In Vivo Calcium Imaging of Neural Network Function

TWINKLE: An open-source two-photon microscope for teaching and research

Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting as well as grasping the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high-performance and cost-effective research and teaching microscope without any custom parts beyond what can be fabricated in a university machine shop. The instrument features a large field of view, using a modern objective with a long working distance and large back aperture to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open-source scientific instrumentation.

Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed

Systems neuroscience has experienced an explosion of new tools for reading and writing neural activity, enabling exciting new experiments such as all-optical or closed-loop control that effect powerful causal interventions. At the same time, improved computational models are capable of reproducing behavior and neural activity with increasing fidelity. Unfortunately, these advances have drastically increased the complexity of integrating different lines of research, resulting in the missed opportunities and untapped potential of suboptimal experiments. Experiment simulation can help bridge this gap, allowing model and experiment to better inform each other by providing a low-cost testbed for experiment design, model validation, and methods engineering. Specifically, this can be achieved by incorporating the simulation of the experimental interface into our models, but no existing tool integrates optogenetics, two-photon calcium imaging, electrode recording, and flexible closed-loop processing with neural population simulations. To address this need, we have developed Cleo: the Closed-Loop, Electrophysiology, and Optophysiology experiment simulation testbed. Cleo is a Python package enabling injection of recording and stimulation devices as well as closed-loop control with realistic latency into a Brian spiking neural network model. It is the only publicly available tool currently supporting two-photon and multi-opsin/wavelength optogenetics. To facilitate adoption and extension by the community, Cleo is open-source, modular, tested, and documented, and can export results to various data formats. Here we describe the design and features of Cleo, validate output of individual components and integrated experiments, and demonstrate its utility for advancing optogenetic techniques in prospective experiments using previously published systems neuroscience models.

A Visual Interface for Exploring Hypotheses About Neural Circuits

One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned tasks by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons. Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits. The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa.

A machine-learning tool to identify bistable states from calcium imaging data

Mapping neuronal activation using calcium imaging in vivo during behavioural tasks has advanced our understanding of nervous system function. In almost all of these studies, calcium imaging is used to infer spike probabilities because action potentials activate voltage-gated calcium channels and increase intracellular calcium levels. However, neurons not only fire action potentials, but also convey information via intrinsic dynamics such as by generating bistable membrane potential states. Although a number of tools for spike inference have been developed and are currently being used, no tool exists for converting calcium imaging signals to maps of cellular state in bistable neurons. Purkinje neurons in the larval zebrafish cerebellum exhibit membrane potential bistability, firing either tonically or in bursts. Several studies have implicated the role of a population code in cerebellar function, with bistability adding an extra layer of complexity to this code. In the present study, we develop a tool, CaMLSort, which uses convolutional recurrent neural networks to classify calcium imaging traces as arising from either tonic or bursting cells. We validate this classifier using a number of different methods and find that it performs well on simulated event rasters as well as real biological data that it had not previously seen. Moreover, we find that CaMLsort generalizes to other bistable neurons, such as dopaminergic neurons in the ventral tegmental area of mice. Thus, this tool offers a new way of analysing calcium imaging data from bistable neurons to understand how they participate in network computation and natural behaviours. KEY POINTS: Calcium imaging, compriising the gold standard of inferring neuronal activity, does not report cellular state in neurons that are bistable, such as Purkinje neurons in the cerebellum of larval zebrafish. We model the relationship between Purkinje neuron electrical activity and its corresponding calcium signal to compile a dataset of state-labelled simulated calcium signals. We apply machine-learning methods to this dataset to develop a tool that can classify the state of a Purkinje neuron using only its calcium signal, which works well on real data even though it was trained only on simulated data. CaMLsort (Calcium imaging and Machine Learning based tool to sort intracellular state) also generalizes well to bistable neurons in a different brain region (ventral tegmental area) in a different model organism (mouse). This tool can facilitate our understanding of how these neurons carry out their functions in a circuit.

Genetic context drives age-related disparities in synaptic maintenance and structure across cortical and hippocampal neuronal circuits

The disconnection of neuronal circuitry through synaptic loss is presumed to be a major driver of age-related cognitive decline. Age-related cognitive decline is heterogeneous, yet whether genetic mechanisms differentiate successful from unsuccessful cognitive decline through maintenance or vulnerability of synaptic connections remains unknown. Previous work using rodent and primate models leveraged various techniques to imply that age-related synaptic loss is widespread on pyramidal cells in prefrontal cortex (PFC) circuits but absent on those in area CA1 of the hippocampus. Here, we examined the effect of aging on synapses on projection neurons forming a hippocampal-cortico-thalamic circuit important for spatial working memory tasks from two genetically distinct mouse strains that exhibit susceptibility (C57BL/6J) or resistance (PWK/PhJ) to cognitive decline during aging. Across both strains, synapse density on CA1-to-PFC projection neurons appeared completely intact with age. In contrast, we found synapse loss on PFC-to-nucleus reuniens (RE) projection neurons from aged C57BL/6J but not PWK/PhJ mice. Moreover, synapses from aged PWK/PhJ mice but not from C57BL/6J exhibited altered morphologies that suggest increased efficiency to drive depolarization in the parent dendrite. Our findings suggest resistance to age-related cognitive decline results in part by age-related synaptic adaptations, and identification of these mechanisms in PWK/PhJ mice could uncover new therapeutic targets for promoting successful cognitive aging and extending human health span.

Standardised Measurements for Monitoring and Comparing Multiphoton Microscope Systems

The goal of this protocol is to enable better characterisation of multiphoton microscopy hardware across a large user base. The scope of this protocol is purposefully limited to focus on hardware, touching on software and data analysis routines only where relevant. The intended audiences are scientists using and building multiphoton microscopes in their laboratories. The goal is that any scientist, not only those with optical expertise, can test whether their multiphoton microscope is performing well and producing consistent data over the lifetime of their system.

Evaluation of compact pulsed lasers for two-photon microscopy using a simple method for measuring two-photon excitation efficiency

Significance

Two-photon (2p) microscopy has historically relied on titanium sapphire pulsed lasers that are expensive and have a large footprint. Recently, several manufacturers have developed less expensive compact pulsed lasers optimized for 2p excitation of green fluorophores. However, quantitative evaluation of their quality is lacking.

