precise measurements of neuronal membrane voltage. To clarify the relation of the membrane voltage and intracellular Ca2+, we analyzed neuronal activities of olfactory neuron AWA in Caenorhabditis elegans by GCaMP6f (GECI) and paQuasAr3 (GEVI) responding to odorants. We found that the membrane voltage encodes the stimuli change by the timing and the duration by the weak semi-stable depolarization. However, the change of the intracellular Ca2+ encodes the strength of the stimuli. Furthermore, ODR-3, a G-protein alpha subunit, was shown to be important for stabilizing the membrane voltage. These results suggest that the combination of calcium and voltage imaging provides a deeper understanding of the information in neural circuits.

Fiber photometry is an optical method to monitor fluorescent signals using a fiber optic cannula. Over the past two decades, together with the development of various genetically encoded biosensors, it has been applied to investigate various types of activity in the central nervous system. This includes not only type-specific neuronal population activity, but also non-neuronal activity and neurotransmitter/neuropeptide signals in awake, freely behaving animals. In this perspective, we summarize the recent development of this technique. After describing common technical pitfalls, we discuss future directions of this powerful approach for investigating brain function and dysfunction.

Fluorescent genetically encoded voltage indicators report transmembrane potentials of targeted cell-types. However, voltage-imaging instrumentation has lacked the sensitivity to track spontaneous or evoked high-frequency voltage oscillations in neural populations. Here we describe two complementary TEMPO voltage-sensing technologies that capture neural oscillations up to ~100 Hz. Fiber-optic TEMPO achieves ~10-fold greater sensitivity than prior photometry systems, allows hour-long recordings, and monitors two neuron-classes per fiber-optic probe in freely moving mice. With it, we uncovered cross-frequency-coupled theta- and gamma-range oscillations and characterized excitatory-inhibitory neural dynamics during hippocampal ripples and visual cortical processing. The TEMPO mesoscope images voltage activity in two cell-classes across a ~8-mm-wide field-of-view in head-fixed animals. In awake mice, it revealed sensory-evoked excitatory-inhibitory neural interactions and traveling gamma and 3-7 Hz waves in the visual cortex, and previously unreported propagation directions for hippocampal theta and beta waves. These technologies have widespread applications probing diverse oscillations and neuron-type interactions in healthy and diseased brains.

Brain oscillations are crucial for perception, memory, and behavior. Parvalbumin-expressing (PV) interneurons are critical for these oscillations, but their population dynamics remain unclear. Using voltage imaging, we simultaneously recorded membrane potentials in up to 26 PV interneurons in vivo during hippocampal ripple oscillations in mice. We found that PV cells generate ripple-frequency rhythms by forming highly dynamic cell assemblies. These assemblies exhibit rapid and significant changes from cycle to cycle, varying greatly in both size and membership. Importantly, this variability is not just random spiking failures of individual neurons. Rather, the activities of other PV cells contain significant information about whether a PV cell spikes or not in a given cycle. This coordination persists without network oscillations, and it exists in subthreshold potentials even when the cells are not spiking. Dynamic assemblies of interneurons may provide a new mechanism to modulate postsynaptic dynamics and impact cognitive functions flexibly and rapidly.

Genetically encoded voltage indicators (GEVIs) are a valuable tool for studying neural circuits in vivo, but the relative merits and limitations of one-photon (1P) versus two-photon (2P) voltage imaging are not well characterized.

We consider the optical and biophysical constraints particular to 1P and 2P voltage imaging and compare the imaging properties of commonly used GEVIs under 1P and 2P excitation.

We measure the brightness and voltage sensitivity of voltage indicators from commonly used classes under 1P and 2P illumination. We also measure the decrease in fluorescence as a function of depth in the mouse brain. We develop a simple model of the number of measurable cells as a function of reporter properties, imaging parameters, and desired signal-to-noise ratio (SNR). We then discuss how the performance of voltage imaging would be affected by sensor improvements and by recently introduced advanced imaging modalities.

