Subcellular Imaging of Voltage and Calcium Signals Reveals Neural Processing In Vivo

Large field-of-view metabolic profiling of murine brain tissue following morphine incubation using label-free multiphoton microscopy

BACKGROUND

Although the effects on neural activation and glucose consumption caused by opiates such as morphine are known, the metabolic machinery underlying opioid use and misuse is not fully explored. Multiphoton microscopy (MPM) techniques have been developed for optical imaging at high spatial resolution. Despite the increased use of MPM for neural imaging, the use of intrinsic optical contrast has seen minimal use in neuroscience.

NEW METHOD

We present a label-free, multimodal microscopy technique for metabolic profiling of murine brain tissue following incubation with morphine sulfate (MSO4). We evaluate two- and three-photon excited autofluorescence, and second and third harmonic generation to determine meaningful intrinsic contrast mechanisms in brain tissue using simultaneous label-free, autofluorescence multi-harmonic (SLAM) microscopy.

RESULTS

Regional differences quantified in the cortex, caudate, and thalamus of the brain demonstrate region-specific changes to metabolic profiles measured from FAD intensity, along with brain-wide quantification. While the overall intensity of FAD signal significantly decreased after morphine incubation, this metabolic molecule accumulated near the nucleus accumbens.

COMPARISON WITH EXISTING METHODS

Histopathology requires tissue fixation and staining to determine cell type and morphology, lacking information about cellular metabolism. Tools such as fMRI or PET imaging have been widely used, but lack cellular resolution. SLAM microscopy obviates the need for tissue preparation, permitting immediate use and imaging of tissue with subcellular resolution in its native environment.

CONCLUSIONS

This study demonstrates the utility of SLAM microscopy for label-free investigations of neural metabolism, especially the intensity changes in FAD autofluorescence and structural morphology from third-harmonic generation.

A recurrent neural circuit in Drosophila deblurs visual inputs

A critical goal of vision is to detect changes in light intensity, even when these changes are blurred by the spatial resolution of the eye and the motion of the animal. Here we describe a recurrent neural circuit in Drosophila that compensates for blur and thereby selectively enhances the perceived contrast of moving edges. Using in vivo , two-photon voltage imaging, we measured the temporal response properties of L1 and L2, two cell types that receive direct synaptic input from photoreceptors. These neurons have biphasic responses to brief flashes of light, a hallmark of cells that encode changes in stimulus intensity. However, the second phase was often much larger than the first, creating an unusual temporal filter. Genetic dissection revealed that recurrent neural circuitry strongly shapes the second phase of the response, informing the structure of a dynamical model. By applying this model to moving natural images, we demonstrate that rather than veridically representing stimulus changes, this temporal processing strategy systematically enhances them, amplifying and sharpening responses. Comparing the measured responses of L2 to model predictions across both artificial and natural stimuli revealed that L2 tunes its properties as the model predicts in order to deblur images. Since this strategy is tunable to behavioral context, generalizable to any time-varying sensory input, and implementable with a common circuit motif, we propose that it could be broadly used to selectively enhance sharp and salient changes.

Stimulus encoding by specific inactivation of cortical neurons

Neuronal ensembles are groups of neurons with correlated activity associated with sensory, motor, and behavioral functions. To explore how ensembles encode information, we investigated responses of visual cortical neurons in awake mice using volumetric two-photon calcium imaging during visual stimulation. We identified neuronal ensembles employing an unsupervised model-free algorithm and, besides neurons activated by the visual stimulus (termed "onsemble"), we also find neurons that are specifically inactivated (termed "offsemble"). Offsemble neurons showed faster calcium decay during stimuli, suggesting selective inhibition. In response to visual stimuli, each ensemble (onsemble+offsemble) exhibited small trial-to-trial variability, high orientation selectivity, and superior predictive accuracy for visual stimulus orientation, surpassing the sum of individual neuron activity. Thus, the combined selective activation and inactivation of cortical neurons enhances visual encoding as an emergent and distributed neural code.

Mapping of multiple neurotransmitter receptor subtypes and distinct protein complexes to the connectome

Neurons express various combinations of neurotransmitter receptor (NR) subunits and receive inputs from multiple neuron types expressing different neurotransmitters. Localizing NR subunits to specific synaptic inputs has been challenging. Here, we use epitope-tagged endogenous NR subunits, expansion light-sheet microscopy, and electron microscopy (EM) connectomics to molecularly characterize synapses in Drosophila. We show that in directionally selective motion-sensitive neurons, different multiple NRs elaborated a highly stereotyped molecular topography with NR localized to specific domains receiving cell-type-specific inputs. Developmental studies suggested that NRs or complexes of them with other membrane proteins determine patterns of synaptic inputs. In support of this model, we identify a transmembrane protein selectively associated with a subset of spatially restricted synapses and demonstrate its requirement for synapse formation through genetic analysis. We propose that mechanisms that regulate the precise spatial distribution of NRs provide a molecular cartography specifying the patterns of synaptic connections onto dendrites.

Dendritic mGluR2 and perisomatic Kv3 signaling regulate dendritic computation of mouse starburst amacrine cells

Dendritic mechanisms driving input-output transformation in starburst amacrine cells (SACs) are not fully understood. Here, we combine two-photon subcellular voltage and calcium imaging and electrophysiological recording to determine the computational architecture of mouse SAC dendrites. We found that the perisomatic region integrates motion signals over the entire dendritic field, providing a low-pass-filtered global depolarization to dendrites. Dendrites integrate local synaptic inputs with this global signal in a direction-selective manner. Coincidental local synaptic inputs and the global motion signal in the outward motion direction generate local suprathreshold calcium transients. Moreover, metabotropic glutamate receptor 2 (mGluR2) signaling in SACs modulates the initiation of calcium transients in dendrites but not at the soma. In contrast, voltage-gated potassium channel 3 (Kv3) dampens fast voltage transients at the soma. Together, complementary mGluR2 and Kv3 signaling in different subcellular regions leads to dendritic compartmentalization and direction selectivity, highlighting the importance of these mechanisms in dendritic computation.