Aim

We describe a simple approach to systematically evaluate 2p excitation efficiency, an empiric measure of the quality of a pulsed laser and its ability to elicit 2p induced fluorescence.

Approach

By measuring pulse width, repetition rate, and fluorescence output, we calculated a measure of 2p excitation efficiency η , which we compared for four commercially available compact pulsed lasers in the 920 to 930 nm wavelength range.

Results

2p excitation efficiency varied substantially among tested lasers. The Coherent Axon exhibited the best 2p excitation efficiency (1.09 ± 0.03 ), exceeding that of a titanium sapphire reference laser (defined to have efficiency = 1). However, its measured fluorescence was modest due to its long pulse width. Of the compact lasers, the Toptica Femtofiber Ultra exhibited the best combination of measured fluorescence (0.75 ± 0.01 ) and 2p excitation efficiency (0.86 ± 0.01 ).

Conclusions

We describe a simple method that both laser developers and end users can use to benchmark the 2p excitation efficiency of lasers used for 2p microscopy.

Genetic context drives age-related disparities in synaptic maintenance and structure across cortical and hippocampal neuronal circuits

The disconnection of neuronal circuits through synaptic loss is presumed to be a major driver of age-related cognitive decline. Age-related cognitive decline is heterogeneous, yet whether genetic mechanisms differentiate successful from unsuccessful cognitive decline through synaptic structural mechanisms remains unknown. Previous work using rodent and primate models leveraged various techniques to suggest that age-related synaptic loss is widespread on pyramidal cells in prefrontal cortex (PFC) circuits but absent on those in area CA1 of the hippocampus. Here, we examined the effect of aging on synapses on projection neurons forming a hippocampal-cortico-thalamic circuit important for spatial working memory tasks from two genetically distinct mouse strains that exhibit susceptibility (C57BL/6J) or resistance (PWK/PhJ) to cognitive decline during aging. Across both strains, synapses on the CA1-to-PFC projection neurons appeared completely intact with age. In contrast, we found synapse loss on PFC-to-nucleus reuniens (RE) projection neurons from aged C57BL/6J but not PWK/PhJ mice. Moreover, synapses from aged PWK/PhJ mice but not from C57BL/6J exhibited morphological changes that suggest increased synaptic efficiency to depolarize the parent dendrite. Our findings suggest resistance to age-related cognitive decline results in part by age-related synaptic adaptations, and identification of these mechanisms in PWK/PhJ mice could uncover new therapeutic targets for promoting successful cognitive aging and extending human health span.

Emerging approaches for decoding neuropeptide transmission

Neuropeptides produce robust effects on behavior across species, and recent research has benefited from advances in high-resolution techniques to investigate peptidergic transmission and expression throughout the brain in model systems. Neuropeptides exhibit distinct characteristics which includes their post-translational processing, release from dense core vesicles, and ability to activate G-protein-coupled receptors (GPCRs). These complex properties have driven the need for development of specialized tools that can sense neuropeptide expression, cell activity, and release. Current research has focused on isolating when and how neuropeptide transmission occurs, as well as the conditions in which neuropeptides directly mediate physiological and adaptive behavioral states. Here we describe the current technological landscape in which the field is operating to decode key questions regarding these dynamic neuromodulators.

Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.

Dynamic Fluorescence Imaging in Experimental Epilepsy

The ability to develop effective new treatments for epilepsy may depend on improved understanding of seizure pathophysiology, about which many questions remain. Dynamic fluorescence imaging of activity at single-neuron resolution with fluorescent indicators in experimental model systems in vivo has revolutionized basic neuroscience and has the potential to do so for epilepsy research as well. Here, we review salient issues as they pertain to experimental imaging in basic epilepsy research, including commonly used imaging technologies, data processing and analysis, interpretation of results, and selected examples of how imaging-based approaches have revealed new insight into mechanisms of seizures and epilepsy.

Deep tissue multi-photon imaging using adaptive optics with direct focus sensing and shaping

High-resolution optical imaging deep in tissues is challenging because of optical aberrations and scattering of light caused by the complex structure of living matter. Here we present an adaptive optics three-photon microscope based on analog lock-in phase detection for focus sensing and shaping (ALPHA-FSS). ALPHA-FSS accurately measures and effectively compensates for both aberrations and scattering induced by specimens and recovers subcellular resolution at depth. A conjugate adaptive optics configuration with remote focusing enables in vivo imaging of fine neuronal structures in the mouse cortex through the intact skull up to a depth of 750 µm below the pia, enabling near-non-invasive high-resolution microscopy in cortex. Functional calcium imaging with high sensitivity and high-precision laser-mediated microsurgery through the intact skull were also demonstrated. Moreover, we achieved in vivo high-resolution imaging of the deep cortex and subcortical hippocampus up to 1.1 mm below the pia within the intact brain.

Two-photon calcium imaging of neuronal activity

In vivo two-photon calcium imaging (2PCI) is a technique used for recording neuronal activity in the intact brain. It is based on the principle that, when neurons fire action potentials, intracellular calcium levels rise, which can be detected using fluorescent molecules that bind to calcium. This Primer is designed for scientists who are considering embarking on experiments with 2PCI. We provide the reader with a background on the basic concepts behind calcium imaging and on the reasons why 2PCI is an increasingly powerful and versatile technique in neuroscience. The Primer explains the different steps involved in experiments with 2PCI, provides examples of what ideal preparations should look like and explains how data are analysed. We also discuss some of the current limitations of the technique, and the types of solutions to circumvent them. Finally, we conclude by anticipating what the future of 2PCI might look like, emphasizing some of the analysis pipelines that are being developed and international efforts for data sharing.

ICoRD: Iterative correlation-based ROI detection method for the extraction of neural signals in calcium imaging

OBJECTIVE

In vivo calcium imaging is a standard neuroimaging technique that allows selective observation of target neuronal activities. In calcium imaging, neuron activation signals provide key information for the investigation of neural circuits. For efficient extraction of the calcium signals of neurons, selective detection of the region of interest (ROI) pixels corresponding to the active subcellular region of the target neuron is essential. However, current ROI detection methods for calcium imaging data exhibit a relatively low signal extraction performance from neurons with a low signal-to-noise power ratio (SNR). This is problematic because a low SNR is unavoidable in many biological experiments.