Compared with 1P excitation, 2P excitation requires ∼ 10 4 -fold more illumination power per cell to produce similar photon count rates. For voltage imaging with JEDI-2P in the mouse cortex with a target SNR of 10 (spike height to baseline shot noise), a measurement bandwidth of 1 kHz, a thermally limited laser power of 200 mW, and an imaging depth of > 300    μ m , 2P voltage imaging using an 80-MHz source can record from no more than ∼ 12 neurons simultaneously.

Due to the stringent photon-count requirements of voltage imaging and the modest voltage sensitivity of existing reporters, 2P voltage imaging in vivo faces a stringent tradeoff between shot noise and tissue photodamage. 2P imaging of hundreds of neurons with high SNR at a depth of > 300    μ m will require either major improvements in 2P GEVIs or qualitatively new approaches to imaging.

Voltage imaging with cellular specificity has been made possible by advances in genetically encoded voltage indicators. However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines the signal-to-noise ratio and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating while also maximizing signal detection efficiency. The resulting benefits in signal-to-noise ratio and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different genetically encoded voltage indicator classes.

In vivo transmembrane-voltage detection reflected the electrophysiological activities of the biological system, which is crucial for the diagnosis of neuronal disease. Traditional implanted electrodes can only monitor limited regions and induce relatively large tissue damage. Despite emerging monitoring methods based on optical imaging have access to signal recording in a larger area, the recording wavelength of less than 1000 nm seriously weakens the detection depth and resolution in vivo. Herein, a Förster resonance energy transfer (FRET)-based nano-indicator, NaYbF4:Er@NaYF4@Cy7.5@DPPC (Cy7.5-ErNP) with emission in the near-infrared IIb biological window (NIR-IIb, 1500-1700 nm) is developed for transmembrane-voltage detection. Cy7.5 dye is found to be voltage-sensitive and is employed as the energy donor for the energy transfer to the lanthanide nanoparticle, NaYbF4:Er@NaYF4 (ErNP), which works as the acceptor to achieve electrophysiological signal responsive NIR-IIb luminescence. Benefiting from the high penetration and low scattering of NIR-IIb luminescence, the Cy7.5-ErNP enables both the visualization of action potential in vitro and monitoring of Mesial Temporal lobe epilepsy (mTLE) disease in vivo. This work presents a concept for leveraging the lanthanide luminescent nanoprobes to visualize electrophysiological activity in vivo, which facilitates the development of an optical nano-indicator for the diagnosis of neurological disorders.

Genetically encoded voltage indicators (GEVIs) are a valuable tool for studying neural circuits in vivo, but the relative merits and limitations of one-photon (1P) vs. two-photon (2P) voltage imaging are not well characterized.

We consider the optical and biophysical constraints particular to 1P and 2P voltage imaging and compare the imaging properties of commonly used GEVIs under 1P and 2P excitation.

We measure brightness and voltage sensitivity of voltage indicators from commonly used classes under 1P and 2P illumination. We also measure the decrease in fluorescence as a function of depth in mouse brain. We develop a simple model of the number of measurable cells as a function of reporter properties, imaging parameters, and desired signal-to-noise ratio (SNR). We then discuss how the performance of voltage imaging would be affected by sensor improvements and by recently introduced advanced imaging modalities.

Compared to 1P excitation, 2P excitation requires ~104-fold more illumination power per cell to produce similar photon count rates. For voltage imaging with JEDI-2P in mouse cortex with a target SNR of 10 (spike height:baseline shot noise), a measurement bandwidth of 1 kHz, a thermally limited laser power of 200 mW, and an imaging depth of > 300 μm, 2P voltage imaging using an 80 MHz source can record from no more 12 cells simultaneously.

