A fast and responsive voltage indicator with enhanced sensitivity for unitary synaptic events.

A remaining challenge for genetically encoded voltage indicators (GEVIs) is the reliable detection of excitatory postsynaptic potentials (EPSPs). Here, we developed ASAP5 as a GEVI with enhanced activation kinetics and responsivity near resting membrane potentials for improved detection of both spiking and subthreshold activity. ASAP5 reported action potentials (APs) in vivo with higher signal-to-noise ratios than previous GEVIs and successfully detected graded and subthreshold responses to sensory stimuli in single two-photon trials. In cultured rat or human neurons, somatic ASAP5 reported synaptic events propagating centripetally and could detect ∼1-mV EPSPs. By imaging spontaneous EPSPs throughout dendrites, we found that EPSP amplitudes decay exponentially during propagation and that amplitude at the initiation site generally increases with distance from the soma. These results extend the applications of voltage imaging to the quantal response domain, including in human neurons, opening up the possibility of high-throughput, high-content characterization of neuronal dysfunction in disease.

Optical constraints on two-photon voltage imaging.

Significance: 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. Aim: 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. Approach: 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. Results: 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. Conclusions: 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.

DIY adapting SEM for low-voltage TEM imaging.

Electron microscopy is essential for examining materials and biological samples at microscopic levels, providing detailed insights. Achieving high-quality imaging is often challenged by the potential damage high-energy beams can cause to sensitive samples. This study compares scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to evaluate image quality, noise levels, and the ability to preserve delicate specimens. We used a modified SEM system with a transmitted electrons conversion accessory, allowing it to operate like a TEM but at lower voltages, thereby reducing sample damage. Our analysis included quantitative assessments of noise levels and texture characteristics such as entropy, contrast, dissimilarity, homogeneity, energy, and correlation. This comprehensive evaluation directly compared traditional TEM and the adapted SEM system across various images. The results showed that TEM provided images with higher clarity and significantly lower noise levels, reinforcing its status as the preferred method for detailed studies. However, the modified SEM system also produced high-quality images at very low acceleration voltages, which is crucial for imaging samples sensitive to high-energy exposure. The texture metrics analysis highlighted the strengths and limitations of each method, with TEM images exhibiting lower entropy and higher homogeneity, indicating smoother and more uniform textures. This study emphasizes the importance of selecting the appropriate electron microscopy method based on research needs, such as sample sensitivity and required detail level. With its conversion accessory, the modified SEM system is a versatile and valuable tool, offering a practical alternative to TEM for various applications. This research enhances our understanding of the capabilities and limitations of SEM and TEM. It paves the way for further innovations in electron microscopy techniques, improving their applicability for studying sensitive materials. RESEARCH HIGHLIGHTS: Our study introduces a modified SEM adapter enabling TEM-like imaging at reduced voltages, effectively minimizing sample damage without compromising image resolution. Through comparative analysis, we found that images from the modified SEM closely match the quality of traditional TEM, showcasing significantly lower noise levels. This advancement underscores the SEM's enhanced capability for detailed structural analysis of sensitive materials, broadening its utility across materials science and biology.

Evolution of Bioelectric Membrane Potentials: Implications in Cancer Pathogenesis and Therapeutic Strategies.

Electrophysiology typically deals with the electrical properties of excitable cells like neurons and muscles. However, all other cells (non-excitable) also possess bioelectric membrane potentials for intracellular and extracellular communications. These membrane potentials are generated by different ions present in fluids available in and outside the cell, playing a vital role in communication and coordination between the cell and its organelles. Bioelectric membrane potential variations disturb cellular ionic homeostasis and are characteristic of many diseases, including cancers. A rapidly increasing interest has emerged in sorting out the electrophysiology of cancer cells. Compared to healthy cells, the distinct electrical properties exhibited by cancer cells offer a unique way of understanding cancer development, migration, and progression. Decoding the altered bioelectric signals influenced by fluctuating electric fields benefits understanding cancer more closely. While cancer research has predominantly focussed on genetic and molecular traits, the delicate area of electrophysiological characteristics has increasingly gained prominence. This review explores the historical exploration of electrophysiology in the context of cancer cells, shedding light on how alterations in bioelectric membrane potentials, mediated by ion channels and gap junctions, contribute to the pathophysiology of cancer.

Dynamic assemblies of parvalbumin interneurons in brain oscillations.

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.

Extended voltage imaging in cardiomyocytes with a triplet state quencher-stabilized silicon rhodamine.

