An integrated calcium imaging processing toolbox for the analysis of neuronal population dynamics

Ciliogenesis defects after neurulation impact brain development and neuronal activity in larval zebrafish

Cilia are slender, hair-like structures extending from cell surfaces and playing essential roles in diverse physiological processes. Within the nervous system, primary cilia contribute to signaling and sensory perception, while motile cilia facilitate cerebrospinal fluid flow. Here, we investigated the impact of ciliary loss on neural circuit development using a zebrafish line displaying ciliogenesis defects. We found that cilia defects after neurulation affect neurogenesis and brain morphology, especially in the cerebellum, and lead to altered gene expression profiles. Using whole brain calcium imaging, we measured reduced light-evoked and spontaneous neuronal activity in all brain regions. By shedding light on the intricate role of cilia in neural circuit formation and function in the zebrafish, our work highlights their evolutionary conserved role in the brain and sets the stage for future analysis of ciliopathy models.

Assessing spontaneous sensory neuron activity using in vivo calcium imaging

ABSTRACT

Heightened spontaneous activity in sensory neurons is often reported in individuals living with chronic pain. It is possible to study this activity in rodents using electrophysiology, but these experiments require great skill and can be prone to bias. Here, we have examined whether in vivo calcium imaging with GCaMP6s can be used as an alternative approach. We show that spontaneously active calcium transients can be visualised in the fourth lumbar dorsal root ganglion (L4 DRG) through in vivo imaging in a mouse model of inflammatory pain. Application of lidocaine to the nerve, between the inflamed site and the DRG, silenced spontaneous firing and revealed the true baseline level of calcium for spontaneously active neurons. We used these data to train a machine learning algorithm to predict when a neuron is spontaneously active. We show that our algorithm is accurate in 2 different models of pain: intraplantar complete Freund adjuvant and antigen-induced arthritis, with accuracies of 90.0% ±1.2 and 85.9% ±2.1, respectively, assessed against visual inspection by an experienced observer. The algorithm can also detect neuronal activity in imaging experiments generated in a different laboratory using a different microscope configuration (accuracy = 94.0% ±2.2). We conclude that in vivo calcium imaging can be used to assess spontaneous activity in sensory neurons and provide a Google Colaboratory Notebook to allow anyone easy access to our novel analysis tool, for the assessment of spontaneous neuronal activity in their own imaging setups.

Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within 'remapped' forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.

Non-Negative Matrix Factorization for Analyzing State Dependent Neuronal Network Dynamics in Calcium Recordings

Calcium imaging allows recording from hundreds of neurons in vivo with the ability to resolve single cell activity. Evaluating and analyzing neuronal responses, while also considering all dimensions of the data set to make specific conclusions, is extremely difficult. Often, descriptive statistics are used to analyze these forms of data. These analyses, however, remove variance by averaging the responses of single neurons across recording sessions, or across combinations of neurons, to create single quantitative metrics, losing the temporal dynamics of neuronal activity, and their responses relative to each other. Dimensionally Reduction (DR) methods serve as a good foundation for these analyses because they reduce the dimensions of the data into components, while still maintaining the variance. Non-negative Matrix Factorization (NMF) is an especially promising DR analysis method for analyzing activity recorded in calcium imaging because of its mathematical constraints, which include positivity and linearity. We adapt NMF for our analyses and compare its performance to alternative dimensionality reduction methods on both artificial and in vivo data. We find that NMF is well-suited for analyzing calcium imaging recordings, accurately capturing the underlying dynamics of the data, and outperforming alternative methods in common use.

Position-independent functional refinement within the vagus motor topographic map

Motor neurons in the central nervous system often lie in a continuous topographic map, where neurons that innervate different body parts are spatially intermingled. This is the case for the efferent neurons of the vagus nerve, which innervate diverse muscle and organ targets in the head and viscera for brain-body communication. It remains elusive how neighboring motor neurons with different fixed peripheral axon targets develop the separate somatodendritic (input) connectivity they need to generate spatially precise body control. Here we show that vagus motor neurons in the zebrafish indeed generate spatially appropriate peripheral responses to focal sensory stimulation even when they are transplanted into ectopic positions within the topographic map, indicating that circuit refinement occurs after the establishment of coarse topography. Refinement depends on motor neuron synaptic transmission, suggesting that an experience-dependent periphery-to-brain feedback mechanism establishes specific input connectivity amongst intermingled motor populations.

In-Vivo Calcium Imaging of Sensory Neurons in the Rat Trigeminal Ganglion

Genetically encoded calcium indicators (GECIs) enable imaging techniques to monitor changes in intracellular calcium in targeted cell populations. Their large signal-to-noise ratio makes GECIs a powerful tool for detecting stimulus-evoked activity in sensory neurons. GECIs facilitate population-level analysis of stimulus encoding with the number of neurons that can be studied simultaneously. This population encoding is most appropriately done in vivo. Dorsal root ganglia (DRG), which house the soma of sensory neurons innervating somatic and visceral structures below the neck, are used most extensively for in vivo imaging because these structures are accessed relatively easily. More recently, this technique was used in mice to study sensory neurons in the trigeminal ganglion (TG) that innervate oral and craniofacial structures. There are many reasons to study TG in addition to DRG, including the long list of pain syndromes specific to oral and craniofacial structures that appear to reflect changes in sensory neuron activity, such as trigeminal neuralgia. Mice are used most extensively in the study of DRG and TG neurons because of the availability of genetic tools. However, with differences in size, ease of handling, and potentially important species differences, there are reasons to study rat rather than mouse TG neurons. Thus, we developed an approach for imaging rat TG neurons in vivo. We injected neonatal pups (p2) intraperitoneally with an AAV encoding GCaMP6s, resulting in >90% infection of both TG and DRG neurons. TG was visualized in the adult following craniotomy and decortication, and changes in GCaMP6s fluorescence were monitored in TG neurons following stimulation of mandibular and maxillary regions of the face. We confirmed that increases in fluorescence were stimulus-evoked with peripheral nerve block. While this approach has many potential uses, we are using it to characterize the subpopulation(s) of TG neurons changed following peripheral nerve injury.

Embryos assist morphogenesis of others through calcium and ATP signaling mechanisms in collective teratogen resistance

Information for organismal patterning can come from a variety of sources. We investigate the possibility that instructive influences for normal embryonic development are provided not only at the level of cells within the embryo, but also via interactions between embryos. To explore this, we challenge groups of embryos with disruptors of normal development while varying group size. Here, we show that Xenopus laevis embryos are much more sensitive to a diverse set of chemical and molecular-biological perturbations when allowed to develop alone or in small groups, than in large groups. Keeping per-embryo exposure constant, we find that increasing the number of exposed embryos in a cohort increases the rate of survival while incidence of defects decreases. This inter-embryo assistance effect is mediated by short-range diffusible signals and involves the P2 ATP receptor. Our data and computational model emphasize that morphogenesis is a collective phenomenon not only at the level of cells, but also of whole bodies, and that cohort size is a crucial variable in studies of ecotoxicology, teratogenesis, and developmental plasticity.