Due to the stringent photon-count requirements of voltage imaging and the modest voltage sensitivity of existing reporters, 2P voltage imaging in vivo faces a stringent tradeoff between shot noise and tissue photodamage. 2P imaging of hundreds of neurons with high SNR at depth > 300 μm will require either major improvements in 2P GEVIs or qualitatively new approaches to imaging.

Efforts starting more than 20 years ago led to increasingly well performing genetically encoded voltage indicators (GEVIs) for optical imaging at wavelengths < 600    nm . Although optical imaging in the > 600    nm wavelength range has many advantages over shorter wavelength approaches for mesoscopic in vivo monitoring of neuronal activity in the mammalian brain, the availability and evaluation of well performing near-infrared GEVIs are still limited.

Here, we characterized two recent near-infrared GEVIs, Archon1 and nirButterfly, to support interested tool users in selecting a suitable near-infrared GEVI for their specific research question requirements.

We characterized side-by-side the brightness, sensitivity, and kinetics of both near-infrared GEVIs in a setting focused on population imaging.

We found that nirButterfly shows seven-fold higher brightness than Archon1 under the same conditions and faster kinetics than Archon1 for population imaging without cellular resolution. But Archon1 showed larger signals than nirButterfly.

Neither GEVI characterized here surpasses in all three key parameters (brightness, kinetics, and sensitivity), so there is no unequivocal preference for one of the two. Our side-by-side characterization presented here provides new information for future in vitro and ex vivo experimental designs.

Endocannabinoid (eCB)-mediated suppression of inhibitory synapses has been hypothesized, but this has not yet been demonstrated to occur in vivo because of the difficulty in tracking eCB dynamics and synaptic plasticity during behavior. In mice navigating a linear track, we observed location-specific eCB signaling in hippocampal CA1 place cells, and this was detected both in the postsynaptic membrane and the presynaptic inhibitory axons. All-optical in vivo investigation of synaptic responses revealed that postsynaptic depolarization was followed by a suppression of inhibitory synaptic potentials. Furthermore, interneuron-specific cannabinoid receptor deletion altered place cell tuning. Therefore, rapid, postsynaptic, activity-dependent eCB signaling modulates inhibitory synapses on a timescale of seconds during behavior.

Electric pulses used in electroporation-based treatments have been shown to affect the excitability of muscle and neuronal cells. However, understanding the interplay between electroporation and electrophysiological response of excitable cells is complex, since both ion channel gating and electroporation depend on dynamic changes in the transmembrane voltage (TMV). In this study, a genetically engineered human embryonic kidney cells expressing NaV1.5 and Kir2.1, a minimal complementary channels required for excitability (named S-HEK), was characterized as a simple cell model used for studying the effects of electroporation in excitable cells. S-HEK cells and their non-excitable counterparts (NS-HEK) were exposed to 100 µs pulses of increasing electric field strength. Changes in TMV, plasma membrane permeability, and intracellular Ca2+ were monitored with fluorescence microscopy. We found that a very mild electroporation, undetectable with the classical propidium assay but associated with a transient increase in intracellular Ca2+, can already have a profound effect on excitability close to the electrostimulation threshold, as corroborated by multiscale computational modelling. These results are of great relevance for understanding the effects of pulse delivery on cell excitability observed in context of the rapidly developing cardiac pulsed field ablation as well as other electroporation-based treatments in excitable tissues.

Bioelectricity is the electrical activity that occurs within living cells and tissues. This activity is critical for regulating homeostatic cellular function and communication, and disruptions of the same can lead to a variety of conditions, including cancer. Cancer cells are known to exhibit abnormal electrical properties compared to their healthy counterparts, and this has driven researchers to investigate the potential of harnessing bioelectricity as a tool in cancer diagnosis, prognosis, and treatment. In parallel, bioelectricity represents one of the means to gain fundamental insights on how electrical signals and charges play a role in cancer insurgence, growth, and progression. This review provides a comprehensive analysis of the literature in this field, addressing the fundamentals of bioelectricity in single cancer cells, cancer cell cohorts, and cancerous tissues. The emerging role of bioelectricity in cancer proliferation and metastasis is introduced. Based on the acknowledgement that this biological information is still hard to access due to the existing gap between biological findings and translational medicine, the latest advancements in the field of nanotechnologies for cellular electrophysiology are examined, as well as the most recent developments in micro- and nano-devices for cancer diagnostics and therapy targeting bioelectricity.