Mapping the neural dynamics of locomotion across the Drosophila brain

Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.

Structural and temporal dynamics analysis of neural circuit from 2002 to 2022: A bibliometric analysis

Background

In the pursuit of causal insights into neural circuit functionality, various interventions, including electrical, genetic, and pharmacological approaches, have been applied over recent decades. This study employs a comprehensive bibliometric perspective to explore the field of neural circuits.

Methods

Reviews and articles on neural circuits were obtained from the Web of Science Core Collection (WOSCC) database on Apr. 12, 2023. In this article, co-authorship analysis, co-occurrence analysis, citation analysis, bibliographic analysis, and co-citation analysis were used to clarify the authors, journals, institutions, countries, topics, and internal associations between them.

Results

More than 2000 organizations from 52 different countries published 3975 articles in the field of "neural circuit" were used to analysis. Luo liqun emerged as the most prolific author, and Deisseroth Karl garners the highest co-citations (3643). The Journal of Neuroscience leaded in publications, while Nature toped in citations. Chinese Academy of Science recorded the highest article count institutionally, with Stanford University ranking first with 14,350 citations. Since 2020, neurodynamic, anxiety-related mechanisms, and GABAergic neurons have gained prominence, shaping the trajectory of neural circuitry research.

Conclusions

Our investigation has discerned a paradigmatic reorientation towards neurodynamic processes, anxiety-related mechanisms, and GABAergic neurons within the domain of neural circuit research. This identification intimates a prospective trajectory for the field. In the future, it is imperative for research endeavors to accord priority to the translational application of these discernments, with the aim of materializing tangible clinical solutions.

Compact Electrochromic Optical Recording of Bioelectric Potentials

Electrochromic optical recording (ECORE) is a label-free method that utilizes electrochromism to optically detect electrical signals in biological cells with a high signal-to-noise ratio and is suitable for long-term recording. However, ECORE usually requires a large and intricate optical setup, making it relatively difficult to transport and to study specimens on a large scale. Here, we present a Compact ECORE (CECORE) apparatus that drastically reduces the spatial footprint and complexity of the ECORE setup whilst maintaining high sensitivity. An autobalancing differential photodetector automates common-mode noise rejection, removing the need for manually adjustable optics, and a compact laser module conserves space compared to a typical laser mount. The result is a simple, easy-to-use, and relatively low cost system that achieves a sensitivity of 16.7 μV (within a factor of 5 of the shot noise limit), and reliably detects action potentials from Human-induced pluripotent stem cell (HiPSC) derived cardiomyocytes. This setup can be further improved to within 1.5 dB of the shot noise limit by filtering out power-line interference.

Multilevel visual motion opponency in Drosophila

Inhibitory interactions between opponent neuronal pathways constitute a common circuit motif across brain areas and species. However, in most cases, synaptic wiring and biophysical, cellular and network mechanisms generating opponency are unknown. Here, we combine optogenetics, voltage and calcium imaging, connectomics, electrophysiology and modeling to reveal multilevel opponent inhibition in the fly visual system. We uncover a circuit architecture in which a single cell type implements direction-selective, motion-opponent inhibition at all three network levels. This inhibition, mediated by GluClα receptors, is balanced with excitation in strength, despite tenfold fewer synapses. The different opponent network levels constitute a nested, hierarchical structure operating at increasing spatiotemporal scales. Electrophysiology and modeling suggest that distributing this computation over consecutive network levels counteracts a reduction in gain, which would result from integrating large opposing conductances at a single instance. We propose that this neural architecture provides resilience to noise while enabling high selectivity for relevant sensory information.

A Miniature Ultrasound Source for Neural Modulation

This work describes a unique ultrasound (US) exposure system designed to create very localized ( [Formula: see text]) sound fields at operating frequencies that are currently being used for preclinical US neuromodulation. This system can expose small clusters of neuronal tissue, such as cell cultures or intact brain structures in target animal models, opening up opportunities to examine possible mechanisms of action. We modified a dental descaler and drove it at a resonance frequency of 96 kHz, well above its nominal operating point of 28 kHz. A ceramic microtip from an ultrasonic wire bonder was attached to the end of the applicator, creating a 100- [Formula: see text] point source. The device was calibrated with a polyvinylidene difluoride (PVDF) membrane hydrophone, in a novel, air-backed, configuration. The experimental results were confirmed by simulation using a monopole model. The results show a consistent decaying sound field from the tip, well-suited to neural stimulation. The system was tested on an existing neurological model, Drosophila melanogaster, which has not previously been used for US neuromodulation experiments. The results show brain-directed US stimulation induces or suppresses motor actions, demonstrated through synchronized tracking of fly limb movements. These results provide the basis for ongoing and future studies of US interaction with neuronal tissue, both at the level of single neurons and intact organisms.

Mapping of multiple neurotransmitter receptor subtypes and distinct protein complexes to the connectome

Neurons express different combinations of neurotransmitter receptor (NR) subunits and receive inputs from multiple neuron types expressing different neurotransmitters. Localizing NR subunits to specific synaptic inputs has been challenging. Here we use epitope tagged endogenous NR subunits, expansion light-sheet microscopy, and EM connectomics to molecularly characterize synapses in Drosophila. We show that in directionally selective motion sensitive neurons, different multiple NRs elaborated a highly stereotyped molecular topography with NR localized to specific domains receiving cell-type specific inputs. Developmental studies suggested that NRs or complexes of them with other membrane proteins determines patterns of synaptic inputs. In support of this model, we identify a transmembrane protein associated selectively with a subset of spatially restricted synapses and demonstrate through genetic analysis its requirement for synapse formation. We propose that mechanisms which regulate the precise spatial distribution of NRs provide a molecular cartography specifying the patterns of synaptic connections onto dendrites.