Radial astrocyte synchronization modulates the visual system during behavioral-state transitions

Glial cells support the function of neurons. Recent evidence shows that astrocytes are also involved in brain computations. To explore whether and how their excitable nature affects brain computations and motor behaviors, we used two-photon Ca2+ imaging of zebrafish larvae expressing GCaMP in both neurons and radial astrocytes (RAs). We found that in the optic tectum, RAs synchronize their Ca2+ transients immediately after the end of an escape behavior. Using optogenetics, ablations, and a genetically encoded norepinephrine sensor, we observed that RA synchronous Ca2+ events are mediated by the locus coeruleus (LC)-norepinephrine circuit. RA synchronization did not induce direct excitation or inhibition of tectal neurons. Nevertheless, it modulated the direction selectivity and the long-distance functional correlations among neurons. This mechanism supports freezing behavior following a switch to an alerted state. These results show that LC-mediated neuro-glial interactions modulate the visual system during transitions between behavioral states.

A protocol for whole-brain Ca2+ imaging in Astyanax mexicanus, a model of comparative evolution

In this protocol, we describe a comparative approach to study the evolution of brain function in the Mexican tetra, Astyanax mexicanus. We developed surface fish and two independent populations of cavefish with pan-neuronal expression of the Ca2+ sensor GCaMP6s. We describe a methodology to prepare samples and image activity across the optic tectum and olfactory bulb.

Pynapple, a toolbox for data analysis in neuroscience

Datasets collected in neuroscientific studies are of ever-growing complexity, often combining high-dimensional time series data from multiple data acquisition modalities. Handling and manipulating these various data streams in an adequate programming environment is crucial to ensure reliable analysis, and to facilitate sharing of reproducible analysis pipelines. Here, we present Pynapple, the PYthon Neural Analysis Package, a lightweight python package designed to process a broad range of time-resolved data in systems neuroscience. The core feature of this package is a small number of versatile objects that support the manipulation of any data streams and task parameters. The package includes a set of methods to read common data formats and allows users to easily write their own. The resulting code is easy to read and write, avoids low-level data processing and other error-prone steps, and is open source. Libraries for higher-level analyses are developed within the Pynapple framework but are contained within a collaborative repository of specialized and continuously updated analysis routines. This provides flexibility while ensuring long-term stability of the core package. In conclusion, Pynapple provides a common framework for data analysis in neuroscience.

Dopamine-Dependent Plasticity Is Heterogeneously Expressed by Presynaptic Calcium Activity across Individual Boutons of the Drosophila Mushroom Body

The Drosophila mushroom body (MB) is an important model system for studying the synaptic mechanisms of associative learning. In this system, coincidence of odor-evoked calcium influx and dopaminergic input in the presynaptic terminals of Kenyon cells (KCs), the principal neurons of the MB, triggers long-term depression (LTD), which plays a critical role in olfactory learning. However, it is controversial whether such synaptic plasticity is accompanied by a corresponding decrease in odor-evoked calcium activity in the KC presynaptic terminals. Here, we address this question by inducing LTD by pairing odor presentation with optogenetic activation of dopaminergic neurons (DANs). This allows us to rigorously compare the changes at the presynaptic and postsynaptic sites in the same conditions. By imaging presynaptic acetylcholine release in the condition where LTD is reliably observed in the postsynaptic calcium signals, we show that neurotransmitter release from KCs is depressed selectively in the MB compartments innervated by activated DANs, demonstrating the presynaptic nature of LTD. However, total odor-evoked calcium activity of the KC axon bundles does not show concurrent depression. We further conduct calcium imaging in individual presynaptic boutons and uncover the highly heterogeneous nature of calcium plasticity. Namely, only a subset of boutons, which are strongly activated by associated odors, undergo calcium activity depression, while weakly responding boutons show potentiation. Thus, our results suggest an unexpected nonlinear relationship between presynaptic calcium influx and the results of plasticity, challenging the simple view of cooperative actions of presynaptic calcium and dopaminergic input.

Machine learning discriminates P2X7-mediated intracellular calcium sparks in human-induced pluripotent stem cell-derived neural stem cells

Adenosine triphosphate (ATP) is an extracellular signaling molecule that mainly affects the pathophysiological situation in the body and can be sensed by purinergic receptors, including ionotropic P2X7. Neuronal stem cells (NSCs) remain in adult neuronal tissues and can contribute to physiological processes via activation by evoked pathophysiological situations. In this study, we revealed that human-induced pluripotent stem cell-derived NSCs (iNSCs) have ATP-sensing ability primarily via the purinergic and ionotropic receptor P2X7. Next, to develop a machine learning (ML)-based screening system for food-derived neuronal effective substances and their effective doses, we collected ATP-triggered calcium responses of iNSCs pretreated with several substances and doses. Finally, we discovered that ML was performed using composite images, each containing nine waveform images, to achieve a better ML model (MLM) with higher precision. Our MLM can correctly sort subtle unidentified changes in waveforms produced by pretreated iNSCs with each substance and/or dose into the positive group, with common mRNA expression changes belonging to the gene ontology signatures.

Cell cycle controls long-range calcium signaling in the regenerating epidermis

Skin homeostasis is maintained by stem cells, which must communicate to balance their regenerative behaviors. Yet, how adult stem cells signal across regenerative tissue remains unknown due to challenges in studying signaling dynamics in live mice. We combined live imaging in the mouse basal stem cell layer with machine learning tools to analyze patterns of Ca2+ signaling. We show that basal cells display dynamic intercellular Ca2+ signaling among local neighborhoods. We find that these Ca2+ signals are coordinated across thousands of cells and that this coordination is an emergent property of the stem cell layer. We demonstrate that G2 cells are required to initiate normal levels of Ca2+ signaling, while connexin43 connects basal cells to orchestrate tissue-wide coordination of Ca2+ signaling. Lastly, we find that Ca2+ signaling drives cell cycle progression, revealing a communication feedback loop. This work provides resolution into how stem cells at different cell cycle stages coordinate tissue-wide signaling during epidermal regeneration.