APPROACH

Therefore, we propose an iterative correlation-based ROI detection (ICoRD) method that robustly extracts the calcium signal of the target neuron from a calcium imaging series with severe noise.

MAIN RESULTS

ICoRD extracts calcium signals closer to the ground-truth calcium signal than the conventional method from simulated calcium imaging data in all low SNR ranges. Additionally, this study confirmed that ICoRD robustly extracts activation signals against noise, even within in vivo environments.

SIGNIFICANCE

ICoRD showed reliable detection from neurons with a low SNR and sparse activation, which were not detected by conventional methods. ICoRD will facilitate our understanding of neural circuit activity by providing significantly improved ROI detection in noisy images.

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.

Archetypal Analysis for neuronal clique detection in low-rate calcium fluorescence imaging

Archetypal analysis (AA) is a versatile data analysis method to cluster distinct features within a data set. Here, we demonstrate a framework showing the power of AA to spatio-temporally resolve events in calcium imaging, an imaging modality commonly used in neurobiology and neuroscience to capture neuronal communication patterns. After validation of our AA-based approach on synthetic data sets, we were able to characterize neuronal communication patterns in recorded calcium waves. Clinical relevance- Transient calcium events play an essential role in brain cell communication, growth, and network formation, as well as in neurodegeneration. To reliably interpret calcium events from personalized medicine data, where patterns may differ from patient to patient, appropriate image processing and signal analysis methods need to be developed for optimal network characterization.

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

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

Development of an Ergonomic User Interface Design of Calcium Imaging Processing System

An optical brain-machine interface (O-BMI) system using calcium imaging has various advantages such as high resolution, a comprehensive view of large neural populations, abilities such as long-term stable recording, and applicability to freely behaving animals in neuroscience research. The present study developed an ergonomic user interface (UI) design, based on a use scenario for an O-BMI system that can be used for the acquisition and processing of calcium imaging in freely behaving rodents. The UI design was developed in three steps: (1) identification of design and function requirements of users, (2) establishment of a use scenario, and (3) development of a UI prototype. The UI design requirements were identified by a literature review, a benchmark of existing systems, and a focus group interview with five neuroscience researchers. Then, the use scenario was developed for tasks of data acquisition, feature extraction, and neural decoding for offline and online processing by considering the sequences of operations and needs of users. Lastly, a digital prototype incorporating an information architecture, graphic user interfaces, and simulated functions was fabricated. A usability test was conducted with five neuroscientists (work experience = 3.4 ± 1.1 years) and five ergonomic experts (work experience = 3.6 ± 2.7 years) to compare the digital prototypes with four existing systems (Miniscope, nVista, Mosaic, and Suite2p). The usability testing results showed that the ergonomic UI design was significantly preferred to the UI designs of the existing systems by reducing the task completion time by 10.1% to 70.2% on average, the scan path length by 14.4% to 88.7%, and perceived workload by 12.2% to 37.9%, increasing satisfaction by 11.3% to 74.3% in data acquisition and signal-extraction tasks. The present study demonstrates the significance of the user-centered design approach in the development of a system for neuroscience research. Further research is needed to validate the usability test results of the UI prototype as a corresponding real system is implemented.

The role of endogenous opioid neuropeptides in neurostimulation-driven analgesia

Due to the prevalence of chronic pain worldwide, there is an urgent need to improve pain management strategies. While opioid drugs have long been used to treat chronic pain, their use is severely limited by adverse effects and abuse liability. Neurostimulation techniques have emerged as a promising option for chronic pain that is refractory to other treatments. While different neurostimulation strategies have been applied to many neural structures implicated in pain processing, there is variability in efficacy between patients, underscoring the need to optimize neurostimulation techniques for use in pain management. This optimization requires a deeper understanding of the mechanisms underlying neurostimulation-induced pain relief. Here, we discuss the most commonly used neurostimulation techniques for treating chronic pain. We present evidence that neurostimulation-induced analgesia is in part driven by the release of endogenous opioids and that this endogenous opioid release is a common endpoint between different methods of neurostimulation. Finally, we introduce technological and clinical innovations that are being explored to optimize neurostimulation techniques for the treatment of pain, including multidisciplinary efforts between neuroscience research and clinical treatment that may refine the efficacy of neurostimulation based on its underlying mechanisms.

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.

Inferring Excitatory and Inhibitory Connections in Neuronal Networks

The comprehension of neuronal network functioning, from most basic mechanisms of signal transmission to complex patterns of memory and decision making, is at the basis of the modern research in experimental and computational neurophysiology. While mechanistic knowledge of neurons and synapses structure increased, the study of functional and effective networks is more complex, involving emergent phenomena, nonlinear responses, collective waves, correlation and causal interactions. Refined data analysis may help in inferring functional/effective interactions and connectivity from neuronal activity. The Transfer Entropy (TE) technique is, among other things, well suited to predict structural interactions between neurons, and to infer both effective and structural connectivity in small- and large-scale networks. To efficiently disentangle the excitatory and inhibitory neural activities, in the article we present a revised version of TE, split in two contributions and characterized by a suited delay time. The method is tested on in silico small neuronal networks, built to simulate the calcium activity as measured via calcium imaging in two-dimensional neuronal cultures. The inhibitory connections are well characterized, still preserving a high accuracy for excitatory connections prediction. The method could be applied to study effective and structural interactions in systems of excitable cells, both in physiological and in pathological conditions.

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

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

Optical Electrophysiology: Toward the Goal of Label-Free Voltage Imaging

Measuring and monitoring the electrical signals transmitted between neurons is key to understanding the communication between neurons that underlies human perception, information processing, and decision-making. While electrode-based electrophysiology has been the gold standard, optical electrophysiology has opened up a new area in the past decade. Voltage-dependent fluorescent reporters enable voltage imaging with high spatial resolution and flexibility to choose recording locations. However, they exhibit photobleaching as well as phototoxicity and may perturb the physiology of the cell. Label-free optical electrophysiology seeks to overcome these hurdles by detecting electrical activities optically, without the incorporation of exogenous fluorophores in cells. For example, electrochromic optical recording detects neuroelectrical signals via a voltage-dependent color change of extracellular materials, and interferometric optical recording monitors membrane deformations that accompany electrical activities. Label-free optical electrophysiology, however, is in an early stage, and often has limited sensitivity and temporal resolution. In this Perspective, we review the recent progress to overcome these hurdles. We hope this Perspective will inspire developments of label-free optical electrophysiology techniques with high recording sensitivity and temporal resolution in the near future.