Voltage Imaging with Engineered Proton-Pumping Rhodopsins: Insights from the Proton Transfer Pathway

Voltage imaging using genetically encoded voltage indicators (GEVIs) has taken the field of neuroscience by storm in the past decade. Its ability to create subcellular and network level readouts of electrical dynamics depends critically on the kinetics of the response to voltage of the indicator used. Engineered microbial rhodopsins form a GEVI subclass known for their high voltage sensitivity and fast response kinetics. Here we review the essential aspects of microbial rhodopsin photocycles that are critical to understanding the mechanisms of voltage sensitivity in these proteins and link them to insights from efforts to create faster, brighter and more sensitive microbial rhodopsin-based GEVIs.

How Flies See Motion

How neurons detect the direction of motion is a prime example of neural computation: Motion vision is found in the visual systems of virtually all sighted animals, it is important for survival, and it requires interesting computations with well-defined linear and nonlinear processing steps-yet the whole process is of moderate complexity. The genetic methods available in the fruit fly Drosophila and the charting of a connectome of its visual system have led to rapid progress and unprecedented detail in our understanding of how neurons compute the direction of motion in this organism. The picture that emerged incorporates not only the identity, morphology, and synaptic connectivity of each neuron involved but also its neurotransmitters, its receptors, and their subcellular localization. Together with the neurons' membrane potential responses to visual stimulation, this information provides the basis for a biophysically realistic model of the circuit that computes the direction of visual motion.

A positively tuned voltage indicator for extended electrical recordings in the brain

Genetically encoded voltage indicators (GEVIs) enable optical recording of electrical signals in the brain, providing subthreshold sensitivity and temporal resolution not possible with calcium indicators. However, one- and two-photon voltage imaging over prolonged periods with the same GEVI has not yet been demonstrated. Here, we report engineering of ASAP family GEVIs to enhance photostability by inversion of the fluorescence-voltage relationship. Two of the resulting GEVIs, ASAP4b and ASAP4e, respond to 100-mV depolarizations with ≥180% fluorescence increases, compared with the 50% fluorescence decrease of the parental ASAP3. With standard microscopy equipment, ASAP4e enables single-trial detection of spikes in mice over the course of minutes. Unlike GEVIs previously used for one-photon voltage recordings, ASAP4b and ASAP4e also perform well under two-photon illumination. By imaging voltage and calcium simultaneously, we show that ASAP4b and ASAP4e can identify place cells and detect voltage spikes with better temporal resolution than commonly used calcium indicators. Thus, ASAP4b and ASAP4e extend the capabilities of voltage imaging to standard one- and two-photon microscopes while improving the duration of voltage recordings.

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.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

Disynaptic inhibition shapes tuning of OFF-motion detectors in Drosophila

The circuitry underlying the detection of visual motion in Drosophila melanogaster is one of the best studied networks in neuroscience. Lately, electron microscopy reconstructions, algorithmic models, and functional studies have proposed a common motif for the cellular circuitry of an elementary motion detector based on both supralinear enhancement for preferred direction and sublinear suppression for null-direction motion. In T5 cells, however, all columnar input neurons (Tm1, Tm2, Tm4, and Tm9) are excitatory. So, how is null-direction suppression realized there? Using two-photon calcium imaging in combination with thermogenetics, optogenetics, apoptotics, and pharmacology, we discovered that it is via CT1, the GABAergic large-field amacrine cell, where the different processes have previously been shown to act in an electrically isolated way. Within each column, CT1 receives excitatory input from Tm9 and Tm1 and provides the sign-inverted, now inhibitory input signal onto T5. Ablating CT1 or knocking down GABA-receptor subunit Rdl significantly broadened the directional tuning of T5 cells. It thus appears that the signal of Tm1 and Tm9 is used both as an excitatory input for preferred direction enhancement and, through a sign inversion within the Tm1/Tm9-CT1 microcircuit, as an inhibitory input for null-direction suppression.

Multisensory learning binds neurons into a cross-modal memory engram

Associating multiple sensory cues with objects and experience is a fundamental brain process that improves object recognition and memory performance. However, neural mechanisms that bind sensory features during learning and augment memory expression are unknown. Here we demonstrate multisensory appetitive and aversive memory in Drosophila. Combining colours and odours improved memory performance, even when each sensory modality was tested alone. Temporal control of neuronal function revealed visually selective mushroom body Kenyon cells (KCs) to be required for enhancement of both visual and olfactory memory after multisensory training. Voltage imaging in head-fixed flies showed that multisensory learning binds activity between streams of modality-specific KCs so that unimodal sensory input generates a multimodal neuronal response. Binding occurs between regions of the olfactory and visual KC axons, which receive valence-relevant dopaminergic reinforcement, and is propagated downstream. Dopamine locally releases GABAergic inhibition to permit specific microcircuits within KC-spanning serotonergic neurons to function as an excitatory bridge between the previously 'modality-selective' KC streams. Cross-modal binding thereby expands the KCs representing the memory engram for each modality into those representing the other. This broadening of the engram improves memory performance after multisensory learning and permits a single sensory feature to retrieve the memory of the multimodal experience.

Direction Selectivity of TmY Neurites in Drosophila

The perception of motion is an important function of vision. Neural wiring diagrams for extracting directional information have been obtained by connectome reconstruction. Direction selectivity in Drosophila is thought to originate in T4/T5 neurons through integrating inputs with different temporal filtering properties. Through genetic screening based on synaptic distribution, we isolated a new type of TmY neuron, termed TmY-ds, that form reciprocal synaptic connections with T4/T5 neurons. Its neurites responded to grating motion along the four cardinal directions and showed a variety of direction selectivity. Intriguingly, its direction selectivity originated from temporal filtering neurons rather than T4/T5. Genetic silencing and activation experiments showed that TmY-ds neurons are functionally upstream of T4/T5. Our results suggest that direction selectivity is generated in a tripartite circuit formed among these three neurons-temporal filtering, TmY-ds, and T4/T5 neurons, in which TmY-ds plays a role in the enhancement of direction selectivity in T4/T5 neurons.