Early development of respiratory motor circuits in larval zebrafish (Danio rerio)

Rhythm-generating circuits in the vertebrate hindbrain form synaptic connections with cranial and spinal motor neurons, to generate coordinated, patterned respiratory behaviors. Zebrafish provide a uniquely tractable model system to investigate the earliest stages in respiratory motor circuit development in vivo. In larval zebrafish, respiratory behaviors are carried out by muscles innervated by cranial motor neurons-including the facial branchiomotor neurons (FBMNs), which innervate muscles that move the jaw, buccal cavity, and operculum. However, it is unclear when FBMNs first receive functional synaptic input from respiratory pattern-generating neurons, and how the functional output of the respiratory motor circuit changes across larval development. In the current study, we used behavior and calcium imaging to determine how early FBMNs receive functional synaptic inputs from respiratory pattern-generating networks in larval zebrafish. Zebrafish exhibited patterned operculum movements by 3 days postfertilization (dpf), though this behavior became more consistent at 4 and 5 dpf. Also by 3dpf, FBMNs fell into two distinct categories ("rhythmic" and "nonrhythmic"), based on patterns of neural activity. These two neuron categories were arranged differently along the dorsoventral axis, demonstrating that FBMNs have already established dorsoventral topography by 3 dpf. Finally, operculum movements were coordinated with pectoral fin movements at 3 dpf, indicating that the operculum behavioral pattern was driven by synaptic input. Taken together, this evidence suggests that FBMNs begin to receive initial synaptic input from a functional respiratory central pattern generator at or prior to 3 dpf. Future studies will use this model to study mechanisms of normal and abnormal respiratory circuit development.

Evaluation of Neurotoxicity With Human Pluripotent Stem Cell-Derived Cerebral Organoids

The recent development of human cerebral organoids provides an invaluable in vitro model of human brain development to assess the toxicity of natural or man-made toxic substances. By recapitulating key aspects of early human neurodevelopment, investigators can evaluate with this three-dimensional (3D) model the effect of certain compounds on the formation of neuronal networks and their electrophysiological properties with more physiological relevance than neurons grown in monolayers and in cultures composed of a unique cell type. This promising potential has contributed to the development of a large number of diverse protocols to generate human cerebral organoids, making interlaboratory comparisons of results difficult. Based on a previously published protocol to generate human cortical organoids (herein called cerebral organoids), we detail several approaches to evaluate the effect of chemicals on neurogenesis, apoptosis, and neuronal function when exogenously applied to cultured specimens. Here, we take as an example 4-aminopyridine, a potassium channel blocker that modulates the activity of neurons and neurogenesis, and describe a simple and cost-effective way to test the impact of this agent on cerebral organoids derived from human induced pluripotent stem cells. We also provide tested protocols to evaluate neurogenesis in cerebral organoids with ethynyl deoxyuridine labeling and neuronal activity with live calcium imaging and microelectrode arrays. Together, these protocols should facilitate the implementation of cerebral organoid technologies in laboratories wishing to evaluate the effects of specific compounds or conditions on the development and function of human neurons with only basic cell culture equipment. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Generation of human cerebral organoids from pluripotent stem cells Support Protocol 1: Human pluripotent stem cell culture Basic Protocol 2: Evaluation of neurogenesis in cerebral organoids with ethynyl deoxyuridine labeling Basic Protocol 3: Calcium imaging in cerebral organoids Basic Protocol 4: Electrophysiological evaluation of cerebral organoids with microelectrode arrays Support Protocol 2: Immunostaining of cerebral organoids.

Review of data processing of functional optical microscopy for neuroscience

Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.

Blind cavefish retain functional connectivity in the tectum despite loss of retinal input

Sensory systems display remarkable plasticity and are under strong evolutionary selection. The Mexican cavefish, Astyanax mexicanus, consists of eyed river-dwelling surface populations and multiple independent cave populations that have converged on eye loss, providing the opportunity to examine the evolution of sensory circuits in response to environmental perturbation. Functional analysis across multiple transgenic populations expressing GCaMP6s showed that functional connectivity of the optic tectum largely did not differ between populations, except for the selective loss of negatively correlated activity within the cavefish tectum, suggesting positively correlated neural activity is resistant to an evolved loss of input from the retina. Furthermore, analysis of surface-cave hybrid fish reveals that changes in the tectum are genetically distinct from those encoding eye loss. Together, these findings uncover the independent evolution of multiple components of the visual system and establish the use of functional imaging in A. mexicanus to study neural circuit evolution.

Visual-area-specific tonic modulation of GABA release by endocannabinoids sets the activity and coordination of neocortical principal neurons

Perisomatic inhibition of pyramidal neurons (PNs) coordinates cortical network activity during sensory processing, and this role is mainly attributed to parvalbumin-expressing basket cells (BCs). However, cannabinoid receptor type 1 (CB1)-expressing interneurons are also BCs, but the connectivity and function of these elusive but prominent neocortical inhibitory neurons are unclear. We find that their connectivity pattern is visual area specific. Persistently active CB1 signaling suppresses GABA release from CB1 BCs in the medial secondary visual cortex (V2M), but not in the primary visual cortex (V1). Accordingly, in vivo, tonic CB1 signaling is responsible for higher but less coordinated PN activity in the V2M than in the V1. These differential firing dynamics in the V1 and V2M can be captured by a computational network model that incorporates visual-area-specific properties. Our results indicate a differential CB1-mediated mechanism controlling PN activity, suggesting an alternative connectivity scheme of a specific GABAergic circuit in different cortical areas.

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CB1⁺ basket cells exhibit visual-area-specific morphology and connectivity patterns

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Tonic CB1 signaling underlies high pyramidal neurons (PN) activity in V2M but not V1

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Tonic CB1 signaling differentially modulates PN-correlated activity in V1 and V2M

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Numerical simulations capture specific CB1-dependent firing dynamics of V1 and V2M

Spontaneous Activity Predicts Survival of Developing Cortical Neurons

Spontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneous activity patterns directly encode for survival of individual cortical neurons during development remains an open question. Here, we longitudinally investigated spontaneous activity and apoptosis in developing cortical cultures, combining extracellular electrophysiology with calcium imaging. These experiments demonstrated that the early occurrence of calcium transients was strongly linked to neuronal survival. Silent neurons exhibited a higher probability of cell death, whereas high frequency spiking and burst behavior were almost exclusively detected in surviving neurons. In local neuronal clusters, activity of neighboring neurons exerted a pro-survival effect, whereas on the functional level, networks with a high modular topology were associated with lower cell death rates. Using machine learning algorithms, cell fate of individual neurons was predictable through the integration of spontaneous activity features. Our results indicate that high frequency spiking activity constrains apoptosis in single neurons through sustained calcium rises and thereby consolidates networks in which a high modular topology is reached during early development.

SmaRT2P: a software for generating and processing smart line recording trajectories for population two-photon calcium imaging

Two-photon fluorescence calcium imaging allows recording the activity of large neural populations with subcellular spatial resolution, but it is typically characterized by low signal-to-noise ratio (SNR) and poor accuracy in detecting single or few action potentials when large number of neurons are imaged. We recently showed that implementing a smart line scanning approach using trajectories that optimally sample the regions of interest increases both the SNR fluorescence signals and the accuracy of single spike detection in population imaging in vivo. However, smart line scanning requires highly specialised software to design recording trajectories, interface with acquisition hardware, and efficiently process acquired data. Furthermore, smart line scanning needs optimized strategies to cope with movement artefacts and neuropil contamination. Here, we develop and validate SmaRT2P, an open-source, user-friendly and easy-to-interface Matlab-based software environment to perform optimized smart line scanning in two-photon calcium imaging experiments. SmaRT2P is designed to interface with popular acquisition software (e.g., ScanImage) and implements novel strategies to detect motion artefacts, estimate neuropil contamination, and minimize their impact on functional signals extracted from neuronal population imaging. SmaRT2P is structured in a modular way to allow flexibility in the processing pipeline, requiring minimal user intervention in parameter setting. The use of SmaRT2P for smart line scanning has the potential to facilitate the functional investigation of large neuronal populations with increased SNR and accuracy in detecting the discharge of single and few action potentials.