Voltage imaging of cardiac electrophysiology with voltage-sensitive dyes has long been a powerful complement to traditional methods like patch-clamp electrophysiology. Chemically synthesized voltage sensitive fluorophores offer flexibility for imaging in sensitive samples like human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs), since they do not require genetic transformation of the sample. One serious concern for any fluorescent voltage indicator, whether chemically synthesized or genetically encoded, is phototoxicity. We have been exploring self-healing fluorophores that use triplet state quenchers (TSQs) as a means to reduce the already low phototoxicity of VoltageFluor dyes developed in our lab. We previously showed that conjugation of the TSQ cyclooctatetraene (COT) to a fluorescein based VoltageFluor dye substantially reduced phototoxicity. Here, we show that this approach can be applied to far-red Silicon rhodamine dyes. COT-conjugated Si-rhodamines show improved photostability and reduced phototoxicity in hiPSC-CMs compared to the unmodified dye. This enables imaging of hiPSC-CMs for up to 30 min with continuous illumination. We show that this effect is mediated by a combination of reduced singlet oxygen production and lower loading in the cellular membrane. We discuss future applications and avenues of improvement for TSQ-stabilized VoltageFluor dyes.

Probing neuronal activity with genetically encoded calcium and voltage fluorescent indicators.

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.

Two-dimensional electro-optical multiphoton microscopy.

Significance: The development of genetically encoded fluorescent indicators of neural activity with millisecond dynamics has generated demand for ever faster two-photon (2P) imaging systems, but acoustic and mechanical beam scanning technologies are approaching fundamental limits. We demonstrate that potassium tantalate niobate (KTN) electro-optical deflectors (EODs), which are not subject to the same fundamental limits, are capable of ultrafast two-dimensional (2D) 2P imaging in vivo. Aim: To determine if KTN-EODs are suitable for 2P imaging, compatible with 2D scanning, and capable of ultrafast in vivo imaging of genetically encoded indicators with millisecond dynamics. Approach: The performance of a commercially available KTN-EOD was characterized across a range of drive frequencies and laser parameters relevant to in vivo 2P microscopy. A second KTN-EOD was incorporated into a dual-axis scan module, and the system was validated by imaging signals in vivo from ASAP3, a genetically encoded voltage indicator. Results: Optimal KTN-EOD deflection of laser light with a central wavelength of 960 nm was obtained up to the highest average powers and pulse intensities tested (power: 350 mW; pulse duration: 118 fs). Up to 32 resolvable spots per line at a 560 kHz line scan rate could be obtained with single-axis deflection. The complete dual-axis EO 2P microscope was capable of imaging a 13 µm by 13 µm field-of-view at over 10 kHz frame rate with ∼0.5 µm lateral resolution. We demonstrate in vivo imaging of neurons expressing ASAP3 with high temporal resolution. Conclusions: We demonstrate the suitability of KTN-EODs for ultrafast 2P cellular imaging in vivo, providing a foundation for future high-performance microscopes to incorporate emerging advances in KTN-based scanning technology.

DeepVID v2: Self-Supervised Denoising with Decoupled Spatiotemporal Enhancement for Low-Photon Voltage Imaging.

Significance: Voltage imaging is a powerful tool for studying the dynamics of neuronal activities in the brain. However, voltage imaging data are fundamentally corrupted by severe Poisson noise in the low-photon regime, which hinders the accurate extraction of neuronal activities. Self-supervised deep learning denoising methods have shown great potential in addressing the challenges in low-photon voltage imaging without the need for ground truth, but usually suffer from the tradeoff between spatial and temporal performance. Aim: We present DeepVID v2, a novel self-supervised denoising framework with decoupled spatial and temporal enhancement capability to significantly augment low-photon voltage imaging. Approach: DeepVID v2 is built on our original DeepVID framework,1,2 which performs frame-based denoising by utilizing a sequence of frames around the central frame targeted for denoising to leverage temporal information and ensure consistency. The network further integrates multiple blind pixels in the central frame to enrich the learning of local spatial information. Additionally, DeepVID v2 introduces a new edge extraction branch to capture fine structural details in order to learn high spatial resolution information. Results: We demonstrate that DeepVID v2 is able to overcome the tradeoff between spatial and temporal performance, and achieve superior denoising capability in resolving both high-resolution spatial structures and rapid temporal neuronal activities. We further show that DeepVID v2 is able to generalize to different imaging conditions, including time-series measurements with various signal-to-noise ratios (SNRs) and in extreme low-photon conditions. Conclusions: Our results underscore DeepVID v2 as a promising tool for enhancing voltage imaging. This framework has the potential to generalize to other low-photon imaging modalities and greatly facilitate the study of neuronal activities in the brain.

