Prepontine non-giant neurons drive flexible escape behavior in zebrafish

Many species execute ballistic escape reactions to avoid imminent danger. Despite fast reaction times, responses are often highly regulated, reflecting a trade-off between costly motor actions and perceived threat level. However, how sensory cues are integrated within premotor escape circuits remains poorly understood. Here, we show that in zebrafish, less precipitous threats elicit a delayed escape, characterized by flexible trajectories, which are driven by a cluster of 38 prepontine neurons that are completely separate from the fast escape pathway. Whereas neurons that initiate rapid escapes receive direct auditory input and drive motor neurons, input and output pathways for delayed escapes are indirect, facilitating integration of cross-modal sensory information. These results show that rapid decision-making in the escape system is enabled by parallel pathways for ballistic responses and flexible delayed actions and defines a neuronal substrate for hierarchical choice in the vertebrate nervous system

Assembling models of embryo development: Image analysis and the construction of digital atlases

Digital atlases of animal development provide a quantitative description of morphogenesis, opening the path toward processes modeling. Prototypic atlases offer a data integration framework where to gather information from cohorts of individuals with phenotypic variability. Relevant information for further theoretical reconstruction includes measurements in time and space for cell behaviors and gene expression. The latter as well as data integration in a prototypic model, rely on image processing strategies. Developing the tools to integrate and analyze biological multidimensional data are highly relevant for assessing chemical toxicity or performing drugs preclinical testing. This article surveys some of the most prominent efforts to assemble these prototypes, categorizes them according to salient criteria and discusses the key questions in the field and the future challenges toward the reconstruction of multiscale dynamics in model organisms

A Three-Dimensional Stereotaxic MRI Brain Atlas of the Cichlid Fish Oreochromis mossambicus

The African cichlid Oreochromis mossambicus (Mozambique tilapia) has been used as a model system in a wide range of behavioural and neurobiological studies. The increasing number of genetic tools available for this species, together with the emerging interest in its use for neurobiological studies, increased the need for an accurate hodological mapping of the tilapia brain to supplement the available histological data. The goal of our study was to elaborate a three-dimensional, high-resolution digital atlas using magnetic resonance imaging, supported by Nissl staining. Resulting images were viewed and analysed in all orientations (transverse, sagittal, and horizontal) and manually labelled to reveal structures in the olfactory bulb, telencephalon, diencephalon, optic tectum, and cerebellum. This high resolution tilapia brain atlas is expected to become a very useful tool for neuroscientists using this fish model and will certainly expand their use in future studies regarding the central nervous system.Fundação para a Ciência e a Tecnologia grant: (PTDC/PSI/71811/2006); FCT PhD fellowships: (SFRH/BD/40976/2007, SFRH/BD/44848/2008); Plurianual Programme R&D: (unit MAR-LVT-Lisboa-331)

Inferring spatial and signaling relationships between cells from single cell transcriptomic data.

Single-cell RNA sequencing (scRNA-seq) provides details for individual cells; however, crucial spatial information is often lost. We present SpaOTsc, a method relying on structured optimal transport to recover spatial properties of scRNA-seq data by utilizing spatial measurements of a relatively small number of genes. A spatial metric for individual cells in scRNA-seq data is first established based on a map connecting it with the spatial measurements. The cell-cell communications are then obtained by "optimally transporting" signal senders to target signal receivers in space. Using partial information decomposition, we next compute the intercellular gene-gene information flow to estimate the spatial regulations between genes across cells. Four datasets are employed for cross-validation of spatial gene expression prediction and comparison to known cell-cell communications. SpaOTsc has broader applications, both in integrating non-spatial single-cell measurements with spatial data, and directly in spatial single-cell transcriptomics data to reconstruct spatial cellular dynamics in tissues

The INCF Digital Atlasing Program: Report on Digital Atlasing Standards in the Rodent Brain

The goal of the INCF Digital Atlasing Program is to provide the vision and direction necessary to make the rapidly growing collection of multidimensional data of the rodent brain (images, gene expression, etc.) widely accessible and usable to the international research community. This Digital Brain Atlasing Standards Task Force was formed in May 2008 to investigate the state of rodent brain digital atlasing, and formulate standards, guidelines, and policy recommendations.