A tool to map changes in synaptic strength during a defined time window could provide powerful insights into the mechanisms governing learning and memory. We developed a technique, Extracellular Protein Surface Labeling in Neurons (EPSILON), to map α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) insertion in vivo by pulse-chase labeling of surface AMPARs with membrane-impermeable dyes. This approach allows for single-synapse resolution maps of plasticity in genetically targeted neurons during memory formation. We investigated the relationship between synapse-level and cell-level memory encodings by mapping synaptic plasticity and cFos expression in hippocampal CA1 pyramidal cells upon contextual fear conditioning (CFC). We observed a strong correlation between synaptic plasticity and cFos expression, suggesting a synaptic mechanism for the association of cFos expression with memory engrams. The EPSILON technique is a useful tool for mapping synaptic plasticity and may be extended to investigate trafficking of other transmembrane proteins.

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.

Genetically encoded voltage indicators (GEVIs) allow the direct visualization of cellular membrane potential at the millisecond time scale. Among these, red-emitting GEVIs have been reported to support multichannel recordings and manipulation of cellular activities with reduced autofluorescence background. However, the limited sensitivity and dimness of existing red GEVIs have restricted their applications in neuroscience. Here, we report a pair of red-shifted opsin-based GEVIs, Cepheid1b and Cepheid1s, with improved dynamic range, brightness, and photostability. The improved dynamic range is achieved by a rational design to raise the electrochromic Förster resonance energy transfer efficiency, and the higher brightness and photostability are approached with separately engineered red fluorescent proteins. With Cepheid1 indicators, we recorded complex firings and subthreshold activities of neurons on acute brain slices and observed heterogeneity in the voltage‑calcium coupling on pancreatic islets. Overall, Cepheid1 indicators provide a strong tool to investigate excitable cells in various sophisticated biological systems.

The human brain represents one of the most complex biological systems, containing billions of neurons interconnected through trillions of synapses. Inherent to the brain is a biochemical complexity involving ions, signaling molecules, and peptides that regulate neuronal activity and allow for short- and long-term adaptations. Large-scale and noninvasive imaging techniques, such as fMRI and EEG, have highlighted brain regions involved in specific functions and visualized connections between different brain areas. A major shortcoming, however, is the need for more information on specific cell types and neurotransmitters involved, as well as poor spatial and temporal resolution. Recent technologies have been advanced for neuronal circuit mapping and implemented in behaving model organisms to address this. Here, we highlight strategies for targeting specific neuronal subtypes, identifying, and releasing signaling molecules, controlling gene expression, and monitoring neuronal circuits in real-time in vivo Combined, these approaches allow us to establish direct causal links from genes and molecules to the systems level and ultimately to cognitive processes.

Despite decades of research on the noradrenergic system, our understanding of its impact on brain function and behavior remains incomplete. Traditional recording techniques are challenging to implement for investigating in vivo noradrenergic activity, due to the relatively small size and the position in the brain of the locus coeruleus (LC), the primary location for noradrenergic neurons. However, recent advances in optical and fluorescent methods have enabled researchers to study the LC more effectively. Use of genetically encoded calcium indicators to image the activity of noradrenergic neurons and biosensors that monitor noradrenaline release with fluorescence can be an indispensable tool for studying noradrenergic activity. In this review, we examine how these methods are being applied to record the noradrenergic system in the rodent brain during behavior.

Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pixel value in voltage imaging data is highly dependent on its spatiotemporal neighboring pixels, even when its temporally adjacent frames alone do not provide useful information for statistical prediction. Such dependency is captured and used by a convolutional neural network with a spatiotemporal blind spot to accurately denoise voltage imaging data in which the existence of the action potential in a time frame cannot be inferred by the information in other frames. Through simulations and experiments, we show that SUPPORT enables precise denoising of voltage imaging data and other types of microscopy image while preserving the underlying dynamics within the scene.

Fluorescent protein (FP)-based biosensors are genetically encoded tools that enable the imaging of biological processes in the context of cells, tissues, or live animals. Though widely used in biological research, practically all existing biosensors are far from ideal in terms of their performance, properties, and applicability for multiplexed imaging. These limitations have inspired researchers to explore an increasing number of innovative and creative ways to improve and maximize biosensor performance. Such strategies include new molecular biology methods to develop promising biosensor prototypes, high throughput microfluidics-based directed evolution screening strategies, and improved ways to perform multiplexed imaging. Yet another approach is to effectively replace components of biosensors with self-labeling proteins, such as HaloTag, that enable the biocompatible incorporation of synthetic fluorophores or other ligands in cells or tissues. This mini-review will summarize and highlight recent innovations and strategies for enhancing the performance of FP-based biosensors for multiplexed imaging to advance the frontiers of research.

Genetically encoded fluorescent indicators are powerful tools for tracking cellular dynamic processes. Engineering these indicators requires balancing screening dimensions with screening throughput. Herein, we present a functional imaging-guided photoactivatable cell selection platform, Faculae (functional imaging-activated molecular evolution), for linking microscopic phenotype with the underlying genotype in a pooled mutant library. Faculae is capable of assessing tens of thousands of variants in mammalian cells simultaneously while achieving photoactivation with single-cell resolution in seconds. To demonstrate the feasibility of this approach, we applied Faculae to perform multidimensional directed evolution for far-red genetically encoded calcium indicators (FR-GECIs) with improved brightness (Nier1b) and signal-to-baseline ratio (Nier1s). We anticipate that this image-based pooled screening method will facilitate the development of a wide variety of biomolecular tools.

Hybrid voltage indicators (HVIs) are chemogenetic sensors that combines the superior photophysical properties of organic dyes and the genetic targetability of protein sensors to report transient membrane voltage changes. They exhibit boosted sensitivity in excitable cells such as neurons and cardiomyocytes. However, the voltage signals recorded during long-term imaging are severely diminished or distorted due to phototoxicity and photobleaching issues. To capture stable electrophysiological activities over a long time, we employ cyanine dyes conjugated with a cyclooctatetraene (COT) molecule as the fluorescence reporter of HVI. The resulting orange-emitting HVI-COT-Cy3 enables high-fidelity voltage imaging for up to 30 min in cultured primary neurons with a sensitivity of ~ -30% ΔF/F0 per action potential (AP). It also maximally preserves the signal of individual APs in cardiomyocytes. The far-red-emitting HVI-COT-Cy5 allows two-color voltage/calcium imaging with GCaMP6s in neurons and cardiomyocytes for 15 min. We leverage the HVI-COT series with reduced phototoxicity and photobleaching to evaluate the impact of drug candidates on the electrophysiology of excitable cells.