Cortical Networks Relating to Arousal Are Differentially Coupled to Neural Activity and Hemodynamics.

Even in the absence of specific sensory input or a behavioral task, the brain produces structured patterns of activity. This organized activity is modulated by changes in arousal. Here, we use wide-field voltage imaging to establish how arousal relates to cortical network voltage and hemodynamic activity in spontaneously behaving head-fixed male and female mice expressing the voltage-sensitive fluorescent FRET sensor Butterfly 1.2. We find that global voltage and hemodynamic signals are both positively correlated with changes in arousal with a maximum correlation of 0.5 and 0.25, respectively, at a time lag of 0 s. We next show that arousal influences distinct cortical regions for both voltage and hemodynamic signals. These include a broad positive correlation across most sensory-motor cortices extending posteriorly to the primary visual cortex observed in both signals. In contrast, activity in the prefrontal cortex is positively correlated to changes in arousal for the voltage signal while it is a slight net negative correlation observed in the hemodynamic signal. Additionally, we show that coherence between voltage and hemodynamic signals relative to arousal is strongest for slow frequencies below 0.15 Hz and is near zero for frequencies >1 Hz. We finally show that coupling patterns are dependent on the behavioral state of the animal with correlations being driven by periods of increased orofacial movement. Our results indicate that while hemodynamic signals show strong relations to behavior and arousal, these relations are distinct from those observed by voltage activity.

Intrinsic and Synaptic Contributions to Repetitive Spiking in Dentate Granule Cells.

Repetitive firing of granule cells (GCs) in the dentate gyrus (DG) facilitates synaptic transmission to the CA3 region. This facilitation can gate and amplify the flow of information through the hippocampus. High-frequency bursts in the DG are linked to behavior and plasticity, but GCs do not readily burst. Under normal conditions, a single shock to the perforant path in a hippocampal slice typically drives a GC to fire a single spike, and only occasionally more than one spike is seen. Repetitive spiking in GCs is not robust, and the mechanisms are poorly understood. Here, we used a hybrid genetically encoded voltage sensor to image voltage changes evoked by cortical inputs in many mature GCs simultaneously in hippocampal slices from male and female mice. This enabled us to study relatively infrequent double and triple spikes. We found GCs are relatively homogeneous and their double spiking behavior is cell autonomous. Blockade of GABA type A receptors increased multiple spikes and prolonged the interspike interval, indicating inhibitory interneurons limit repetitive spiking and set the time window for successive spikes. Inhibiting synaptic glutamate release showed that recurrent excitation mediated by hilar mossy cells contributes to, but is not necessary for, multiple spiking. Blockade of T-type Ca2+ channels did not reduce multiple spiking but prolonged interspike intervals. Imaging voltage changes in different GC compartments revealed that second spikes can be initiated in either dendrites or somata. Thus, pharmacological and biophysical experiments reveal roles for both synaptic circuitry and intrinsic excitability in GC repetitive spiking.

Characterization of two near-infrared genetically encoded voltage indicators.

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

Microglia mediate contact-independent neuronal pruning via secreted Neuraminidase-3 associated with extracellular vesicles.

Neurons communicate with each other through electrochemical transmission at synapses. Microglia, the resident immune cells of the central nervous system, can prune these synapses through a variety of contact-dependent and -independent means. Microglial secretion of active sialidase enzymes upon exposure to inflammatory stimuli is one unexplored mechanism of pruning. Recent work from our lab showed that treatment of neurons with bacterial sialidases disrupts neuronal network connectivity. Here, we find that activated microglia secrete Neuraminidase-3 (Neu3) associated with fusogenic extracellular vesicles. Furthermore, we show Neu3 mediates contact-independent pruning of neurons and subsequent disruption of neuronal networks through neuronal glycocalyx remodeling. We observe that NEU3 is transcriptionally upregulated upon exposure to inflammatory stimuli, and that a genetic knock-out of NEU3 abrogates the sialidase activity of inflammatory microglial secretions. Moreover, we demonstrate that Neu3 is associated with a subpopulation of extracellular vesicles, possibly exosomes, that are secreted by microglia upon inflammatory insult. Finally, we demonstrate that Neu3 is both necessary and sufficient to both desialylate neurons and decrease neuronal network connectivity. These results implicate Neu3 in remodeling of the glycocalyx leading to aberrant network-level activity of neurons, with implications in neuroinflammatory diseases such as Parkinson's disease and Alzheimer's disease.