Dynamic real-time subtraction of stray-light and background for multiphoton imaging

We introduce a new approach to reduce uncorrelated background signals from fluorescence imaging data, using real-time subtraction of background light. This approach takes advantage of the short fluorescence lifetime of most popular fluorescent activity reporters, and the low duty-cycle of ultrafast lasers. By synchronizing excitation and recording, laser-induced multiphoton fluorescence can be discriminated from background light levels with each laser pulse. We demonstrate the ability of our method to - in real-time - remove image artifacts that in a conventional imaging setup lead to clipping of the signal. In other words, our method enables imaging under conditions that in a conventional setup would yield corrupted data from which no accurate information can be extracted. This is advantageous in experimental setups requiring additional light sources for applications such as optogenetic stimulation.

Modeling time-varying brain networks with a self-tuning optimized Kalman filter

Brain networks are complex dynamical systems in which directed interactions between different areas evolve at the sub-second scale of sensory, cognitive and motor processes. Due to the highly non-stationary nature of neural signals and their unknown noise components, however, modeling dynamic brain networks has remained one of the major challenges in contemporary neuroscience. Here, we present a new algorithm based on an innovative formulation of the Kalman filter that is optimized for tracking rapidly evolving patterns of directed functional connectivity under unknown noise conditions. The Self-Tuning Optimized Kalman filter (STOK) is a novel adaptive filter that embeds a self-tuning memory decay and a recursive regularization to guarantee high network tracking accuracy, temporal precision and robustness to noise. To validate the proposed algorithm, we performed an extensive comparison against the classical Kalman filter, in both realistic surrogate networks and real electroencephalography (EEG) data. In both simulations and real data, we show that the STOK filter estimates time-frequency patterns of directed connectivity with significantly superior performance. The advantages of the STOK filter were even clearer in real EEG data, where the algorithm recovered latent structures of dynamic connectivity from epicranial EEG recordings in rats and human visual evoked potentials, in excellent agreement with known physiology. These results establish the STOK filter as a powerful tool for modeling dynamic network structures in biological systems, with the potential to yield new insights into the rapid evolution of network states from which brain functions emerge.

During normal behavior, brains transition between functional network states several times per second. This allows humans to quickly read a sentence, and a frog to catch a fly. Understanding these fast network dynamics is fundamental to understanding how brains work, but up to now it has proven very difficult to model fast brain dynamics for various methodological reasons. To overcome these difficulties, we designed a new Kalman filter (STOK) by innovating on previous solutions from control theory and state-space modelling. We show that STOK accurately models fast network changes in simulations and real neural data, making it an essential new tool for modelling fast brain networks in the time and frequency domain.

Adapting techniques for calcium imaging in muscles of adult Brugia malayi

Brugia malayi is a human filarial nematode parasite that causes lymphatic filariasis or 'elephantiasis' a disfiguring neglected tropical disease. This parasite is a more tractable nematode parasite for the experimental study of anthelmintic drugs and has been studied with patch-clamp and RNAi techniques. Unlike in C. elegans however, calcium signaling in B. malayi or other nematode parasites has not been achieved, limiting the studies of the mode of action of anthelmintic drugs. We describe here the development of calcium imaging methods that allow us to characterize changes in cellular calcium in the muscles of B. malayi. This is a powerful technique that can help in elucidating the mode of action of selected anthelmintics. We developed two approaches that allow the recording of calcium signals in the muscles of adult B. malayi: (a) soaking the muscles with Fluo-3AM, promoting large-scale imaging of multiple cells simultaneously and, (b) direct insertion of Fluo-3 using microinjection, providing the possibility of performing dual calcium and electrophysiological recordings. Here, we describe the techniques used to optimize dye entry into the muscle cells and demonstrate that detectable increases in Fluo-3 fluorescence to elevated calcium concentrations can be achieved in B. malayi using both techniques.

Functional Architecture of Motion Direction in the Mouse Superior Colliculus

Motion vision is important in guiding animal behavior. Both the retina and the visual cortex process object motion in largely unbiased fashion: all directions are represented at all locations in the visual field. We investigate motion processing in the superior colliculus of the awake mouse by optically recording neural responses across both hemispheres. Within the retinotopic map, one finds large regions of ∼500 μm size where neurons prefer the same direction of motion. This preference is maintained in depth to ∼350 μm. The scale of these patches, ∼30 degrees of visual angle, is much coarser than the animal's visual resolution (∼2 degrees). A global map of motion direction shows approximate symmetry between the left and right hemispheres and a net bias for upward-nasal motion in the upper visual field.

Biolistic transfection and expression analysis of acute cortical slices

BACKGROUND

Biolistic gene gun transfection has been used to transfect organotypic cultures (OTCs) or dissociated cultures in vitro. Here, we modified this technique to allow successful transfection of acute brain slices, followed by measurement of neuronal activity within a few hours.

NEW METHOD

We established biolistic transfection of murine acute cortical slices to measure calcium signals. Acute slices are mounted on plasma/thrombin coagulate and transfected with a calcium sensor. Imaging can be performed within 4 h post transfection without affecting cell viability.

RESULTS

Four hours after GCaMP6s transfection, acute slices display remarkable fluorescent protein expression level allowing to study spontaneous activity and receptor pharmacology. While optimal gas pressure (150 psi) and gold particle size used (1 μm) confirm previously published protocols, the amount of 5 μg DNA was found to be optimal for particle coating.

COMPARISON WITH EXISTING METHODS

The major advantage of this technique is the rapid disposition of acute slices for calcium imaging. No transgenic GECI expressing animals or OTC for long periods are required. In acute slices, network interaction and connectivity are preserved. The method allows to obtain physiological readouts within 4 h, before functional tissue modifications might come into effect. Limitations of this technique are random transfection, low expression efficiency when using specific promotors, and preclusion or genetic manipulations that require a prolonged time before physiological changes become measurable, such as expression of recombinant proteins that require transport to distant subcellular localizations.

