93 research outputs found
Topography of the complete corticopontine projection: From experiments to principal Maps
The mammalian brain is characterized by orderly spatial distribution of its cellular components, commonly referred to as topographical organization. The topography of cortical and subcortical maps is thought to represent functional or computational properties. In the present investigation, we have studied map transformations and organizing principles in the projections from the cerebral cortex to the pontine nuclei, with emphasis on the mapping of the cortex as a whole onto the pontine nuclei. Following single or multiple axonal tracer injections into different cortical regions, three-dimensional (3-D) distributions of anterogradely labeled axons in the pontine nuclei were mapped. All 3-D reconstructed data sets were normalized to a standardized local coordinate system for the pontine nuclei and uploaded in a database application (FACCS, Functional Anatomy of the Cerebro-Cerebellar System, available via The Rodent Brain Workbench, http://www.rbwb.org). The database application allowed flexible use of the data in novel combinations, and use of a previously published data sets. Visualization of different combinations of data was used to explore alternative principles of organization. As a result of these analyses, a principal map of the topography of corticopontine projections was developed. This map followed the organization of early spatiotemporal gradients present in the cerebral cortex and the pontine nuclei. With the principal map for corticopontine projections, a fairly accurate prediction of pontine target area can be made for any site of origin in the cerebral cortex. The map and the underlying shared data sets represent a basis for modeling of topographical organization and structure–function relationships in this system
Mapping the Connectome: Multi-Level Analysis of Brain Connectivity
Background and scope The brain contains vast numbers of interconnected neurons that constitute anatomical and functional networks. Structural descriptions of neuronal network elements and connections make up the “connectome ” of the brain (Hagmann, 2005; Sporns et al., 2005; Sporns, 2011), and are important for understanding normal brain function and disease-related dysfunction. A long-standing ambition of the neuroscience community has been to achieve complete connectome maps for the human brain as well as the brains of non-human primates, rodents, and other species (Bohland et al., 2009; Hagmann et al., 2010; Van Essen and Ugurbil, 2012). A wide repertoire of experimental tools is currently available to map neural connectivity at multiple levels, from the tracing of mesoscopic axonal connections and the delineation of white matter tracts (Saleem et al., 2002; Van der Linden et al., 2002; Sporns et al., 2005; Schmahmann et al., 2007; Hagmann et al., 2010), the mappin
Digital Atlas of Anatomical Subdivisions and Boundaries of the Rat Hippocampal Region
The rat hippocampal region is frequently studied in relation to learning and memory processes and brain diseases. The region is complex, consisting of multiple subdivisions that are challenging to delineate anatomically. Published atlases of the rat brain typically lack the underlying histological criteria necessary to identify boundaries, and textbooks descriptions of the region are often inadequately illustrated and thus difficult to relate to experimental data. An overview of both anatomical features and criteria used to delineate boundaries is required to assign location to experimental material from the hippocampal region. To address this issue, we have developed a web-based atlas application in which images of histological sections are integrated with new and up-to-date criteria for subdividing the rat hippocampus formation, fasciola, and associated parahippocampal regions. The atlas application consists of an interactive image viewer with high-resolution images of an extensive series of sections stained for NeuN, calbindin, and parvalbumin, and an index of structures with detailed descriptions of the criteria used to define the boundaries. Images can be inspected with a graphical overlay of selected subregions. Bi-directional links between images and the index of structures are provided. In summary, we provide a novel content-rich digital atlas resource facilitating identification of morphological features relevant for delineating the anatomical subdivisions of the rat hippocampal region. The atlas application is available at http://www.rbwb.org
Three-Dimensional Atlas System for Mouse and Rat Brain Imaging Data
Tomographic neuroimaging techniques allow visualization of functionally and structurally specific signals in the mouse and rat brain. The interpretation of the image data relies on accurate determination of anatomical location, which is frequently obstructed by the lack of structural information in the data sets. Positron emission tomography (PET) generally yields images with low spatial resolution and little structural contrast, and many experimental magnetic resonance imaging (MRI) paradigms give specific signal enhancements but often limited anatomical information. Side-by-side comparison of image data with conventional atlas diagram is hampered by the 2-D format of the atlases, and by the lack of an analytical environment for accumulation of data and integrative analyses. We here present a method for reconstructing 3-D atlases from digital 2-D atlas diagrams, and exemplify 3-D atlas-based analysis of PET and MRI data. The reconstruction procedure is based on two seminal mouse and brain atlases, but is applicable to any stereotaxic atlas. Currently, 30 mouse brain structures and 60 rat brain structures have been reconstructed. To exploit the 3-D atlas models, we have developed a multi-platform atlas tool (available via The Rodent Workbench, http://rbwb.org) which allows combined visualization of experimental image data within the 3-D atlas space together with 3-D viewing and user-defined slicing of selected atlas structures. The tool presented facilitates assignment of location and comparative analysis of signal location in tomographic images with low structural contrast