Computational Methods for Neuron Segmentation in Two-Photon Calcium Imaging Data: A Survey

Calcium imaging has rapidly become a methodology of choice for real-time in vivo neuron analysis. Its application to large sets of data requires automated tools to annotate and segment cells, allowing scalable image segmentation under reproducible criteria. In this paper, we review and summarize the most recent methods for computational segmentation of calcium imaging. The contributions of the paper are three-fold: we provide an overview of the main algorithms taxonomized in three categories (signal processing, matrix factorization and machine learning-based approaches), we highlight the main advantages and disadvantages of each category and we provide a summary of the performance of the methods that have been tested on public benchmarks (with links to the public code when available).

Critical Spatial-Temporal Dynamics and Prominent Shape Collapse of Calcium Waves Observed in Human hNT Astrocytes in Vitro

Networks of neurons are typically studied in the field of Criticality. However, the study of astrocyte networks in the brain has been recently lauded to be of equal importance to that of the neural networks. To date criticality assessments have only been performed on networks astrocytes from healthy rats, and astrocytes from cultured dissociated resections of intractable epilepsy. This work, for the first time, presents studies of the critical dynamics and shape collapse of calcium waves observed in cultures of healthy human astrocyte networks in vitro, derived from the human hNT cell line. In this article, we demonstrate that avalanches of spontaneous calcium waves display strong critical dynamics, including power-laws in both the size and duration distributions. In addition, the temporal profiles of avalanches displayed self-similarity, leading to shape collapse of the temporal profiles. These findings are significant as they suggest that cultured networks of healthy human hNT astrocytes self-organize to a critical point, implying that healthy astrocytic networks operate at a critical point to process and transmit information. Furthermore, this work can serve as a point of reference to which other astrocyte criticality studies can be compared.

cytoNet: Spatiotemporal network analysis of cell communities

We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet’s capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo, 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin α4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.

Calcium imaging in intact mouse acinar cells in acute pancreas tissue slices

The physiology and pathophysiology of the exocrine pancreas are in close connection to changes in intra-cellular Ca²⁺ concentration. Most of our knowledge is based on in vitro experiments on acinar cells or acini enzymatically isolated from their surroundings, which can alter their structure, physiology, and limit our understanding. Due to these limitations, the acute pancreas tissue slice technique was introduced almost two decades ago as a complementary approach to assess the morphology and physiology of both the endocrine and exocrine pancreas in a more conserved in situ setting. In this study, we extend previous work to functional multicellular calcium imaging on acinar cells in tissue slices. The viability and morphological characteristics of acinar cells within the tissue slice were assessed using the LIVE/DEAD assay, transmission electron microscopy, and immunofluorescence imaging. The main aim of our study was to characterize the responses of acinar cells to stimulation with acetylcholine and compare them with responses to cerulein in pancreatic tissue slices, with special emphasis on inter-cellular and inter-acinar heterogeneity and coupling. To this end, calcium imaging was performed employing confocal microscopy during stimulation with a wide range of acetylcholine concentrations and selected concentrations of cerulein. We show that various calcium oscillation parameters depend monotonically on the stimulus concentration and that the activity is rather well synchronized within acini, but not between acini. The acute pancreas tissue slice represents a viable and reliable experimental approach for the evaluation of both intra- and inter-cellular signaling characteristics of acinar cell calcium dynamics. It can be utilized to assess many cells simultaneously with a high spatiotemporal resolution, thus providing an efficient and high-yield platform for future studies of normal acinar cell biology, pathophysiology, and screening pharmacological substances.

Genetic and Neurological Deficiencies in the Visual System of mct8 Mutant Zebrafish

Thyroid hormones (THs; T3 and T4) enter cells using specific transporters and regulate development and metabolism. Mutation in the TH transporter monocarboxylate transporter 8 (MCT8, SLC16A2) is associated with brain hypothyroidism and neurological impairment. We established mct8 mutant (mct8-/-) zebrafish as a model for MCT8 deficiency, which causes endocrinological, neurological, and behavioral alterations. Here, we profiled the transcriptome of mct8-/- larvae. Among hundreds of differentially expressed genes, the expression of a cluster of vision-related genes was distinct. Specifically, the expression of the opsin 1 medium wave sensitive 2 (opn1mw2) decreased in two mct8 mutants: mct8-/- and mct8^-25bp-/- larvae, and under pharmacological inhibition of TH production. Optokinetic reflex (OKR) assays showed a reduction in the number of conjugated eye movements, and live imaging of genetically encoded Ca²⁺ indicator revealed altered neuronal activity in the pretectum area of mct8^-25bp-/- larvae. These results imply that MCT8 and THs regulate the development of the visual system and suggest a mechanism to the deficiencies observed in the visual system of MCT8-deficiency patients.

To deconvolve, or not to deconvolve: Inferences of neuronal activities using calcium imaging data

BACKGROUND

With the increasing popularity of calcium imaging in neuroscience research, choosing the right methods to analyze calcium imaging data is critical to address various scientific questions. Unlike spike trains measured using electrodes, fluorescence intensity traces provide an indirect and noisy measurement of the underlying neuronal activities. The observed calcium traces are either analyzed directly or deconvolved to spike trains to infer neuronal activities. When both approaches are applicable, it is unclear whether deconvolving calcium traces is a necessary step.

METHODS

In this article, we compare the performance of using calcium traces or their deconvolved spike trains for three common analyses: clustering, principal component analysis (PCA), and population decoding.

RESULTS

We found that (1) the two approaches lead to diverging results; (2) estimated spike trains, when smoothed or binned appropriately, usually lead to satisfactory performances, such as more accurate estimation of cluster membership; (3) although estimate spike train produce results more similar to true spike data than trace data, we found that the PCA results from trace data might better reflect the underlying neuronal ensembles (clusters); and (4) for both approaches, decobability can be improved by using denoising or smoothing methods.

COMPARISON WITH EXISTING METHODS

Our simulations and applications to real data suggest that estimated spike data outperform trace data in cluster analysis and give comparable results for population decoding. In addition, the decobability of estimated spike data can be slightly better than that of calcium trace data with appropriate filtering / smoothing methods.

CONCLUSION

We conclude that spike detection might be a useful pre-processing step for certain problems such as clustering; however, the continuous nature of calcium imaging data provides a natural smoothness that might be helpful for problems such as dimensional reduction.