Bioelectricity in Developmental Patterning and Size Control: Evidence and Genetically Encoded Tools in the Zebrafish Model

Developmental patterning is essential for regulating cellular events such as axial patterning, segmentation, tissue formation, and organ size determination during embryogenesis. Understanding the patterning mechanisms remains a central challenge and fundamental interest in developmental biology. Ion-channel-regulated bioelectric signals have emerged as a player of the patterning mechanism, which may interact with morphogens. Evidence from multiple model organisms reveals the roles of bioelectricity in embryonic development, regeneration, and cancers. The Zebrafish model is the second most used vertebrate model, next to the mouse model. The zebrafish model has great potential for elucidating the functions of bioelectricity due to many advantages such as external development, transparent early embryogenesis, and tractable genetics. Here, we review genetic evidence from zebrafish mutants with fin-size and pigment changes related to ion channels and bioelectricity. In addition, we review the cell membrane voltage reporting and chemogenetic tools that have already been used or have great potential to be implemented in zebrafish models. Finally, new perspectives and opportunities for bioelectricity research with zebrafish are discussed.

Voltage to Calcium Transformation Enhances Direction Selectivity in Drosophila T4 Neurons

An important step in neural information processing is the transformation of membrane voltage into calcium signals leading to transmitter release. However, the effect of voltage to calcium transformation on neural responses to different sensory stimuli is not well understood. Here, we use in vivo two-photon imaging of genetically encoded voltage and calcium indicators, ArcLight and GCaMP6f, respectively, to measure responses in direction-selective T4 neurons of female Drosophila Comparison between ArcLight and GCaMP6f signals reveals calcium signals to have a significantly higher direction selectivity compared with voltage signals. Using these recordings, we build a model which transforms T4 voltage responses into calcium responses. Using a cascade of thresholding, temporal filtering and a stationary nonlinearity, the model reproduces experimentally measured calcium responses across different visual stimuli. These findings provide a mechanistic underpinning of the voltage to calcium transformation and show how this processing step, in addition to synaptic mechanisms on the dendrites of T4 cells, enhances direction selectivity in the output signal of T4 neurons. Measuring the directional tuning of postsynaptic vertical system (VS)-cells with inputs from other cells blocked, we found that, indeed, it matches the one of the calcium signal in presynaptic T4 cells.SIGNIFICANCE STATEMENT The transformation of voltage to calcium influx is an important step in the signaling cascade within a nerve cell. While this process has been intensely studied in the context of transmitter release mechanism, its consequences for information transmission and neural computation are unclear. Here, we measured both membrane voltage and cytosolic calcium levels in direction-selective cells of Drosophila in response to a large set of visual stimuli. We found direction selectivity in the calcium signal to be significantly enhanced compared with membrane voltage through a nonlinear transformation of voltage to calcium. Our findings highlight the importance of an additional step in the signaling cascade for information processing within single nerve cells.

Subcellular Imaging of Neuronal Calcium Handling In Vivo

Calcium (Ca2+) imaging has been largely used to examine neuronal activity, but it is becoming increasingly clear that subcellular Ca2+ handling is a crucial component of intracellular signaling. The visualization of subcellular Ca2+ dynamics in vivo, where neurons can be studied in their native, intact circuitry, has proven technically challenging in complex nervous systems. The transparency and relatively simple nervous system of the nematode Caenorhabditis elegans enable the cell-specific expression and in vivo visualization of fluorescent tags and indicators. Among these are fluorescent indicators that have been modified for use in the cytoplasm as well as various subcellular compartments, such as the mitochondria. This protocol enables non-ratiometric Ca2+ imaging in vivo with a subcellular resolution that permits the analysis of Ca2+ dynamics down to the level of individual dendritic spines and mitochondria. Here, two available genetically encoded indicators with different Ca2+ affinities are used to demonstrate the use of this protocol for measuring relative Ca2+ levels within the cytoplasm or mitochondrial matrix in a single pair of excitatory interneurons (AVA). Together with the genetic manipulations and longitudinal observations possible in C. elegans, this imaging protocol may be useful for answering questions regarding how Ca2+ handling regulates neuronal function and plasticity.

Fast and sensitive GCaMP calcium indicators for imaging neural populations

Calcium imaging with protein-based indicators1,2 is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators3-8. The resulting 'jGCaMP8' sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation.

Genetically encoded fluorescent sensors for imaging neuronal dynamics in vivo

The brain relies on many forms of dynamic activities in individual neurons, from synaptic transmission to electrical activity and intracellular signaling events. Monitoring these neuronal activities with high spatiotemporal resolution in the context of animal behavior is a necessary step to achieve a mechanistic understanding of brain function. With the rapid development and dissemination of highly optimized genetically encoded fluorescent sensors, a growing number of brain activities can now be visualized in vivo. To date, cellular calcium imaging, which has been largely used as a proxy for electrical activity, has become a mainstay in systems neuroscience. While challenges remain, voltage imaging of neural populations is now possible. In addition, it is becoming increasingly practical to image over half a dozen neurotransmitters, as well as certain intracellular signaling and metabolic activities. These new capabilities enable neuroscientists to test previously unattainable hypotheses and questions. This review summarizes recent progress in the development and delivery of genetically encoded fluorescent sensors, and highlights example applications in the context of in vivo imaging.

A visuomotor circuit for evasive flight turns in Drosophila

Visual systems extract multiple features from a scene using parallel neural circuits. Ultimately, the separate neural signals must come together to coherently influence action. Here, we characterize a circuit in Drosophila that integrates multiple visual features related to imminent threats to drive evasive locomotor turns. We identified, using genetic perturbation methods, a pair of visual projection neurons (LPLC2) and descending neurons (DNp06) that underlie evasive flight turns in response to laterally moving or approaching visual objects. Using two-photon calcium imaging or whole-cell patch clamping, we show that these cells indeed respond to both translating and approaching visual patterns. Furthermore, by measuring visual responses of LPLC2 neurons after genetically silencing presynaptic motion-sensing neurons, we show that their visual properties emerge by integrating multiple visual features across two early visual structures: the lobula and the lobula plate. This study highlights a clear example of how distinct visual signals converge on a single class of visual neurons and then activate premotor neurons to drive action, revealing a concise visuomotor pathway for evasive flight maneuvers in Drosophila.

