Chronic calcium imaging in neuronal development and disease

New imaging instrument in animal models: Two-photon miniature microscope and large field of view miniature microscope for freely behaving animals

Over the past decade, novel optical imaging tools have been developed for imaging neuronal activities along with the evolution of fluorescence indicators with brighter expression and higher sensitivity. Miniature microscopes, as revolutionary approaches, enable the imaging of large populations of neuron ensembles in freely behaving rodents and mammals, which allows exploring the neural basis of behaviors. Recent progress in two-photon miniature microscopes and mesoscale single-photon miniature microscopes further expand those affordable methods to navigate neural activities during naturalistic behaviors. In this review article, two-photon miniature microscopy techniques are summarized historically from the first documented attempt to the latest ones, and comparisons are made. The driving force behind and their potential for neuroscientific inquiries are also discussed. Current progress in terms of the mesoscale, i.e., the large field-of-view miniature microscopy technique, is addressed as well. Then, pipelines for registering single cells from the data of two-photon and large field-of-view miniature microscopes are discussed. Finally, we present the potential evolution of the techniques.

Chronic Ca2+ imaging of cortical neurons with long-term expression of GCaMP-X

Dynamic Ca2+ signals reflect acute changes in membrane excitability, and also mediate signaling cascades in chronic processes. In both cases, chronic Ca2+ imaging is often desired, but challenged by the cytotoxicity intrinsic to calmodulin (CaM)-based GCaMP, a series of genetically-encoded Ca2+ indicators that have been widely applied. Here, we demonstrate the performance of GCaMP-X in chronic Ca2+ imaging of cortical neurons, where GCaMP-X by design is to eliminate the unwanted interactions between the conventional GCaMP and endogenous (apo)CaM-binding proteins. By expressing in adult mice at high levels over an extended time frame, GCaMP-X showed less damage and improved performance in two-photon imaging of sensory (whisker-deflection) responses or spontaneous Ca2+ fluctuations, in comparison with GCaMP. Chronic Ca2+ imaging of one month or longer was conducted for cultured cortical neurons expressing GCaMP-X, unveiling that spontaneous/local Ca2+ transients progressively developed into autonomous/global Ca2+ oscillations. Along with the morphological indices of neurite length and soma size, the major metrics of oscillatory Ca2+, including rate, amplitude and synchrony were also examined. Dysregulations of both neuritogenesis and Ca2+ oscillations became discernible around 2-3 weeks after virus injection or drug induction to express GCaMP in newborn or mature neurons, which were exacerbated by stronger or prolonged expression of GCaMP. In contrast, neurons expressing GCaMP-X were significantly less damaged or perturbed, altogether highlighting the unique importance of oscillatory Ca2+ to neural development and neuronal health. In summary, GCaMP-X provides a viable solution for Ca2+ imaging applications involving long-time and/or high-level expression of Ca2+ probes.

Monitoring Astrocytic Ca2+ Activity in Freely Behaving Mice

Monitoring astrocytic Ca²⁺ activity is essential to understand the physiological and pathological roles of astrocytes in the brain. However, previous commonly used methods for studying astrocytic Ca²⁺ activities can be applied in only anesthetized or head-fixed animals, which significantly affects in vivo astrocytic Ca²⁺ dynamics. In the current study, we combined optic fiber recordings with genetically encoded Ca²⁺ indicators (GECIs) to monitor astrocytic activity in freely behaving mice. This approach enabled selective and reliable measurement of astrocytic Ca²⁺ activity, which was verified by the astrocyte-specific labeling of GECIs and few movement artifacts. Additionally, astrocytic Ca²⁺ activities induced by locomotion or footshock were stably recorded in the cortices and hippocampi of freely behaving mice. Furthermore, this method allowed for the longitudinal study of astrocytic activities over several weeks. This work provides a powerful approach to record astrocytic activity selectively, stably, and chronically in freely behaving mice.

Long-term optical brain imaging in live adult fruit flies

Time-lapse in vivo microscopy studies of cellular morphology and physiology are crucial toward understanding brain function but have been infeasible in the fruit fly, a key model species. Here we use laser microsurgery to create a chronic fly preparation for repeated imaging of neural architecture and dynamics for up to 50 days. In fly mushroom body neurons, we track axonal boutons for 10 days and record odor-evoked calcium transients over 7 weeks. Further, by using voltage imaging to resolve individual action potentials, we monitor spiking plasticity in dopamine neurons of flies undergoing mechanical stress. After 24 h of stress, PPL1-α’3 but not PPL1-α’2α2 dopamine neurons have elevated spike rates. Overall, our chronic preparation is compatible with a broad range of optical techniques and enables longitudinal studies of many biological questions that could not be addressed before in live flies.

Time-lapse imaging studies of more than a day in the fly brain have been infeasible until now. Here the authors present a laser microsurgery approach to create a permanent window in the fly cuticle to enable time-lapse imaging of neural architecture and dynamics for up to 10–50 days.

Genetically Encoded Calcium Indicators as Probes to Assess the Role of Calcium Channels in Disease and for High-Throughput Drug Discovery

The calcium ion (Ca²⁺) is an important signaling molecule implicated in many cellular processes, and the remodeling of Ca²⁺ homeostasis is a feature of a variety of pathologies. Typical methods to assess Ca²⁺ signaling in cells often employ small molecule fluorescent dyes, which are sometimes poorly suited to certain applications such as assessment of cellular processes, which occur over long periods (hours or days) or in vivo experiments. Genetically encoded calcium indicators are a set of tools available for the measurement of Ca²⁺ changes in the cytosol and subcellular compartments, which circumvent some of the inherent limitations of small molecule Ca²⁺ probes. Recent advances in genetically encoded calcium sensors have greatly increased their ability to provide reliable monitoring of Ca²⁺ changes in mammalian cells. New genetically encoded calcium indicators have diverse options in terms of targeting, Ca²⁺ affinity and fluorescence spectra, and this will further enhance their potential use in high-throughput drug discovery and other assays. This review will outline the methods available for Ca²⁺ measurement in cells, with a focus on genetically encoded calcium sensors. How these sensors will improve our understanding of the deregulation of Ca²⁺ handling in disease and their application to high-throughput identification of drug leads will also be discussed.

Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data

Inferring connectivity in neuronal networks remains a key challenge in statistical neuroscience. The “common input” problem presents a major roadblock: it is difficult to reliably distinguish causal connections between pairs of observed neurons versus correlations induced by common input from unobserved neurons. Available techniques allow us to simultaneously record, with sufficient temporal resolution, only a small fraction of the network. Consequently, naive connectivity estimators that neglect these common input effects are highly biased. This work proposes a “shotgun” experimental design, in which we observe multiple sub-networks briefly, in a serial manner. Thus, while the full network cannot be observed simultaneously at any given time, we may be able to observe much larger subsets of the network over the course of the entire experiment, thus ameliorating the common input problem. Using a generalized linear model for a spiking recurrent neural network, we develop a scalable approximate expected loglikelihood-based Bayesian method to perform network inference given this type of data, in which only a small fraction of the network is observed in each time bin. We demonstrate in simulation that the shotgun experimental design can eliminate the biases induced by common input effects. Networks with thousands of neurons, in which only a small fraction of the neurons is observed in each time bin, can be quickly and accurately estimated, achieving orders of magnitude speed up over previous approaches.

Optical imaging of the activity in a neuronal network is limited by the scanning speed of the imaging device. Therefore, typically, only a small fixed part of the network is observed during the entire experiment. However, in such an experiment, it can be hard to infer from the observed activity patterns whether (1) a neuron A directly affects neuron B, or (2) another, unobserved neuron C affects both A and B. To deal with this issue, we propose a “shotgun” observation scheme, in which, at each time point, we observe a small changing subset of the neurons from the network. Consequently, many fewer neurons remain completely unobserved during the entire experiment, enabling us to eventually distinguish between cases (1) and (2) given sufficiently long experiments. Since previous inference algorithms cannot efficiently handle so many missing observations, we develop a scalable algorithm for data acquired using the shotgun observation scheme, in which only a small fraction of the neurons are observed in each time bin. Using this kind of simulated data, we show the algorithm is able to quickly infer connectivity in spiking recurrent networks with thousands of neurons.

Monitoring activity in neural circuits with genetically encoded indicators

Recent developments in genetically encoded indicators of neural activity (GINAs) have greatly advanced the field of systems neuroscience. As they are encoded by DNA, GINAs can be targeted to genetically defined cellular populations. Combined with fluorescence microscopy, most notably multi-photon imaging, GINAs allow chronic simultaneous optical recordings from large populations of neurons or glial cells in awake, behaving mammals, particularly rodents. This large-scale recording of neural activity at multiple temporal and spatial scales has greatly advanced our understanding of the dynamics of neural circuitry underlying behavior—a critical first step toward understanding the complexities of brain function, such as sensorimotor integration and learning. Here, we summarize the recent development and applications of the major classes of GINAs. In particular, we take an in-depth look at the design of available GINA families with a particular focus on genetically encoded calcium indicators (GCaMPs), sensors probing synaptic activity, and genetically encoded voltage indicators. Using the family of the GCaMP as an example, we review established sensor optimization pipelines. We also discuss practical considerations for end users of GINAs about experimental methods including approaches for gene delivery, imaging system requirements, and data analysis techniques. With the growing toolbox of GINAs and with new microscopy techniques pushing beyond their current limits, the age of light can finally achieve the goal of broad and dense sampling of neuronal activity across time and brain structures to obtain a dynamic picture of brain function.

Putting a finishing touch on GECIs

More than a decade ago genetically encoded calcium indicators (GECIs) entered the stage as new promising tools to image calcium dynamics and neuronal activity in living tissues and designated cell types in vivo. From a variety of initial designs two have emerged as promising prototypes for further optimization: FRET (Förster Resonance Energy Transfer)-based sensors and single fluorophore sensors of the GCaMP family. Recent efforts in structural analysis, engineering and screening have broken important performance thresholds in the latest generation for both classes. While these improvements have made GECIs a powerful means to perform physiology in living animals, a number of other aspects of sensor function deserve attention. These aspects include indicator linearity, toxicity and slow response kinetics. Furthermore creating high performance sensors with optically more favorable emission in red or infrared wavelengths as well as new stably or conditionally GECI-expressing animal lines are on the wish list. When the remaining issues are solved, imaging of GECIs will finally have crossed the last milestone, evolving from an initial promise into a fully matured technology.

Genetically encoded optical indicators for the analysis of neuronal circuits

In a departure from previous top-down or bottom-up strategies used to understand neuronal circuits, many forward-looking research programs now place the circuit itself at their centre. This has led to an emphasis on the dissection and elucidation of neuronal circuit elements and mechanisms, and on studies that ask how these circuits generate behavioural outputs. This movement towards circuit-centric strategies is progressing rapidly as a result of technological advances that combine genetic manipulation with light-based methods. The core tools of these new approaches are genetically encoded optical indicators and actuators that enable non-destructive interrogation and manipulation of neuronal circuits in behaving animals with cellular-level precision. This Review examines genetically encoded reporters of neuronal function and assesses their value for circuit-oriented neuroscientific investigations.