CONCLUSION

The method is optimal for short-time investigation of calcium signals in acute slices.

In Vivo Two-photon Calcium Imaging in Dendrites of Rabies Virus-labeled V1 Corticothalamic Neurons

Monitoring neuronal activity in vivo is critical to understanding the physiological or pathological functions of the brain. Two-photon Ca²⁺ imaging in vivo using a cranial window and specific neuronal labeling enables real-time, in situ, and long-term imaging of the living brain. Here, we constructed a recombinant rabies virus containing the Ca²⁺ indicator GCaMP6s along with the fluorescent protein DsRed2 as a baseline reference to ensure GCaMP6s signal reliability. This functional tracer was applied to retrogradely label specific V1-thalamus circuits and detect spontaneous Ca²⁺ activity in the dendrites of V1 corticothalamic neurons by in vivo two-photon Ca²⁺ imaging. Notably, we were able to record single-spine spontaneous Ca²⁺ activity in specific circuits. Distinct spontaneous Ca²⁺ dynamics in dendrites of V1 corticothalamic neurons were found for different V1-thalamus circuits. Our method can be applied to monitor Ca²⁺ dynamics in specific input circuits in vivo, and contribute to functional studies of defined neural circuits and the dissection of functional circuit connections.

Multimodal Functional Neuroimaging by Simultaneous BOLD fMRI and Fiber-Optic Calcium Recordings and Optogenetic Control

Recent developments of optogenetic tools and fluorescence-based calcium recording techniques enable the manipulation and monitoring of neural circuits on a cellular level. Non-invasive imaging of brain networks, however, requires the application of methods such as blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI), which is commonly used for functional neuroimaging. While BOLD fMRI provides brain-wide non-invasive reading of the hemodynamic response, it is only an indirect measure of neural activity. Direct observation of neural responses requires electrophysiological or optical methods. The latter can be combined with optogenetic control of neuronal circuits and are MRI compatible. Yet, simultaneous optical recordings are still limited to fiber-optic-based approaches. Here, we review the integration of optical recordings and optogenetic manipulation into fMRI experiments. As a practical example, we describe how BOLD fMRI in a 9.4-T small animal MR scanner can be combined with in vivo fiber-optic calcium recordings and optogenetic control in a multimodal setup. We present simultaneous BOLD fMRI and calcium recordings under optogenetic control in rat. We outline details about MR coil configuration, choice, and usage of opsins and chemically and genetically encoded calcium sensors, fiber implantation, appropriate light power for stimulation, and calcium signal detection, to provide a glimpse into challenges and opportunities of this multimodal molecular neuroimaging approach.

Characterization of Dmrt3-Derived Neurons Suggest a Role within Locomotor Circuits

Neuronal networks within the spinal cord, collectively known as the central pattern generator (CPG), coordinate rhythmic movements underlying locomotion. The transcription factor doublesex and mab-3-related transcription factor 3 (DMRT3) is involved in the differentiation of the dorsal interneuron 6 class of spinal cord interneurons. In horses, a non-sense mutation in the Dmrt3 gene has major effects on gaiting ability, whereas mice lacking the Dmrt3 gene display impaired locomotor activity. Although the Dmrt3 gene is necessary for normal spinal network formation and function in mice, a direct role for Dmrt3-derived neurons in locomotor-related activities has not been demonstrated. Here we present the characteristics of the Dmrt3-derived spinal cord interneurons. Using transgenic mice of both sexes, we characterized interneurons labeled by their expression of Cre driven by the endogenous Dmrt3 promoter. We used molecular, retrograde tracing and electrophysiological techniques to examine the anatomical, morphological, and electrical properties of the Dmrt3-Cre neurons. We demonstrate that inhibitory Dmrt3-Cre neurons receive extensive synaptic inputs, innervate surrounding CPG neurons, intrinsically regulate CPG neuron's electrical activity, and are rhythmically active during fictive locomotion, bursting at frequencies independent to the ventral root output. The present study provides novel insights on the character of spinal Dmrt3-derived neurons, data demonstrating that these neurons participate in locomotor coordination.SIGNIFICANCE STATEMENT In this work, we provide evidence for a role of the Dmrt3 interneurons in spinal cord locomotor circuits as well as molecular and functional insights on the cellular and microcircuit level of the Dmrt3-expressing neurons in the spinal cord. Dmrt3 neurons provide the first example of an interneuron population displaying different oscillation frequencies. This study presents novel findings on an under-reported population of spinal cord neurons, which will aid in deciphering the locomotor network and will facilitate the design and development of therapeutics for spinal cord injury and motor disorders.

Calcium imaging of CPG-evoked activity in efferent neurons of the stick insect

The stick insect is a well-established experimental animal to study the neural basis of walking. Here, we introduce a preparation that allows combining calcium imaging in efferent neurons with electrophysiological recordings of motor neuron activity in the stick insect thoracic nerve cord. The intracellular free calcium concentration in middle leg retractor coxae motor neurons and modulatory octopaminergic DUM neurons was monitored after backfilling lateral nerve nl5 that contains the axons of these neurons with the calcium indicator Oregon Green BAPTA-1. Rhythmic spike activity in retractor and protractor motor neurons was evoked by pharmacological activation of central pattern generating neuronal networks and recorded extracellularly from lateral nerves. A primary goal of this study was to investigate whether changes in the intracellular free calcium concentration observed in motor neurons during oscillatory activity depend on action potentials. We show that rhythmic spike activity in leg motor neurons induced either pharmacologically or by tactile stimulation of the animal is accompanied by a synchronous modulation in the intracellular free calcium concentration. Calcium oscillations in motor neurons do not appear to depend on calcium influx through voltage-sensitive calcium channels that are gated by action potentials because Calcium oscillations persist after pharmacologically blocking action potentials in the motor neurons. Calcium oscillations were also apparent in the modulatory DUM neurons innervating the same leg muscle. However, the timing of calcium oscillations varied not only between DUM neurons and motor neurons, but also among different DUM neurons. Therefore, we conclude that the motor neurons and the different DUM neurons receive independent central drive.