Smart genetically-encoded biosensors for the chemical monitoring of living systems

Genetically-encoded biosensors provide the all-optical and non-invasive visualization of dynamic biochemical events within living systems, which has allowed the discovery of profound new insights. Twenty-five years of biosensor development has steadily improved their performance and has provided us with an ever increasing biosensor repertoire. In this feature article, we present recent advances made in biosensor development and provide a perspective on the future direction of the field.

Dual-Color Optical Recording of Bioelectric Potentials by Polymer Electrochromism

Optical recording based on voltage-sensitive fluorescent reporters allows for spatial flexibility of measuring from desired cells, but photobleaching and phototoxicity of the fluorescent labels often limit their sensitivity and recording duration. Voltage-dependent optical absorption, rather than fluorescence, of electrochromic materials, would overcome these limitations to achieve long-term optical recording of bioelectrical signals. Electrochromic materials such as PEDOT:PSS possess the property that an applied voltage can either increase or decrease the light absorption depending on the wavelength. In this work, we harness this anticorrelated light absorption at two different wavelengths to significantly improve the signal detection. With dual-color detection, electrical activity from cells produces signals of opposite polarity, while artifacts, mechanical motions, and technical noises are uncorrelated or positively correlated. Using this technique, we are able to optically record cardiac action potentials with a high signal-to-noise ratio, 10 kHz sampling rate, >15 min recording duration, and no time-dependent degradation of the signal. Furthermore, we can reliably perform multiple recording sessions from the same culture for over 25 days.

Dual-polarity voltage imaging of the concurrent dynamics of multiple neuron types

Genetically encoded fluorescent voltage indicators are ideally suited to reveal the millisecond-scale interactions among and between targeted cell populations. However, current indicators lack the requisite sensitivity for in vivo multipopulation imaging. We describe next-generation green and red voltage sensors, Ace-mNeon2 and VARNAM2, and their reverse response-polarity variants pAce and pAceR. Our indicators enable 0.4- to 1-kilohertz voltage recordings from >50 spiking neurons per field of view in awake mice and ~30-minute continuous imaging in flies. Using dual-polarity multiplexed imaging, we uncovered brain state–dependent antagonism between neocortical somatostatin-expressing (SST + ) and vasoactive intestinal peptide–expressing (VIP + ) interneurons and contributions to hippocampal field potentials from cell ensembles with distinct axonal projections. By combining three mutually compatible indicators, we performed simultaneous triple-population imaging. These approaches will empower investigations of the dynamic interplay between neuronal subclasses at single-spike resolution.

Contrast polarity-specific mapping improves efficiency of neuronal computation for collision detection

Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cell's dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. The lack of retinotopic synaptic arrangement results in the neuron's inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animal's escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.

Excitatory and inhibitory neural dynamics jointly tune motion detection

Neurons integrate excitatory and inhibitory signals to produce their outputs, but the role of input timing in this integration remains poorly understood. Motion detection is a paradigmatic example of this integration, since theories of motion detection rely on different delays in visual signals. These delays allow circuits to compare scenes at different times to calculate the direction and speed of motion. Different motion detection circuits have different velocity sensitivity, but it remains untested how the response dynamics of individual cell types drive this tuning. Here, we sped up or slowed down specific neuron types in Drosophila's motion detection circuit by manipulating ion channel expression. Altering the dynamics of individual neuron types upstream of motion detectors increased their sensitivity to fast or slow visual motion, exposing distinct roles for excitatory and inhibitory dynamics in tuning directional signals, including a role for the amacrine cell CT1. A circuit model constrained by functional data and anatomy qualitatively reproduced the observed tuning changes. Overall, these results reveal how excitatory and inhibitory dynamics together tune a canonical circuit computation.

Sustained deep-tissue voltage recording using a fast indicator evolved for two-photon microscopy

Genetically encoded voltage indicators are emerging tools for monitoring voltage dynamics with cell-type specificity. However, current indicators enable a narrow range of applications due to poor performance under two-photon microscopy, a method of choice for deep-tissue recording. To improve indicators, we developed a multiparameter high-throughput platform to optimize voltage indicators for two-photon microscopy. Using this system, we identified JEDI-2P, an indicator that is faster, brighter, and more sensitive and photostable than its predecessors. We demonstrate that JEDI-2P can report light-evoked responses in axonal termini of Drosophila interneurons and the dendrites and somata of amacrine cells of isolated mouse retina. JEDI-2P can also optically record the voltage dynamics of individual cortical neurons in awake behaving mice for more than 30 min using both resonant-scanning and ULoVE random-access microscopy. Finally, ULoVE recording of JEDI-2P can robustly detect spikes at depths exceeding 400 μm and report voltage correlations in pairs of neurons.

Calcium Imaging of Neural Activity in Fly Photoreceptors

Functional imaging methodologies allow researchers to simultaneously monitor the neural activities of all single neurons in a population, and this ability has led to great advances in neuroscience research. Taking advantage of a genetically tractable model organism, functional imaging in Drosophila provides opportunities to probe scientific questions that were previously unanswerable by electrophysiological recordings. Here, we introduce comprehensive protocols for two-photon calcium imaging in fly visual neurons. We also discuss some challenges in applying optical imaging techniques to study visual systems and consider the best practices for making comparisons between different neuron groups.

Fluorescence Imaging of Neural Activity, Neurochemical Dynamics, and Drug-Specific Receptor Conformation with Genetically Encoded Sensors

Recent advances in fluorescence imaging permit large-scale recording of neural activity and dynamics of neurochemical release with unprecedented resolution in behaving animals. Calcium imaging with highly optimized genetically encoded indicators provides a mesoscopic view of neural activity from genetically defined populations at cellular and subcellular resolutions. Rigorously improved voltage sensors and microscopy allow for robust spike imaging of populational neurons in various brain regions. In addition, recent protein engineering efforts in the past few years have led to the development of sensors for neurotransmitters and neuromodulators. Here, we discuss the development and applications of these genetically encoded fluorescent indicators in reporting neural activity in response to various behaviors in different biological systems as well as in drug discovery. We also report a simple model to guide sensor selection and optimization.