Our first objective has been the preparation of a detailed document that includes the vision and specific description of an infrastructure, systems and methods capable of serving the scientific goals of the community, as well as practical issues for achieving
the goals. This report builds on the 1st INCF Workshop on Mouse and Rat Brain Digital Atlasing Systems (Boline et al., 2007, _Nature Preceedings_, doi:10.1038/npre.2007.1046.1) and includes a more detailed analysis of both the current state and desired state of digital atlasing along with specific recommendations for achieving these goals

Enhanced characterization of the zebrafish brain as revealed by super-resolution track-density imaging

In this study, we explored the use of super-resolution track-density imaging (TDI) for neuroanatomical characterization of the adult zebrafish brain. We compared the quality of image contrast and resolution obtained with T-2* magnetic resonance imaging (MRI), diffusion tensor-based imaging (DTI), TDI, and histology. The anatomical structures visualized in 5 mu m TDI maps corresponded with histology. Moreover, the super-resolution property and the local-directional information provided by directionally encoded color TDI facilitated delineation of a larger number of brain regions, commissures and small white matter tracks when compared to conventional MRI and DTI. In total, we were able to visualize 17 structures that were previously unidentifiable using MR microimaging, such as the four layers of the optic tectum. This study demonstrates the use of TDI for characterization of the adult zebrafish brain as a pivotal tool for future phenotypic examination of transgenic models of neurological diseases

FishNet: an online database of zebrafish anatomy

Background: Over the last two decades, zebrafish have been established as a genetically versatile model system for investigating many different aspects of vertebrate developmental biology. With the credentials of zebrafish as a developmental model now well recognized, the emerging new opportunity is the wider application of zebrafish biology to aspects of human disease modelling. This rapidly increasing use of zebrafish as a model for human disease has necessarily generated interest in the anatomy of later developmental phases such as the larval, juvenile, and adult stages, during which many of the key aspects of organ morphogenesis and maturation take place. Anatomical resources and references that encompass these stages are non-existent in zebrafish and there is therefore an urgent need to understand how different organ systems and anatomical structures develop throughout the life of the fish. Results: To overcome this deficit we have utilized the technique of optical projection tomography to produce three-dimensional (3D) models of larval fish. In order to view and display these models we have created FishNet http://www.fishnet.org.au, an interactive reference of zebrafish anatomy spanning the range of zebrafish development from 24 h until adulthood. Conclusion: FishNet contains more than 36 000 images of larval zebrafish, with more than 1 500 of these being annotated. The 3D models can be manipulated on screen or virtually sectioned. This resource represents the first complete embryo to adult atlas for any species in 3D

Reduction of the ATPase inhibitory factor 1 (IF1) leads to visual impairment in vertebrates

In vertebrates, mitochondria are tightly preserved energy producing organelles, which sustain nervous system development and function. The understanding of proteins that regulate their homoeostasis in complex animals is therefore critical and doing so via means of systemic analysis pivotal to inform pathophysiological conditions associated with mitochondrial deficiency. With the goal to decipher the role of the ATPase inhibitory factor 1 (IF1) in brain development, we employed the zebrafish as elected model reporting that the Atpif1a−/− zebrafish mutant, pinotage (pnttq209), which lacks one of the two IF1 paralogous, exhibits visual impairment alongside increased apoptotic bodies and neuroinflammation in both brain and retina. This associates with increased processing of the dynamin-like GTPase optic atrophy 1 (OPA1), whose ablation is a direct cause of inherited optic atrophy. Defects in vision associated with the processing of OPA1 are specular in Atpif1−/− mice thus confirming a regulatory axis, which interlinks IF1 and OPA1 in the definition of mitochondrial fitness and specialised brain functions. This study unveils a functional relay between IF1 and OPA1 in central nervous system besides representing an example of how the zebrafish model could be harnessed to infer the activity of mitochondrial proteins during development

Understanding Neural Pathways in Zebrafish through Deep Learning and High Resolution Electron Microscope Data

The tracing of neural pathways through large volumes of image data is an incredibly tedious and time-consuming process that significantly encumbers progress in neuroscience. We are exploring deep learning's potential to automate segmentation of high-resolution scanning electron microscope (SEM) image data to remove that barrier. We have started with neural pathway tracing through 5.1GB of whole-brain serial-section slices from larval zebrafish collected by the Center for Brain Science at Harvard University. This kind of manual image segmentation requires years of careful work to properly trace the neural pathways in an organism as small as a zebrafish larva (approximately 5mm in total body length). In automating this process, we would vastly improve productivity, leading to faster data analysis and breakthroughs in understanding the complexity of the brain. We will build upon prior attempts to employ deep learning for automatic image segmentation extending methods for unconventional deep learning data.Comment: 8 pages, 5 figures (1a to 5c), PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US