Navigating the Murine Brain: Toward Best Practices for Determining and Documenting Neuroanatomical Locations in Experimental Studies
In experimental neuroscientific research, anatomical location is a key attribute of experimental observations and critical for interpretation of results, replication of findings, and comparison of data across studies. With steadily rising numbers of publications reporting basic experimental results, there is an increasing need for integration and synthesis of data. Since comparison of data relies on consistently defined anatomical locations, it is a major concern that practices and precision in the reporting of location of observations from different types of experimental studies seem to vary considerably. To elucidate and possibly meet this challenge, we have evaluated and compared current practices for interpreting and documenting the anatomical location of measurements acquired from murine brains with different experimental methods. Our observations show substantial differences in approach, interpretation and reproducibility of anatomical locations among reports of different categories of experimental research, and strongly indicate that ambiguous reports of anatomical location can be attributed to missing descriptions. Based on these findings, we suggest a set of minimum requirements for documentation of anatomical location in experimental murine brain research. We furthermore demonstrate how these requirements have been applied in the EU Human Brain Project to optimize workflows for integration of heterogeneous data in common reference atlases. We propose broad adoption of some straightforward steps for improving the precision of location metadata and thereby facilitating interpretation, reuse and integration of data
A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility
There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body
Workflow and Atlas System for Brain-Wide Mapping of Axonal Connectivity in Rat
Detailed knowledge about the anatomical organization of axonal connections is important for understanding normal functions of brain systems and disease-related dysfunctions. Such connectivity data are typically generated in neuroanatomical tract-tracing experiments in which specific axonal connections are visualized in histological sections. Since journal publications typically only accommodate restricted data descriptions and example images, literature search is a cumbersome way to retrieve overviews of brain connectivity. To explore more efficient ways of mapping, analyzing, and sharing detailed axonal connectivity data from the rodent brain, we have implemented a workflow for data production and developed an atlas system tailored for online presentation of axonal tracing data. The system is available online through the Rodent Brain WorkBench (www.rbwb.org; Whole Brain Connectivity Atlas) and holds experimental metadata and high-resolution images of histological sections from experiments in which axonal tracers were injected in the primary somatosensory cortex. We here present the workflow and the data system, and exemplify how the online image repository can be used to map different aspects of the brain-wide connectivity of the rat primary somatosensory cortex, including not only presence of connections but also morphology, densities, and spatial organization. The accuracy of the approach is validated by comparing results generated with our system with findings reported in previous publications. The present study is a contribution to a systematic mapping of rodent brain connections and represents a starting point for further large-scale mapping efforts
Recommendations and guidelines from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 -- In vivo small-animal imaging
The value of in vivo preclinical diffusion MRI (dMRI) is substantial.
Small-animal dMRI has been used for methodological development and validation,
characterizing the biological basis of diffusion phenomena, and comparative
anatomy. Many of the influential works in this field were first performed in
small animals or ex vivo samples. The steps from animal setup and monitoring,
to acquisition, analysis, and interpretation are complex, with many decisions
that may ultimately affect what questions can be answered using the data. This
work aims to serve as a reference, presenting selected recommendations and
guidelines from the diffusion community, on best practices for preclinical dMRI
of in vivo animals. In each section, we also highlight areas for which no
guidelines exist (and why), and where future work should focus. We first
describe the value that small animal imaging adds to the field of dMRI,
followed by general considerations and foundational knowledge that must be
considered when designing experiments. We briefly describe differences in
animal species and disease models and discuss how they are appropriate for
different studies. We then give guidelines for in vivo acquisition protocols,
including decisions on hardware, animal preparation, imaging sequences and data
processing, including pre-processing, model-fitting, and tractography. Finally,
we provide an online resource which lists publicly available preclinical dMRI
datasets and software packages, to promote responsible and reproducible
research. An overarching goal herein is to enhance the rigor and
reproducibility of small animal dMRI acquisitions and analyses, and thereby
advance biomedical knowledge.Comment: 69 pages, 6 figures, 1 tabl
Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain
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