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.

Optogenetic reporters delivered as mRNA facilitate repeatable action potential and calcium handling assessment in human iPSC-derived cardiomyocytes

Electrical activity and intracellular Ca 2+ transients are key features of cardiomyocytes. They can be measured using organic voltage- and Ca 2+-sensitive dyes but their photostability and phototoxicity means they are unsuitable for long-term measurements. Here, we investigated whether genetically-encoded voltage and Ca 2+ indicators (GEVIs and GECIs) delivered as modified mRNA (modRNA) into human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) would be accurate alternatives allowing measurements over long periods. These indicators were detected in hiPSC-CMs for up to 7 days after transfection and did not affect responses to proarrhythmic compounds. Furthermore, using the GEVI ASAP2f we observed action potential prolongation in long QT syndrome models, while the GECI jRCaMP1b facilitated the repeated evaluation of Ca 2+ handling responses for various tyrosine kinase inhibitors. This study demonstrated that modRNAs encoding optogenetic constructs report cardiac physiology in hiPSC-CMs without toxicity or the need for stable integration, illustrating their value as alternatives to organic dyes or other gene delivery methods for expressing transgenes.

Imaging Synaptic Density: The Next Holy Grail of Neuroscience?

The brain is the central and most complex organ in the nervous system, comprising billions of neurons that constantly communicate through trillions of connections called synapses. Despite being formed mainly during prenatal and early postnatal development, synapses are continually refined and eliminated throughout life via complicated and hitherto incompletely understood mechanisms. Failure to correctly regulate the numbers and distribution of synapses has been associated with many neurological and psychiatric disorders, including autism, epilepsy, Alzheimer’s disease, and schizophrenia. Therefore, measurements of brain synaptic density, as well as early detection of synaptic dysfunction, are essential for understanding normal and abnormal brain development. To date, multiple synaptic density markers have been proposed and investigated in experimental models of brain disorders. The majority of the gold standard methodologies (e.g., electron microscopy or immunohistochemistry) visualize synapses or measure changes in pre- and postsynaptic proteins ex vivo. However, the invasive nature of these classic methodologies precludes their use in living organisms. The recent development of positron emission tomography (PET) tracers [such as (¹⁸F)UCB-H or (¹¹C)UCB-J] that bind to a putative synaptic density marker, the synaptic vesicle 2A (SV2A) protein, is heralding a likely paradigm shift in detecting synaptic alterations in patients. Despite their limited specificity, novel, non-invasive magnetic resonance (MR)-based methods also show promise in inferring synaptic information by linking to glutamate neurotransmission. Although promising, all these methods entail various advantages and limitations that must be addressed before becoming part of routine clinical practice. In this review, we summarize and discuss current ex vivo and in vivo methods of quantifying synaptic density, including an evaluation of their reliability and experimental utility. We conclude with a critical assessment of challenges that need to be overcome before successfully employing synaptic density biomarkers as diagnostic and/or prognostic tools in the study of neurological and neuropsychiatric disorders.

Binocular mirror-symmetric microsaccadic sampling enables Drosophila hyperacute 3D vision

To move efficiently, animals must continuously work out their x,y,z positions with respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes’ optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes’ whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila superresolution three-dimensional vision and proposes neural computations for accurately predicting these flies’ depth-perception dynamics, limits, and visual behaviors.

Neural mechanisms behind stereopsis, which requires simultaneous disparity inputs from two eyes, have remained mysterious. Here we show how ultrafast mirror-symmetric photomechanical contractions in the frontal forward-facing left and right eye photoreceptors give Drosophila superresolution three-dimensional (3D) vision. By interlinking multiscale in vivo assays with multiscale simulations, we reveal how these photoreceptor microsaccades—by verging, diverging, and narrowing the eyes’ overlapping receptive fields—channel depth information, as phasic binocular image motion disparity signals in time. We further show how peripherally, outside stereopsis, microsaccadic sampling tracks a flying fly’s optic flow field to better resolve the world in motion. These results change our understanding of how insect compound eyes work and suggest a general dynamic stereo-information sampling strategy for animals, robots, and sensors.

First-order visual interneurons distribute distinct contrast and luminance information across ON and OFF pathways to achieve stable behavior

The accurate processing of contrast is the basis for all visually guided behaviors. Visual scenes with rapidly changing illumination challenge contrast computation because photoreceptor adaptation is not fast enough to compensate for such changes. Yet, human perception of contrast is stable even when the visual environment is quickly changing, suggesting rapid post receptor luminance gain control. Similarly, in the fruit fly Drosophila, such gain control leads to luminance invariant behavior for moving OFF stimuli. Here, we show that behavioral responses to moving ON stimuli also utilize a luminance gain, and that ON-motion guided behavior depends on inputs from three first-order interneurons L1, L2, and L3. Each of these neurons encodes contrast and luminance differently and distributes information asymmetrically across both ON and OFF contrast-selective pathways. Behavioral responses to both ON and OFF stimuli rely on a luminance-based correction provided by L1 and L3, wherein L1 supports contrast computation linearly, and L3 non-linearly amplifies dim stimuli. Therefore, L1, L2, and L3 are not specific inputs to ON and OFF pathways but the lamina serves as a separate processing layer that distributes distinct luminance and contrast information across ON and OFF pathways to support behavior in varying conditions.