Fourier Motion Processing in the Optic Tectum and Pretectum of the Zebrafish Larva

In the presence of moving visual stimuli, the majority of animals follow the Fourier motion energy (luminance), independently of other stimulus features (edges, contrast, etc.). While the behavioral response to Fourier motion has been studied in the past, how Fourier motion is represented and processed by sensory brain areas remains elusive. Here, we investigated how visual moving stimuli with or without the first Fourier component (square-wave signal or missing fundamental signal) are represented in the main visual regions of the zebrafish brain. First, we monitored the larva's optokinetic response (OKR) induced by square-wave and missing fundamental signals. Then, we used two-photon microscopy and GCaMP6f zebrafish larvae to monitor neuronal circuit dynamics in the optic tectum and the pretectum. We observed that both the optic tectum and the pretectum circuits responded to the square-wave gratings. However, only the pretectum responded specifically to the direction of the missing-fundamental signal. In addition, a group of neurons in the pretectum responded to the direction of the behavioral output (OKR), independently of the type of stimulus presented. Our results suggest that the optic tectum responds to the different features of the stimulus (e.g., contrast, spatial frequency, direction, etc.), but does not respond to the direction of motion if the motion information is not coherent (e.g., the luminance and the edges and contrast in the missing-fundamental signal). On the other hand, the pretectum mainly responds to the motion of the stimulus based on the Fourier energy.

Experience-dependent plasticity modulates ongoing activity in the antennal lobe and enhances odor representations

Ongoing neural activity has been observed across several brain regions and is thought to reflect the internal state of the brain. Yet, it is important to understand how ongoing neural activity interacts with sensory experience and shapes sensory representations. Here, we show that the projection neurons of the fruit fly antennal lobe exhibit spatiotemporally organized ongoing activity. After repeated exposure to odors, we observe a gradual and cumulative decrease in the amplitude and number of calcium events occurring in the absence of odor stimulation, as well as a reorganization of correlations between olfactory glomeruli. Accompanying these plastic changes, we find that repeated odor experience decreases trial-to-trial variability and enhances the specificity of odor representations. Our results reveal an odor-experience-dependent modulation of ongoing and sensory-evoked activity at peripheral levels of the fruit fly olfactory system.

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The fruit fly antennal lobe exhibits spatiotemporally organized ongoing activity

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Repeated odor experience decreases the amplitude and number of ongoing calcium events

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Odor experience enhances the robustness and the specificity of odor representations

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Representations of different odors become more dissimilar upon repeated exposure

Parp1 promotes sleep, which enhances DNA repair in neurons

The characteristics of the sleep drivers and the mechanisms through which sleep relieves the cellular homeostatic pressure are unclear. In flies, zebrafish, mice, and humans, DNA damage levels increase during wakefulness and decrease during sleep. Here, we show that 6 h of consolidated sleep is sufficient to reduce DNA damage in the zebrafish dorsal pallium. Induction of DNA damage by neuronal activity and mutagens triggered sleep and DNA repair. The activity of the DNA damage response (DDR) proteins Rad52 and Ku80 increased during sleep, and chromosome dynamics enhanced Rad52 activity. The activity of the DDR initiator poly(ADP-ribose) polymerase 1 (Parp1) increased following sleep deprivation. In both larva zebrafish and adult mice, Parp1 promoted sleep. Inhibition of Parp1 activity reduced sleep-dependent chromosome dynamics and repair. These results demonstrate that DNA damage is a homeostatic driver for sleep, and Parp1 pathways can sense this cellular pressure and facilitate sleep and repair activity.

Cocaine experience induces functional adaptations in astrocytes: Implications for synaptic plasticity in the nucleus accumbens shell

Astrocytes have become established as an important regulator of neuronal activity in the brain. Accumulating literature demonstrates that cocaine self-administration in rodent models induces structural changes within astrocytes that may influence their interaction with the surrounding neurons. Here, we provide evidence that cocaine impacts astrocytes at the functional level and alters neuronal sensitivity to astrocyte-derived glutamate. We report that a 14-day period of short access to cocaine (2 h/day) decreases spontaneous astrocytic Ca²⁺ transients and precipitates changes in astrocyte network activity in the nucleus accumbens shell. This is accompanied by increased prevalence of slow inward currents, a physiological marker of neuronal activation by astrocytic glutamate, in a subset of medium spiny neurons. Within, but not outside, of this subset, we observe an increase in duration and frequency of N-methyl-D-aspartate (NMDA) receptor-mediated synaptic events. Additionally, we find that the link between synaptic NMDA receptor plasticity and neuron sensitivity to astrocytic glutamate is maintained independent of drug exposure and is observed in both cocaine and saline control animals. Imaging analyses of neuronal Ca²⁺ activity show no effect of cocaine self-administration on individual cells or on neuronal network activity in brain slices. Therefore, our data indicate that cocaine self-administration promotes astrocyte-specific functional changes that can be linked to increased glutamate-mediated coupling with principal neurons in the nucleus accumbens. Such coupling may be spatially restricted as it does not result in a broad impact on network structure of local neuronal circuits.

Loss of glutamate transporter eaat2a leads to aberrant neuronal excitability, recurrent epileptic seizures, and basal hypoactivity

Astroglial excitatory amino acid transporter 2 (EAAT2, GLT‐1, and SLC1A2) regulates the duration and extent of neuronal excitation by removing glutamate from the synaptic cleft. Hence, an impairment in EAAT2 function could lead to an imbalanced brain network excitability. Here, we investigated the functional alterations of neuronal and astroglial networks associated with the loss of function in the astroglia predominant eaat2a gene in zebrafish. We observed that eaat2a^−/− mutant zebrafish larvae display recurrent spontaneous and light‐induced seizures in neurons and astroglia, which coincide with an abrupt increase in extracellular glutamate levels. In stark contrast to this hyperexcitability, basal neuronal and astroglial activity was surprisingly reduced in eaat2a^−/− mutant animals, which manifested in decreased overall locomotion. Our results reveal an essential and mechanistic contribution of EAAT2a in balancing brain excitability, and its direct link to epileptic seizures.

Quantitative Confocal Microscopy for Grouping of Dose-Response Data: Deciphering Calcium Sequestration and Subsequent Cell Death in the Presence of Excess Norepinephrine

Fluorescent calcium (Ca²⁺) imaging is one of the preferred methods to record cellular activity during in vitro preclinical studies, high-content drug screening, and toxicity analysis. Visualization and analysis for dose-response data obtained using high-resolution imaging remain challenging, due to the inherent heterogeneity present in the Ca²⁺ spiking. To address this challenge, we propose measurement of cytosolic Ca²⁺ ions using spinning-disk confocal microscopy and machine learning-based analytics that is scalable. First, we implemented uniform manifold approximation and projection (UMAP) for visualizing the multivariate time-series dataset in the two-dimensional (2D) plane using Python. The dataset was obtained through live imaging experiments with norepinephrine-induced Ca²⁺ oscillation in HeLa cells for a large range of doses. Second, we demonstrate that the proposed framework can be used to depict the grouping of the spiking pattern for lower and higher drug doses. To the best of our knowledge, this is the first attempt at UMAP visualization of the time-series dose response and identification of the Ca²⁺ signature during lytic death. Such quantitative microscopy can be used as a component of a high-throughput data analysis workflow for toxicity analysis.