The prefrontal cortex (PFC) is a hub for higher-level cognitive behaviors and is a key target for neuroadaptations in alcohol use disorders. Preclinical models of ethanol consumption are instrumental for understanding how acute and repeated drinking affects PFC structure and function. Recent advances in genetically encoded sensors of neuronal activity and neuromodulator release combined with functional microscopy (multiphoton and one-photon widefield imaging) allow multimodal in-vivo PFC recordings at subcellular and cellular scales. While these methods could enable a deeper understanding of the relationship between alcohol and PFC function/dysfunction, they require animals to be head-fixed. Here, we present a method in mice for binge-like ethanol consumption during head-fixation. Male and female mice were first acclimated to ethanol by providing home cage access to 20% ethanol (v/v) for 4 or 8 days. After home cage drinking, mice consumed ethanol from a lick spout during head-fixation. We used two-photon calcium imaging during the head-fixed drinking paradigm to record from a large population of PFC neurons (>1000) to explore how acute ethanol affects their activity. Drinking modulated activity rates in a subset of neurons on slow (minutes) and fast (seconds) time scales but the majority of neurons were unaffected. Moreover, ethanol intake did not significantly affect network level interactions in the PFC as assessed through inter-neuronal pairwise correlations. By establishing a method for binge-like drinking in head-fixed mice, we lay the groundwork for leveraging advanced microscopy technologies to study alcohol-induced neuroadaptations in PFC and other brain circuits.

Dopamine (DA) is a critical neuromodulator involved in various brain functions. To understand how DA regulates neural circuits and behaviors in the physiological and pathological conditions, it is essential to have tools that enable the direct detection of DA dynamics in vivo. Recently, genetically encoded DA sensors based on G protein-coupled receptors revolutionized this field, as it allows us to track in vivo DA dynamic with unprecedented spatial-temporal resolution, high molecular specificity, and sub-second kinetics. In this review, we first summarize traditional DA detection methods. Then we focus on the development of genetically encoded DA sensors and feature its significance to understanding dopaminergic neuromodulation across diverse behaviors and species. Finally, we present our perspectives about the future direction of the next-generation DA sensors and extend their potential applications. Overall, this review offers a comprehensive perspective on the past, present, and future of DA detection tools, with important implications for the study of DA functions in health and disease.

The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics of neural activity, from tiny subthreshold synaptic events in the axon and dendrites at the subcellular level to the fluctuation of field potentials and how they spread across large areas of the brain. Initially, synthetic voltage-sensitive dyes (VSDs) were applied directly to brain tissue via staining, but recent advances in transgenic methods now allow the expression of genetically encoded voltage indicators (GEVIs), specifically in selected neuron types. However, voltage imaging is technically difficult and limited by several methodological constraints that determine its applicability in a given type of experiment. The prevalence of this method is far from being comparable to patch clamp voltage recording or similar routine methods in neuroscience research. There are more than twice as many studies on VSDs as there are on GEVIs. As can be seen from the majority of the papers, most of them are either methodological ones or reviews. However, potentiometric imaging is able to address key questions in neuroscience by recording most or many neurons simultaneously, thus providing unique information that cannot be obtained via other methods. Different types of optical voltage indicators have their advantages and limitations, which we focus on in detail. Here, we summarize the experience of the scientific community in the application of voltage imaging and try to evaluate the contribution of this method to neuroscience research.

Microbial rhodopsin is a family of photoreceptive membrane proteins that commonly consist of a seven-transmembrane domain and a derivative of vitamin-A, retinal, as a chromophore. In 2011, archaeorhodopsin-3 (AR3) was shown to exhibit voltage-dependent fluorescence changes in mammalian cells. Since then, AR3 and its variants have been used as genetically encoded voltage indicators, in which mostly intense laser stimulation (1-1000 W/cm2) is used for the detection of dim fluorescence of rhodopsin, leading to high spatiotemporal resolution. However, intense laser stimulation potentially causes serious cell damage, particularly during long-term imaging over minutes. In this study, we present the successful detection of voltage-sensitive fluorescence of AR3 and its high fluorescence mutant Archon1 in a variety of mammalian cell lines using low-intensity light emitting diode stimulation (0.15 W/cm2) with long exposure time (500 ms). The detection system enables real-time imaging of drug-induced slow changes in voltage within the cells for minutes harmlessly and without fluorescence bleaching. Therefore, we demonstrate a method to quantitatively understand the dynamics of slow changes in membrane voltage on long time scales.