Combining biophysical modeling and deep learning for multielectrode array neuron localization and classification

Neural circuits typically consist of many different types of neurons, and one faces a challenge in disentangling their individual contributions in measured neural activity. Classification of cells into inhibitory and excitatory neurons and localization of neurons on the basis of extracellular recordings are frequently employed procedures. Current approaches, however, need a lot of human intervention, which makes them slow, biased, and unreliable. In light of recent advances in deep learning techniques and exploiting the availability of neuron models with quasi-realistic three-dimensional morphology and physiological properties, we present a framework for automatized and objective classification and localization of cells based on the spatiotemporal profiles of the extracellular action potentials recorded by multielectrode arrays. We train convolutional neural networks on simulated signals from a large set of cell models and show that our framework can predict the position of neurons with high accuracy, more precisely than current state-of-the-art methods. Our method is also able to classify whether a neuron is excitatory or inhibitory with very high accuracy, substantially improving on commonly used clustering techniques. Furthermore, our new method seems to have the potential to separate certain subtypes of excitatory and inhibitory neurons. The possibility of automatically localizing and classifying all neurons recorded with large high-density extracellular electrodes contributes to a more accurate and more reliable mapping of neural circuits. NEW & NOTEWORTHY We propose a novel approach to localize and classify neurons from their extracellularly recorded action potentials with a combination of biophysically detailed neuron models and deep learning techniques. Applied to simulated data, this new combination of forward modeling and machine learning yields higher performance compared with state-of-the-art localization and classification methods.

An open source tool for automatic spatiotemporal assessment of calcium transients and local 'signal-close-to-noise' activity in calcium imaging data

Local and spontaneous calcium signals play important roles in neurons and neuronal networks. Spontaneous or cell-autonomous calcium signals may be difficult to assess because they appear in an unpredictable spatiotemporal pattern and in very small neuronal loci of axons or dendrites. We developed an open source bioinformatics tool for an unbiased assessment of calcium signals in x,y-t imaging series. The tool bases its algorithm on a continuous wavelet transform-guided peak detection to identify calcium signal candidates. The highly sensitive calcium event definition is based on identification of peaks in 1D data through analysis of a 2D wavelet transform surface. For spatial analysis, the tool uses a grid to separate the x,y-image field in independently analyzed grid windows. A document containing a graphical summary of the data is automatically created and displays the loci of activity for a wide range of signal intensities. Furthermore, the number of activity events is summed up to create an estimated total activity value, which can be used to compare different experimental situations, such as calcium activity before or after an experimental treatment. All traces and data of active loci become documented. The tool can also compute the signal variance in a sliding window to visualize activity-dependent signal fluctuations. We applied the calcium signal detector to monitor activity states of cultured mouse neurons. Our data show that both the total activity value and the variance area created by a sliding window can distinguish experimental manipulations of neuronal activity states. Notably, the tool is powerful enough to compute local calcium events and ‘signal-close-to-noise’ activity in small loci of distal neurites of neurons, which remain during pharmacological blockade of neuronal activity with inhibitors such as tetrodotoxin, to block action potential firing, or inhibitors of ionotropic glutamate receptors. The tool can also offer information about local homeostatic calcium activity events in neurites.

Calcium imaging has become a standard tool to investigate local, spontaneous, or cell-autonomous calcium signals in neurons. Some of these calcium signals are fast and ‘small’, thus making it difficult to identify real signaling events due to an unavoidable signal noise. Therefore, it is difficult to assess the spatiotemporal activity footprint of individual neurons or a neuronal network. We developed this open source tool to automatically extract, count, and localize calcium signals from the whole x,y-t image series. As demonstrated here, the tool is useful for an unbiased comparison of activity states of neurons, helps to assess local calcium transients, and even visualizes local homeostatic calcium activity. The tool is powerful enough to visualize signal-close-to-noise calcium activity.

Adaptive optical microscopy for neurobiology

With the ability to correct for the aberrations introduced by biological specimens, adaptive optics-a method originally developed for astronomical telescopes-has been applied to optical microscopy to recover diffraction-limited imaging performance deep within living tissue. In particular, this technology has been used to improve image quality and provide a more accurate characterization of both structure and function of neurons in a variety of living organisms. Among its many highlights, adaptive optical microscopy has made it possible to image large volumes with diffraction-limited resolution in zebrafish larval brains, to resolve dendritic spines over 600μm deep in the mouse brain, and to more accurately characterize the orientation tuning properties of thalamic boutons in the primary visual cortex of awake mice.

New Neuroscience Tools That Are Identifying the Sleep-Wake Circuit

The complexity of the brain is yielding to technology. In the area of sleep neurobiology, conventional neuroscience tools such as lesions, cell recordings, c-Fos, and axon-tracing methodologies have been instrumental in identifying the complex and intermingled populations of sleep- and arousal-promoting neurons that orchestrate and generate wakefulness, NREM, and REM sleep. In the last decade, new technologies such as optogenetics, chemogenetics, and the CRISPR-Cas system have begun to transform how biologists understand the finer details associated with sleep-wake regulation. These additions to the neuroscience toolkit are helping to identify how discrete populations of brain cells function to trigger and shape the timing and transition into and out of different sleep-wake states, and how glia partner with neurons to regulate sleep. Here, we detail how some of the newest technologies are being applied to understand the neural circuits underlying sleep and wake.

Adaptive optical versus spherical aberration corrections for in vivo brain imaging

Adjusting the objective correction collar is a widely used approach to correct spherical aberrations (SA) in optical microscopy. In this work, we characterized and compared its performance with adaptive optics in the context of in vivo brain imaging with two-photon fluorescence microscopy. We found that the presence of sample tilt had a deleterious effect on the performance of SA-only correction. At large tilt angles, adjusting the correction collar even worsened image quality. In contrast, adaptive optical correction always recovered optimal imaging performance regardless of sample tilt. The extent of improvement with adaptive optics was dependent on object size, with smaller objects having larger relative gains in signal intensity and image sharpness. These observations translate into a superior performance of adaptive optics for structural and functional brain imaging applications in vivo, as we confirmed experimentally.