Direct extraction of signal and noise correlations from two-photon calcium imaging of ensemble neuronal activity

Neuronal activity correlations are key to understanding how populations of neurons collectively encode information. While two-photon calcium imaging has created a unique opportunity to record the activity of large populations of neurons, existing methods for inferring correlations from these data face several challenges. First, the observations of spiking activity produced by two-photon imaging are temporally blurred and noisy. Secondly, even if the spiking data were perfectly recovered via deconvolution, inferring network-level features from binary spiking data is a challenging task due to the non-linear relation of neuronal spiking to endogenous and exogenous inputs. In this work, we propose a methodology to explicitly model and directly estimate signal and noise correlations from two-photon fluorescence observations, without requiring intermediate spike deconvolution. We provide theoretical guarantees on the performance of the proposed estimator and demonstrate its utility through applications to simulated and experimentally recorded data from the mouse auditory cortex.

Near-infrared catecholamine nanosensors for high spatiotemporal dopamine imaging

Dopamine neuromodulation of neural synapses is a process implicated in a number of critical brain functions and diseases. Development of protocols to visualize this dynamic neurochemical process is essential to understanding how dopamine modulates brain function. We have developed a non-genetically encoded, near-IR (nIR) catecholamine nanosensor (nIRCat) capable of identifying ~2-µm dopamine release hotspots in dorsal striatal brain slices. nIRCat is readily synthesized through sonication of single walled carbon nanotubes with DNA oligos, can be readily introduced into both genetically tractable and intractable organisms and is compatible with a number of dopamine receptor agonists and antagonists. Here we describe the synthesis, characterization and implementation of nIRCat in acute mouse brain slices. We demonstrate how nIRCat can be used to image electrically or optogenetically stimulated dopamine release, and how these procedures can be leveraged to study the effects of dopamine receptor pharmacology. In addition, we provide suggestions for building or adapting wide-field microscopy to be compatible with nIRCat nIR fluorescence imaging. We discuss strategies for analyzing nIR video data to identify dopamine release hotspots and quantify their kinetics. This protocol can be adapted and implemented for imaging other neuromodulators by using probes of this class and can be used in a broad range of species without genetic manipulation. The synthesis and characterization protocols for nIRCat take ~5 h, and the preparation and fluorescence imaging of live brain slices by using nIRCats require ~6 h.

Extracting neuronal activity signals from microscopy recordings of contractile tissue using B-spline Explicit Active Surfaces (BEAS) cell tracking

Ca2+ imaging is a widely used microscopy technique to simultaneously study cellular activity in multiple cells. The desired information consists of cell-specific time series of pixel intensity values, in which the fluorescence intensity represents cellular activity. For static scenes, cellular signal extraction is straightforward, however multiple analysis challenges are present in recordings of contractile tissues, like those of the enteric nervous system (ENS). This layer of critical neurons, embedded within the muscle layers of the gut wall, shows optical overlap between neighboring neurons, intensity changes due to cell activity, and constant movement. These challenges reduce the applicability of classical segmentation techniques and traditional stack alignment and regions-of-interest (ROIs) selection workflows. Therefore, a signal extraction method capable of dealing with moving cells and is insensitive to large intensity changes in consecutive frames is needed. Here we propose a b-spline active contour method to delineate and track neuronal cell bodies based on local and global energy terms. We develop both a single as well as a double-contour approach. The latter takes advantage of the appearance of GCaMP expressing cells, and tracks the nucleus' boundaries together with the cytoplasmic contour, providing a stable delineation of neighboring, overlapping cells despite movement and intensity changes. The tracked contours can also serve as landmarks to relocate additional and manually-selected ROIs. This improves the total yield of efficacious cell tracking and allows signal extraction from other cell compartments like neuronal processes. Compared to manual delineation and other segmentation methods, the proposed method can track cells during large tissue deformations and high-intensity changes such as during neuronal firing events, while preserving the shape of the extracted Ca2+ signal. The analysis package represents a significant improvement to available Ca2+ imaging analysis workflows for ENS recordings and other systems where movement challenges traditional Ca2+ signal extraction workflows.

Comparative Effects of Event Detection Methods on the Analysis and Interpretation of Ca2+ Imaging Data

Calcium imaging has gained substantial popularity as a tool to profile the activity of multiple simultaneously active cells at high spatiotemporal resolution. Among the diverse approaches to processing of Ca²⁺ imaging data is an often subjective decision of how to quantify baseline fluorescence or F ₀. We examine the effect of popular F ₀ determination methods on the interpretation of neuronal and astrocyte activity in a single dataset of rats trained to self-administer intravenous infusions of cocaine and compare them with an F ₀-independent wavelet ridgewalking event detection approach. We find that the choice of the processing method has a profound impact on the interpretation of widefield imaging results. All of the dF/F ₀ thresholding methods tended to introduce spurious events and fragment individual transients, leading to smaller calculated event durations and larger event frequencies. Analysis of simulated datasets confirmed these observations and indicated substantial intermethod variability as to the events classified as significant. Additionally, most dF/F ₀ methods on their own were unable to adequately account for bleaching of fluorescence, although the F ₀ smooth approach and the wavelet ridgewalking algorithm both did so. In general, the choice of the processing method led to dramatically different quantitative and sometimes opposing qualitative interpretations of the effects of cocaine self-administration both at the level of individual cells and at the level of cell networks. Significantly different distributions of event duration, amplitude, frequency, and network measures were found across the majority of dF/F ₀ approaches. The wavelet ridgewalking algorithm broadly outperformed dF/F ₀-based methods for both neuron and astrocyte recordings. These results indicate the need for heightened awareness of the limitations and tendencies associated with decisions to use particular Ca²⁺ image processing pipelines. Both quantification and interpretation of the effects of experimental manipulations are strongly sensitive to such decisions.

Synaptic communication mediates the assembly of a self-organizing circuit that controls reproduction

Migration of gonadotropin-releasing hormone (GnRH) neurons from their birthplace in the nasal placode to their hypothalamic destination is critical for vertebrate reproduction and species persistence. While their migration mode as individual GnRH neurons has been extensively studied, the role of GnRH-GnRH cell communication during migration remains largely unexplored. Here, we show in awake zebrafish larvae that migrating GnRH neurons pause at the nasal-forebrain junction and form clusters that act as interhemisphere neuronal ensembles. Within the ensembles, GnRH neurons create an isolated, spontaneously active circuit that is internally wired through monosynaptic glutamatergic synapses into which newborn GnRH neurons integrate before entering the brain. This initial phase of integration drives a phenotypic switch, which is essential for GnRH neurons to properly migrate toward their hypothalamic destination. Together, these experiments reveal a critical step for reproduction, which depends on synaptic communication between migrating GnRH neurons.