A red fluorescent protein with improved monomericity enables ratiometric voltage imaging with ASAP3

A ratiometric genetically encoded voltage indicator (GEVI) would be desirable for tracking transmembrane voltage changes in the presence of sample motion. We performed combinatorial multi-site mutagenesis on a cyan-excitable red fluorescent protein to create the bright and monomeric mCyRFP3, which proved to be uniquely non-perturbing when fused to the GEVI ASAP3. The green/red ratio from ASAP3-mCyRFP3 (ASAP3-R3) reported voltage while correcting for motion artifacts, allowing the visualization of membrane voltage changes in contracting cardiomyocytes and throughout the cell cycle of motile cells.

Connectomic features underlying diverse synaptic connection strengths and subcellular computation

Connectomes generated from electron microscopy images of neural tissue unveil the complex morphology of every neuron and the locations of every synapse interconnecting them. These wiring diagrams may also enable inference of synaptic and neuronal biophysics, such as the functional weights of synaptic connections, but this requires integration with physiological data to properly parameterize. Working with a stereotyped olfactory network in the Drosophila brain, we make direct comparisons of the anatomy and physiology of diverse neurons and synapses with subcellular and subthreshold resolution. We find that synapse density and location jointly predict the amplitude of the somatic postsynaptic potential evoked by a single presynaptic spike. Biophysical models fit to data predict that electrical compartmentalization allows axon and dendrite arbors to balance independent and interacting computations. These findings begin to fill the gap between connectivity maps and activity maps, which should enable new hypotheses about how network structure constrains network function.

Voltage imaging in the olfactory bulb using transgenic mouse lines expressing the genetically encoded voltage indicator ArcLight

Genetically encoded voltage indicators (GEVIs) allow optical recordings of membrane potential changes in defined cell populations. Transgenic reporter animals that facilitate precise and repeatable targeting with high expression levels would further the use of GEVIs in the in vivo mammalian brain. However, the literature on developing and applying transgenic mouse lines as vehicles for GEVI expression is limited. Here we report the first in vivo experiments using a transgenic reporter mouse for the GEVI ArcLight, which utilizes a Cre/tTA dependent expression system (TIGRE 1.0). We developed two mouse lines with ArcLight expression restricted to either olfactory receptor neurons, or a subpopulation of interneurons located in the granule and glomerular layers in the olfactory bulb. The ArcLight expression in these lines was sufficient for in vivo imaging of odorant responses in single trials using epifluorescence and 2-photon imaging. The voltage responses were odor-specific and concentration-dependent, which supported earlier studies about perceptual transformations carried out by the bulb that used calcium sensors of neural activity. This study demonstrates that the ArcLight transgenic line is a flexible genetic tool that can be used to record the neuronal electrical activity of different cell types with a signal-to-noise ratio that is comparable to previous reports using viral transduction.

A single motor neuron determines the rhythm of early motor behavior in Ciona

Recent work in tunicate supports the similarity between the motor circuits of vertebrates and basal deuterostome lineages. To understand how the rhythmic activity in motor circuits is acquired during development of protochordate Ciona, we investigated the coordination of the motor response by identifying a single pair of oscillatory motor neurons (MN2/A10.64). The MN2 neurons had Ca²⁺ oscillation with an ~80-s interval that was cell autonomous even in a dissociated single cell. The Ca²⁺ oscillation of MN2 coincided with the early tail flick (ETF). The spikes of the membrane potential in MN2 gradually correlated with the rhythm of ipsilateral muscle contractions in ETFs. The optogenetic experiments indicated that MN2 is a necessary and sufficient component of ETFs. These results indicate that MN2 is indispensable for the early spontaneous rhythmic motor behavior of Ciona. Our findings shed light on the understanding of development and evolution of chordate rhythmical locomotion.

Flexible filtering by neural inputs supports motion computation across states and stimuli

Sensory systems flexibly adapt their processing properties across a wide range of environmental and behavioral conditions. Such variable processing complicates attempts to extract a mechanistic understanding of sensory computations. This is evident in the highly constrained, canonical Drosophila motion detection circuit, where the core computation underlying direction selectivity is still debated despite extensive studies. Here we measured the filtering properties of neural inputs to the OFF motion-detecting T5 cell in Drosophila. We report state- and stimulus-dependent changes in the shape of these signals, which become more biphasic under specific conditions. Summing these inputs within the framework of a connectomic-constrained model of the circuit demonstrates that these shapes are sufficient to explain T5 responses to various motion stimuli. Thus, our stimulus- and state-dependent measurements reconcile motion computation with the anatomy of the circuit. These findings provide a clear example of how a basic circuit supports flexible sensory computation.

An Autonomous Molecular Bioluminescent Reporter (AMBER) for Voltage Imaging in Freely Moving Animals

Genetically encoded reporters have greatly increased our understanding of biology. While fluorescent reporters have been widely used, photostability and phototoxicity have hindered their use in long-term experiments. Bioluminescence overcomes some of these challenges but requires the addition of an exogenous luciferin limiting its use. Using a modular approach, Autonomous Molecular BioluminEscent Reporter (AMBER), an indicator of membrane potential is engineered. Unlike other bioluminescent systems, AMBER is a voltage-gated luciferase coupling the functionalities of the Ciona voltage-sensing domain (VSD) and bacterial luciferase, luxAB. When co-expressed with the luciferin-producing genes, AMBER reversibly switches the bioluminescent intensity as a function of membrane potential. Using biophysical and biochemical methods, it is shown that AMBER switches its enzymatic activity from an OFF to an ON state as a function of the membrane potential. Upon depolarization, AMBER switches from a low to a high enzymatic activity state, showing a several-fold increase in the bioluminescence output (ΔL/L). AMBER in the pharyngeal muscles and mechanosensory touch neurons of Caenorhabditis elegans is expressed. Using the compressed sensing approach, the electropharingeogram of the C. elegans pharynx is reconstructed, validating the sensor in vivo. Thus, AMBER represents the first fully genetically encoded bioluminescent reporter without requiring exogenous luciferin addition.