New Tools to Study Astrocyte Ca2+ Signal Dynamics in Brain Networks In Vivo

Sensory information processing is a fundamental operation in the brain that is based on dynamic interactions between different neuronal populations. Astrocytes, a type of glial cells, have been proposed to represent active elements of brain microcircuits that, through dynamic interactions with neurons, provide a modulatory control of neuronal network activity. Specifically, astrocytes in different brain regions have been described to respond to neuronal signals with intracellular Ca²⁺ elevations that represent a key step in the functional recruitment of astrocytes to specific brain circuits. Accumulating evidence shows that Ca²⁺ elevations regulate the release of gliotransmitters that, in turn, modulate synaptic transmission and neuronal excitability. Recent studies also provided new insights into the spatial and temporal features of astrocytic Ca²⁺ elevations revealing a surprising complexity of Ca²⁺ signal dynamics in astrocytes. Here we discuss how recently developed experimental tools such as the genetically encoded Ca²⁺ indicators (GECI), optogenetics and chemogenetics can be applied to the study of astrocytic Ca²⁺ signals in the living brain.

Video-rate volumetric functional imaging of the brain at synaptic resolution

Neurons and neural networks often extend hundreds to thousands of micrometers in three dimensions. To capture all the calcium transients associated with their activity, we need volume imaging methods with sub-second temporal resolution. Such speed is challenging for conventional two-photon laser scanning microscopy (2PLSM) to achieve, because of its dependence on serial focal scanning in 3D and the limited brightness of indicators. Here we present an optical module that can be easily integrated into standard 2PLSMs to generate an axially elongated Bessel focus. Scanning the Bessel focus in 2D turned frame rate into volume rate and enabled video-rate volumetric imaging. Using Bessel foci designed to maintain lateral resolution that resolves synapses in sparsely labeled brains in vivo, we demonstrated the power of this approach in enabling discoveries for neurobiology by imaging the calcium dynamics of volumes of neurons and synapses in fruit flies, zebrafish larvae, mice, and ferrets in vivo.

Probing Deep Brain Circuitry: New Advances in in Vivo Calcium Measurement Strategies

The study of neuronal ensembles in awake and behaving animals is a critical question in contemporary neuroscience research. Through the examination of calcium fluctuations, which are correlated with neuronal activity, we are able to better understand complex neural circuits. Recently, the development of technologies including two-photon microscopy, miniature microscopes, and fiber photometry has allowed us to examine calcium activity in behaving subjects over time. Visualizing changes in intracellular calcium in vivo has been accomplished utilizing GCaMP, a genetically encoded calcium indicator. GCaMP allows researchers to tag cell-type specific neurons with engineered fluorescent proteins that alter their levels of fluorescence in response to changes in intracellular calcium concentration. Even with the evolution of GCaMP, in vivo calcium imaging had yet to overcome the limitation of light scattering, which occurs when imaging from neural tissue in deep brain regions. Currently, researchers have created in vivo methods to bypass this problem; this Review will delve into three of these state of the art techniques: (1) two-photon calcium imaging, (2) single photon calcium imaging, and (3) fiber photometry. Here we discuss the advantages and disadvantages of the three techniques. Continued advances in these imaging techniques will provide researchers with unparalleled access to the inner workings of the brain.

Simultaneous high-speed imaging and optogenetic inhibition in the intact mouse brain

Genetically encoded calcium indicators and optogenetic actuators can report and manipulate the activity of specific neuronal populations. However, applying imaging and optogenetics simultaneously has been difficult to establish in the mammalian brain, even though combining the techniques would provide a powerful approach to reveal the functional organization of neural circuits. Here, we developed a technique based on patterned two-photon illumination to allow fast scanless imaging of GCaMP6 signals in the intact mouse brain at the same time as single-photon optogenetic inhibition with Archaerhodopsin. Using combined imaging and electrophysiological recording, we demonstrate that single and short bursts of action potentials in pyramidal neurons can be detected in the scanless modality at acquisition frequencies up to 1 kHz. Moreover, we demonstrate that our system strongly reduces the artifacts in the fluorescence detection that are induced by single-photon optogenetic illumination. Finally, we validated our technique investigating the role of parvalbumin-positive (PV) interneurons in the control of spontaneous cortical dynamics. Monitoring the activity of cellular populations on a precise spatiotemporal scale while manipulating neuronal activity with optogenetics provides a powerful tool to causally elucidate the cellular mechanisms underlying circuit function in the intact mammalian brain.

Development of practical red fluorescent probe for cytoplasmic calcium ions with greatly improved cell-membrane permeability

Fluorescence imaging of calcium ions (Ca(2+)) has become an essential technique for investigation of signaling pathways involving Ca(2+) as a second messenger. But, Ca(2+) signaling is involved in many biological phenomena, and therefore simultaneous visualization of Ca(2+) and other biomolecules (multicolor imaging) would be particularly informative. For this purpose, we set out to develop a fluorescent probe for Ca(2+) that would operate in a different color region (red) from that of probes for other molecules, many of which show green fluorescence, as exemplified by green fluorescent protein (GFP). We previously developed a red fluorescent probe for monitoring cytoplasmic Ca(2+) concentration, based on our established red fluorophore, TokyoMagenta (TM), but there remained room for improvement, especially as regards efficiency of introduction into cells. We considered that this issue was probably mainly due to limited water solubility of the probe. So, we designed and synthesized a red-fluorescent probe with improved water solubility. We confirmed that this Ca(2+) red-fluorescent probe showed high cell-membrane permeability with bright fluorescence. It was successfully applied to fluorescence imaging of not only live cells, but also brain slices, and should be practically useful for multicolor imaging studies of biological mechanisms.

Reconstruction of burst activity from calcium imaging of neuronal population via Lq minimization and interval screening

Calcium imaging is becoming an increasingly popular technology to indirectly measure activity patterns in local neuronal networks. Based on the dependence of calcium fluorescence on neuronal spiking, two-photon calcium imaging affords single-cell resolution of neuronal population activity. However, it is still difficult to reconstruct neuronal activity from complex calcium fluorescence traces, particularly for traces contaminated by noise. Here, we describe a robust and efficient neuronal-activity reconstruction method that utilizes Lq minimization and interval screening (IS), which we refer to as LqIS. The simulation results show that LqIS performs satisfactorily in terms of both accuracy and speed of reconstruction. Reconstruction of simulation and experimental data also shows that LqIS has advantages in terms of the recall rate, precision rate, and timing error. Finally, LqIS is demonstrated to effectively reconstruct neuronal burst activity from calcium fluorescence traces recorded from large-size neuronal population.