Hypothalamic Dopamine Neurons Control Sensorimotor Behavior by Modulating Brainstem Premotor Nuclei in Zebrafish

Dopamine (DA)-producing neurons are critically involved in the production of motor behaviors in multiple circuits that are conserved from basal vertebrates to mammals. Although there is increasing evidence that DA neurons in the hypothalamus play a locomotor role, their precise contributions to behavior and the circuit mechanisms by which they are achieved remain unclear. Here, we demonstrate that tyrosine-hydroxylase-2-expressing (th2+) DA neurons in the zebrafish hypothalamus fire phasic bursts of activity to acutely promote swimming and modulate audiomotor behaviors on fast timescales. Their anatomy and physiology reveal two distinct functional DA modules within the hypothalamus. The first comprises an interconnected set of cerebrospinal-fluid-contacting DA nuclei surrounding the 3^rd ventricle, which lack distal projections outside of the hypothalamus and influence locomotion through unknown means. The second includes neurons in the preoptic nucleus, which send long-range projections to targets throughout the brain, including the mid- and hindbrain, where they activate premotor circuits involved in swimming and sensorimotor integration. These data suggest a broad regulation of motor behavior by DA neurons within multiple hypothalamic nuclei and elucidate a novel functional mechanism for the preoptic DA neurons in the initiation of movement.

Functional properties of habenular neurons are determined by developmental stage and sequential neurogenesis

The developing brain undergoes drastic alterations. Here, we investigated developmental changes in the habenula, a brain region that mediates behavioral flexibility during learning, social interactions, and aversive experiences. We showed that developing habenular circuits exhibit multiple alterations that lead to an increase in the structural and functional diversity of cell types, inputs, and functional modules. As the habenula develops, it sequentially transforms into a multisensory brain region that can process visual, olfactory, mechanosensory, and aversive stimuli. Moreover, we observed that the habenular neurons display spatiotemporally structured spontaneous activity that shows prominent alterations and refinement with age. These alterations in habenular activity are accompanied by sequential neurogenesis and the integration of distinct neural clusters across development. Last, we revealed that habenular neurons with distinct functional properties are born sequentially at distinct developmental time windows. Our results highlight a strong link between the functional properties of habenular neurons and their precise birthdate.

Neural Stem Cell Grafts Form Extensive Synaptic Networks that Integrate with Host Circuits after Spinal Cord Injury

Neural stem/progenitor cell (NSPC) grafts can integrate into sites of spinal cord injury (SCI) and generate neuronal relays across lesions that can provide functional benefit. To determine if and how grafts become synaptically organized and connect with host systems, we performed calcium imaging of NSPC grafts in SCI sites in vivo and in adult spinal cord slices. NSPC grafts organize into localized and spontaneously active synaptic networks. Optogenetic stimulation of host corticospinal tract axons regenerating into grafts elicited distinct and segregated neuronal network responses throughout the graft. Moreover, optogenetic stimulation of graft-derived axons extending from the graft into the denervated spinal cord also triggered local host neuronal network responses. In vivo imaging revealed that behavioral stimulation likewise elicited focal synaptic responses within grafts. Thus neural progenitor grafts can form functional synaptic subnetworks whose activity patterns resemble intact spinal cord.

NOSA, an Analytical Toolbox for Multicellular Optical Electrophysiology

Understanding how neural networks generate activity patterns and communicate with each other requires monitoring the electrical activity from many neurons simultaneously. Perfectly suited tools for addressing this challenge are genetically encoded voltage indicators (GEVIs) because they can be targeted to specific cell types and optically report the electrical activity of individual, or populations of neurons. However, analyzing and interpreting the data from voltage imaging experiments is challenging because high recording speeds and properties of current GEVIs yield only low signal-to-noise ratios, making it necessary to apply specific analytical tools. Here, we present NOSA (Neuro-Optical Signal Analysis), a novel open source software designed for analyzing voltage imaging data and identifying temporal interactions between electrical activity patterns of different origin. In this work, we explain the challenges that arise during voltage imaging experiments and provide hands-on analytical solutions. We demonstrate how NOSA's baseline fitting, filtering algorithms and movement correction can compensate for shifts in baseline fluorescence and extract electrical patterns from low signal-to-noise recordings. NOSA allows to efficiently identify oscillatory frequencies in electrical patterns, quantify neuronal response parameters and moreover provides an option for analyzing simultaneously recorded optical and electrical data derived from patch-clamp or other electrode-based recordings. To identify temporal relations between electrical activity patterns we implemented different options to perform cross correlation analysis, demonstrating their utility during voltage imaging in Drosophila and mice. All features combined, NOSA will facilitate the first steps into using GEVIs and help to realize their full potential for revealing cell-type specific connectivity and functional interactions.

Precision Calcium Imaging of Dense Neural Populations via a Cell-Body-Targeted Calcium Indicator

Methods for one-photon fluorescent imaging of calcium dynamics can capture the activity of hundreds of neurons across large fields of view at a low equipment complexity and cost. In contrast to two-photon methods, however, one-photon methods suffer from higher levels of crosstalk from neuropil, resulting in a decreased signal-to-noise ratio and artifactual correlations of neural activity. We address this problem by engineering cell-body-targeted variants of the fluorescent calcium indicators GCaMP6f and GCaMP7f. We screened fusions of GCaMP to natural, as well as artificial, peptides and identified fusions that localized GCaMP to within 50 μm of the cell body of neurons in mice and larval zebrafish. One-photon imaging of soma-targeted GCaMP in dense neural circuits reported fewer artifactual spikes from neuropil, an increased signal-to-noise ratio, and decreased artifactual correlation across neurons. Thus, soma-targeting of fluorescent calcium indicators facilitates usage of simple, powerful, one-photon methods for imaging neural calcium dynamics.

Real-Time Neuron Detection and Neural Signal Extraction Platform for Miniature Calcium Imaging

Real-time neuron detection and neural activity extraction are critical components of real-time neural decoding. In this paper, we propose a novel real-time neuron detection and activity extraction system using a dataflow framework to provide real-time performance and adaptability to new algorithms and hardware platforms. The proposed system was evaluated on simulated calcium imaging data, calcium imaging data with manual annotation, and calcium imaging data of the anterior lateral motor cortex. We found that the proposed system accurately detected neurons and extracted neural activities in real time without any requirement for expensive, cumbersome, or special-purpose computing hardware. We expect that the system will enable cost-effective, real-time calcium imaging-based neural decoding, leading to precise neuromodulation.