Theta and gamma rhythmic coding through two spike output modes in the hippocampus during spatial navigation.

Hippocampal CA1 neurons generate single spikes and stereotyped bursts of spikes. However, it is unclear how individual neurons dynamically switch between these output modes and whether these two spiking outputs relay distinct information. We performed extracellular recordings in spatially navigating rats and cellular voltage imaging and optogenetics in awake mice. We found that spike bursts are preferentially linked to cellular and network theta rhythms (3-12 Hz) and encode an animal's position via theta phase precession, particularly as animals are entering a place field. In contrast, single spikes exhibit additional coupling to gamma rhythms (30-100 Hz), particularly as animals leave a place field. Biophysical modeling suggests that intracellular properties alone are sufficient to explain the observed input frequency-dependent spike coding. Thus, hippocampal neurons regulate the generation of bursts and single spikes according to frequency-specific network and intracellular dynamics, suggesting that these spiking modes perform distinct computations to support spatial behavior.

A Retrofittable Photoelectron Gun for Low-Voltage Imaging Applications in the Scanning Electron Microscope.

Low-voltage scanning electron microscopy is a powerful tool for examining surface features and imaging beam-sensitive materials. Improving resolution during low-voltage imaging is then an important area of development. Decreasing the effect of chromatic aberration is one solution to improving the resolution and can be achieved by reducing the energy spread of the electron source. Our approach involves retrofitting a light source onto a thermionic lanthanum hexaboride (LaB6) electron gun as a cost-effective low energy-spread photoelectron emitter. The energy spread of the emitter's photoelectrons is theorized to be between 0.11 and 0.38 eV, depending on the photon energy of the ultraviolet (UV) light source. Proof-of-principle images have been recorded using this retrofitted photoelectron gun, and an analysis of its performance is presented.

Cortical Correlates of Psychedelic-Induced Shaking Behavior Revealed by Voltage Imaging.

(1) From mouse to man, shaking behavior (head twitches and/or wet dog shakes) is a reliable readout of psychedelic drug action. Shaking behavior like psychedelia is thought to be mediated by serotonin 2A receptors on cortical pyramidal cells. The involvement of pyramidal cells in psychedelic-induced shaking behavior remains hypothetical, though, as experimental in vivo evidence is limited. (2) Here, we use cell type-specific voltage imaging in awake mice to address this issue. We intersectionally express the genetically encoded voltage indicator VSFP Butterfly 1.2 in layer 2/3 pyramidal neurons. We simultaneously capture cortical hemodynamics and cell type-specific voltage activity while mice display psychedelic shaking behavior. (3) Shaking behavior is preceded by high-frequency oscillations and overlaps with low-frequency oscillations in the motor cortex. Oscillations spectrally mirror the rhythmics of shaking behavior and reflect layer 2/3 pyramidal cell activity complemented by hemodynamics. (4) Our results reveal a clear cortical fingerprint of serotonin-2A-receptor-mediated shaking behavior and open a promising methodological avenue relating a cross-mammalian psychedelic effect to cell-type specific brain dynamics.

Current Practice in Using Voltage Imaging to Record Fast Neuronal Activity: Successful Examples from Invertebrate to Mammalian Studies.

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.

Assessment of Tissue Viability by Functional Imaging of Membrane Potential.

Electrical activity plays a key role in physiology, in particular for signaling and coordination. Cellular electrophysiology is often studied with micropipette-based techniques such as patch clamp and sharp electrodes, but for measurements at the tissue or organ scale, more integrated approaches are needed. Epifluorescence imaging of voltage-sensitive dyes ("optical mapping") is a tissue non-destructive approach to obtain insight into electrophysiology with high spatiotemporal resolution. Optical mapping has primarily been applied to excitable organs, especially the heart and brain. Action potential durations, conduction patterns, and conduction velocities can be determined from the recordings, providing information about electrophysiological mechanisms, including factors such as effects of pharmacological interventions, ion channel mutations, or tissue remodeling. Here, we describe the process for optical mapping of Langendorff-perfused mouse hearts, highlighting potential issues and key considerations.

Awakening from anesthesia switches cortical wave modes.

Spontaneous cortical activity exhibits diverse spatiotemporal dynamics across brain states, but the organizational principles during state transitions remain unclear. In a recent study combining cortex-wide voltage imaging and neural modeling, Liang and colleagues revealed that global-local competition and long-range connections underlie the emergence of complex cortical wave patterns during awakening from anesthesia.

Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator.

The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.