Imaging Axonal Degeneration and Repair in Preclinical Animal Models of Multiple Sclerosis

Multiple sclerosis (MS) is a central nervous system (CNS) disease characterized by chronic neuroinflammation, demyelination, and axonal damage. Infiltration of activated lymphocytes and myeloid cells are thought to be primarily responsible for white matter damage and axonopathy. Over time, this neurologic damage manifests clinically as debilitating motor and cognitive symptoms. Existing MS therapies focus on symptom relief and delay of disease progression through reduction of neuroinflammation. However, long-term strategies to remyelinate, protect, or regenerate axons have remained elusive, posing a challenge to treating progressive forms of MS. Preclinical mouse models and techniques, such as immunohistochemistry, flow cytometry, and genomic and proteomic analysis have provided advances in our understanding of discrete time-points of pathology following disease induction. More recently, in vivo and in situ two-photon (2P) microscopy has made it possible to visualize continuous real-time cellular behavior and structural changes occurring within the CNS during neuropathology. Research utilizing 2P imaging to study axonopathy in neuroinflammatory demyelinating disease has focused on five areas: (1) axonal morphologic changes, (2) organelle transport and health, (3) relationship to inflammation, (4) neuronal excitotoxicity, and (5) regenerative therapies. 2P imaging may also be used to identify novel therapeutic targets via identification and clarification of dynamic cellular and molecular mechanisms of axonal regeneration and remyelination. Here, we review tools that have made 2P accessible for imaging neuropathologies and advances in our understanding of axonal degeneration and repair in preclinical models of demyelinating diseases.

Inferring Neuronal Dynamics from Calcium Imaging Data Using Biophysical Models and Bayesian Inference

Calcium imaging has been used as a promising technique to monitor the dynamic activity of neuronal populations. However, the calcium trace is temporally smeared which restricts the extraction of quantities of interest such as spike trains of individual neurons. To address this issue, spike reconstruction algorithms have been introduced. One limitation of such reconstructions is that the underlying models are not informed about the biophysics of spike and burst generations. Such existing prior knowledge might be useful for constraining the possible solutions of spikes. Here we describe, in a novel Bayesian approach, how principled knowledge about neuronal dynamics can be employed to infer biophysical variables and parameters from fluorescence traces. By using both synthetic and in vitro recorded fluorescence traces, we demonstrate that the new approach is able to reconstruct different repetitive spiking and/or bursting patterns with accurate single spike resolution. Furthermore, we show that the high inference precision of the new approach is preserved even if the fluorescence trace is rather noisy or if the fluorescence transients show slow rise kinetics lasting several hundred milliseconds, and inhomogeneous rise and decay times. In addition, we discuss the use of the new approach for inferring parameter changes, e.g. due to a pharmacological intervention, as well as for inferring complex characteristics of immature neuronal circuits.

Calcium imaging of single neurons enables the indirect observation of neuronal dynamics, for example action potential firing. In contrast to the precise timing of spike trains, the calcium trace is temporally rather smeared and measured as a fluorescence trace. Consequently, several methods have been proposed to reconstruct spikes from calcium imaging data. However, a common feature of these methods is that they are not based on the biophysics of how neurons fire spikes and bursts. We propose to introduce well-established biophysical models to create a direct link between neuronal dynamics, e.g. the membrane potential, and fluorescence traces. Using both synthetic and experimental data, we show that this approach not only provides a robust and accurate spike reconstruction but also a reliable inference about the biophysically relevant parameters and variables. This enables novel ways of analyzing calcium imaging experiments in terms of the underlying biophysical quantities.

Immediate manifestation of acoustic trauma in the auditory cortex is layer specific and cell type dependent

Exposure to loud sounds damages the auditory periphery and induces maladaptive changes in central parts of the auditory system. Diminished peripheral afferentation and altered inhibition influence the processing of sounds in the auditory cortex. It is unclear, however, which types of inhibitory interneurons are affected by acoustic trauma. Here we used single-unit electrophysiological recording and two-photon calcium imaging in anesthetized mice to evaluate the effects of acute acoustic trauma (125 dB SPL, white noise, 5 min) on the response properties of neurons in the core auditory cortex. Electrophysiological measurements suggested the selective impact of acoustic trauma on inhibitory interneurons in the auditory cortex. To further investigate which interneuronal types were affected, we used two-photon calcium imaging to record the activity of neurons in cortical layers 2/3 and 4, specifically focusing on parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons. Spontaneous and pure-tone-evoked firing rates of SST+ interneurons increased in layer 4 immediately after acoustic trauma and remained almost unchanged in layer 2/3. Furthermore, PV+ interneurons with high best frequencies increased their evoked-to-spontaneous firing rate ratios only in layer 2/3 and did not change in layer 4. Finally, acoustic trauma unmasked low-frequency excitatory inputs only in layer 2/3. Our results demonstrate layer-specific changes in the activity of auditory cortical inhibitory interneurons within minutes after acoustic trauma.

LFP-guided targeting of a cortical barrel column for in vivo two-photon calcium imaging

Two-photon microscopy of bulk-loaded functional dyes is an outstanding physiological technique that enables simultaneous functional mapping of hundreds of brain cells in vivo at single-cell resolution. However, precise targeting of a specific cortical location is not easy due to its fine dimensionality. To enable precise targeting, intrinsic-signal optical imaging is often additionally performed. However, the intrinsic-signal optical imaging is not only time-consuming but also ineffective in ensuring precision. Here, we propose an alternative method for precise targeting based on local field potential (LFP) recording, a conventional electrophysiological method. The heart of this method lies in use of the same glass pipette to record LFPs and to eject calcium dye. After confirming the target area by LFP using a glass pipette, the calcium dye is ejected from the same pipette without a time delay or spatial adjustment. As a result, the calcium dye is loaded into the same ensemble of brain cells from which the LFP was obtained. As a validation of the proposed LFP-based method, we targeted and successfully loaded calcium dye into layer 2/3 of a mouse barrel column.