Advancing zebrafish as a model for studying developmental neurotoxicology

The cover photo shows the developing zebrafish nervous system at 5 days post-fertilization. Axon tracts are labeled with an anti-acetylated alpha tubulin antibody. The image, which was acquired on a Zeiss LSM 880 confocal microscope, is a maximum intensity projection of a z-stack that has been color-coded for depth. Major brain regions such as the olfactory bulb, forebrain, habenula, optic tectum, cerebellum, hindbrain, and eye are identifiable. This image is part of a study (Plavicki Lab, Brown University) focused on understanding the impact of toxicant exposures on brain development and activity with the goal of identifyingenvironmental factors that contribute to the etiology of neurodevelopmental disorders.

Organizing principles of whole-brain functional connectivity in zebrafish larvae

Network science has begun to reveal the fundamental principles by which large-scale brain networks are organized, including geometric constraints, a balance between segregative and integrative features, and functionally flexible brain areas. However, it remains unknown whether whole-brain networks imaged at the cellular level are organized according to similar principles. Here, we analyze whole-brain functional networks reconstructed from calcium imaging data recorded in larval zebrafish. Our analyses reveal that functional connections are distance-dependent and that networks exhibit hierarchical modular structure and hubs that span module boundaries. We go on to show that spontaneous network structure places constraints on stimulus-evoked reconfigurations of connections and that networks are highly consistent across individuals. Our analyses reveal basic organizing principles of whole-brain functional brain networks at the mesoscale. Our overarching methodological framework provides a blueprint for studying correlated activity at the cellular level using a low-dimensional network representation. Our work forms a conceptual bridge between macro- and mesoscale network neuroscience and opens myriad paths for future studies to investigate network structure of nervous systems at the cellular level.

Dynamic Tracking Algorithm for Time-Varying Neuronal Network Connectivity using Wide-Field Optical Image Video Sequences

Propagation of signals between neurons and brain regions provides information about the functional properties of neural networks, and thus information transfer. Advances in optical imaging and statistical analyses of acquired optical signals have yielded various metrics for inferring neural connectivity, and hence for mapping signal intercorrelation. However, a single coefficient is traditionally derived to classify the connection strength between two cells, ignoring the fact that neural systems are inherently time-variant systems. To overcome these limitations, we utilized a time-varying Pearson's correlation coefficient, spike-sorting, wavelet transform, and wavelet coherence of calcium transients from DIV 12-15 hippocampal neurons from GCaMP6s mice after applying various concentrations of glutamate. Results provide a comprehensive overview of resulting firing patterns, network connectivity, signal directionality, and network properties. Together, these metrics provide a more comprehensive and robust method of analyzing transient neural signals, and enable future investigations for tracking the effects of different stimuli on network properties.

CALIMA: The semi-automated open-source calcium imaging analyzer

BACKGROUND AND OBJECTIVE

Ever since its discovery, calcium imaging has proven its worth in discovering new insights into the mechanisms of cellular communication. Yet, the analysis of the data generated by calcium imaging experiments demands a large amount of time from researchers. Tools enabling automated and semi-automated analysis are available, but often they allow automating only a part of the data analysis process. Therefore, we developed CALIMA (https://aethelraed.nl/calima), a free and open-source standalone software tool that provides an opportunity to quickly detect cells, to obtain the calcium spikes, and to determine the underlying network structure of neuronal cell cultures.

METHODS

Owing to the difference of Gaussians algorithm applied for the cell detection, CALIMA is able to detect regions of interest (ROIs) quickly. The z-scoring algorithm provides a means to set the requirements for spike detection, and the neuronal connections can be reconstructed by analyzing the cross-correlation between the cellular activity. We evaluated CALIMA's reliability, speed, and functionality with a special focus on neuronal cell detection and network reconstruction. The evaluation was performed by using real-life data such as a known example dataset (cultured primary rat cortical neurons, University of Pennsylvania) and by analyzing video graphic footage of in vitro brain cell samples (SH-SY5Y neuroblastoma cultures, one sample with synchronous neuron firing). The obtained results were compared to the corresponding outcomes observed on same datasets for other similar software solutions. Moreover, we compared the results of segmentation and peak detection analysis, the ones obtained using CALIMA and those acquired manually.

RESULTS

CALIMA was able to detect the cells in the cultures within seconds. The average sensitivity was 82% across the datasets checked, comparing favorably with the alternative software solutions. Using the correct parameters, CALIMA's Ca-spikes detection sensitivity reached 96%. Lastly, neuronal networks were reconstructed by combining the data on the ROI's activity and the cell's positions, finding the most likely inter-cell connections.

CONCLUSIONS

We found that CALIMA proved to be a robust and fast tool to analyze the data of experiments for the digital reconstruction of the neuronal cellular network while being able to process the analysis steps with minimal user input required and in a time efficient manner.

Imaging and analysis of genetically encoded calcium indicators linking neural circuits and behaviors

Confirming the direct link between neural circuit activity and animal behavior has been a principal aim of neuroscience. The genetically encoded calcium indicator (GECI), which binds to calcium ions and emits fluorescence visualizing intracellular calcium concentration, enables detection of in vivo neuronal firing activity. Various GECIs have been developed and can be chosen for diverse purposes. These GECI-based signals can be acquired by several tools including two-photon microscopy and microendoscopy for precise or wide imaging at cellular to synaptic levels. In addition, the images from GECI signals can be analyzed with open source codes including constrained non-negative matrix factorization for endoscopy data (CNMF_E) and miniscope 1-photon-based calcium imaging signal extraction pipeline (MIN1PIPE), and considering parameters of the imaged brain regions (e.g., diameter or shape of soma or the resolution of recorded images), the real-time activity of each cell can be acquired and linked with animal behaviors. As a result, GECI signal analysis can be a powerful tool for revealing the functions of neuronal circuits related to specific behaviors.

Engineering brain activity patterns by neuromodulator polytherapy for treatment of disorders

Conventional drug screens and treatments often ignore the underlying complexity of brain network dysfunctions, resulting in suboptimal outcomes. Here we ask whether we can correct abnormal functional connectivity of the entire brain by identifying and combining multiple neuromodulators that perturb connectivity in complementary ways. Our approach avoids the combinatorial complexity of screening all drug combinations. We develop a high-speed platform capable of imaging more than 15000 neurons in 50ms to map the entire brain functional connectivity in large numbers of vertebrates under many conditions. Screening a panel of drugs in a zebrafish model of human Dravet syndrome, we show that even drugs with related mechanisms of action can modulate functional connectivity in significantly different ways. By clustering connectivity fingerprints, we algorithmically select small subsets of complementary drugs and rapidly identify combinations that are significantly more effective at correcting abnormal networks and reducing spontaneous seizures than monotherapies, while minimizing behavioral side effects. Even at low concentrations, our polytherapy performs superior to individual drugs even at highest tolerated concentrations.

Brain disorders are associated with network dysfunctions that are not addressed by conventional drug screens. Here, the authors use high-throughput functional imaging of brain activity in zebrafish larvae to study the effects of individual drugs on network connectivity and demonstrate an algorithm that predicts the most effective drug combinations to normalize both the activity patterns and the animal behavior.