Voltage Imaging in Drosophila Using a Hybrid Chemical-Genetic Rhodamine Voltage Reporter

We combine a chemically-synthesized, voltage-sensitive fluorophore with a genetically encoded, self-labeling enzyme to enable voltage imaging in Drosophila melanogaster. Previously, we showed that a rhodamine voltage reporter (RhoVR) combined with the HaloTag self-labeling enzyme could be used to monitor membrane potential changes from mammalian neurons in culture and brain slice. Here, we apply this hybrid RhoVR-Halo approach in vivo to achieve selective neuron labeling in intact fly brains. We generate a Drosophila UAS-HaloTag reporter line in which the HaloTag enzyme is expressed on the surface of cells. We validate the voltage sensitivity of this new construct in cell culture before driving expression of HaloTag in specific brain neurons in flies. We show that selective labeling of synapses, cells, and brain regions can be achieved with RhoVR-Halo in either larval neuromuscular junction (NMJ) or in whole adult brains. Finally, we validate the voltage sensitivity of RhoVR-Halo in fly tissue via dual-electrode/imaging at the NMJ, show the efficacy of this approach for measuring synaptic excitatory post-synaptic potentials (EPSPs) in muscle cells, and perform voltage imaging of carbachol-evoked depolarization and osmolarity-evoked hyperpolarization in projection neurons and in interoceptive subesophageal zone neurons in fly brain explants following in vivo labeling. We envision the turn-on response to depolarizations, fast response kinetics, and two-photon compatibility of chemical indicators, coupled with the cellular and synaptic specificity of genetically-encoded enzymes, will make RhoVR-Halo a powerful complement to neurobiological imaging in Drosophila.

Constructing and Tuning Excitatory Cholinergic Synapses: The Multifaceted Functions of Nicotinic Acetylcholine Receptors in Drosophila Neural Development and Physiology

Nicotinic acetylcholine receptors (nAchRs) are widely distributed within the nervous system across most animal species. Besides their well-established roles in mammalian neuromuscular junctions, studies using invertebrate models have also proven fruitful in revealing the function of nAchRs in the central nervous system. During the earlier years, both in vitro and animal studies had helped clarify the basic molecular features of the members of the Drosophila nAchR gene family and illustrated their utility as targets for insecticides. Later, increasingly sophisticated techniques have illuminated how nAchRs mediate excitatory neurotransmission in the Drosophila brain and play an integral part in neural development and synaptic plasticity, as well as cognitive processes such as learning and memory. This review is intended to provide an updated survey of Drosophila nAchR subunits, focusing on their molecular diversity and unique contributions to physiology and plasticity of the fly neural circuitry. We will also highlight promising new avenues for nAchR research that will likely contribute to better understanding of central cholinergic neurotransmission in both Drosophila and other organisms.

Monitoring of compound resting membrane potentials of cell cultures with ratiometric genetically encoded voltage indicators

The cellular resting membrane potential (V_m) not only determines electrical responsiveness of excitable cells but also plays pivotal roles in non-excitable cells, mediating membrane transport, cell-cycle progression, and tumorigenesis. Studying these processes requires estimation of V_m, ideally over long periods of time. Here, we introduce two ratiometric genetically encoded V_m indicators, rArc and rASAP, and imaging and analysis procedures for measuring differences in average resting V_m between cell groups. We investigated the influence of ectopic expression of K⁺ channels and their disease-causing mutations involved in Andersen-Tawil (Kir2.1) and Temple-Baraitser (K_V10.1) syndrome on median resting V_m of HEK293T cells. Real-time long-term monitoring of V_m changes allowed to estimate a 40–50 min latency from induction of transcription to functional Kir2.1 channels in HEK293T cells. The presented methodology is readily implemented with standard fluorescence microscopes and offers deeper insights into the role of the resting V_m in health and disease.

Rühl et al. report the generation of ratiometric genetically encoded voltage indicators (GEVIs) and establish that they can be used in high-throughput automated imaging to measure compound membrane potential (Vm) in mammalian cells. This method is implementable with standard fluorescence microscopes and has the potential to offer insights into the role of the resting Vm in health and disease.

Miniature microscopes for manipulating and recording in vivo brain activity

Here we describe the development and application of miniature integrated microscopes (miniscopes) paired with microendoscopes that allow for the visualization and manipulation of neural circuits in superficial and subcortical brain regions in freely behaving animals. Over the past decade the miniscope platform has expanded to include simultaneous optogenetic capabilities, electrically-tunable lenses that enable multi-plane imaging, color-corrected optics, and an integrated data acquisition platform that streamlines multimodal experiments. Miniscopes have given researchers an unprecedented ability to monitor hundreds to thousands of genetically-defined neurons from weeks to months in both healthy and diseased animal brains. Sophisticated algorithms that take advantage of constrained matrix factorization allow for background estimation and reliable cell identification, greatly improving the reliability and scalability of source extraction for large imaging datasets. Data generated from miniscopes have empowered researchers to investigate the neural circuit underpinnings of a wide array of behaviors that cannot be studied under head-fixed conditions, such as sleep, reward seeking, learning and memory, social behaviors, and feeding. Importantly, the miniscope has broadened our understanding of how neural circuits can go awry in animal models of progressive neurological disorders, such as Parkinson's disease. Continued miniscope development, including the ability to record from multiple populations of cells simultaneously, along with continued multimodal integration of techniques such as electrophysiology, will allow for deeper understanding into the neural circuits that underlie complex and naturalistic behavior.

Predicting individual neuron responses with anatomically constrained task optimization

Artificial neural networks trained to solve sensory tasks can develop statistical representations that match those in biological circuits. However, it remains unclear whether they can reproduce properties of individual neurons. Here, we investigated how artificial networks predict individual neuron properties in the visual motion circuits of the fruit fly Drosophila. We trained anatomically constrained networks to predict movement in natural scenes, solving the same inference problem as fly motion detectors. Units in the artificial networks adopted many properties of analogous individual neurons, even though they were not explicitly trained to match these properties. Among these properties was the split into ON and OFF motion detectors, which is not predicted by classical motion detection models. The match between model and neurons was closest when models were trained to be robust to noise. These results demonstrate how anatomical, task, and noise constraints can explain properties of individual neurons in a small neural network.