Software and pipelines for registration and analyses of rodent brain image data in reference atlas space.

IF 2.5 4区 医学 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in Neuroinformatics Pub Date : 2025-09-24 eCollection Date: 2025-01-01 DOI:10.3389/fninf.2025.1629388
Maja A Puchades, Sharon C Yates, Gergely Csucs, Harry Carey, Arda Balkir, Trygve B Leergaard, Jan G Bjaalie
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引用次数: 0

Abstract

Advancements in methodologies for efficient large-scale acquisition of high-resolution serial microscopy image data have opened new possibilities for experimental studies of cellular and subcellular features across whole brains in animal models. There is a high demand for open-source software and workflows for automated or semi-automated analysis of such data, facilitating anatomical, functional, and molecular mapping in healthy and diseased brains. These studies share a common need to consistently identify, visualize, and quantify the location of observations within anatomically defined regions, ensuring reproducible interpretation of anatomical locations, and thereby allowing meaningful comparisons of results across multiple independent studies. Addressing this need, we have developed a suite of desktop and web-applications for registration of serial brain section images to three-dimensional brain reference atlases (QuickNII, VisuAlign, WebAlign, WebWarp, and DeepSlice) and for performing data analysis in a spatial context provided by an atlas (Nutil, QCAlign, SeriesZoom, LocaliZoom, and MeshView). The software can be utilized in various combinations, creating customized analytical pipelines suited to specific research needs. The web-applications are integrated in the EBRAINS research infrastructure and coupled to the EBRAINS data platform, establishing the foundation for an online analytical workbench. We here present our software ecosystem, exemplify its use by the research community, and discuss possible directions for future developments.

参考地图集空间中啮齿类动物脑图像数据配准和分析的软件和管道。
高效大规模获取高分辨率串行显微镜图像数据的方法的进步,为动物模型中全脑细胞和亚细胞特征的实验研究开辟了新的可能性。对这些数据的自动化或半自动分析的开源软件和工作流程有很高的需求,有助于在健康和患病的大脑中进行解剖、功能和分子定位。这些研究都有一个共同的需求,即在解剖学定义的区域内一致地识别、可视化和量化观察到的位置,确保解剖位置的可重复性解释,从而允许在多个独立研究中对结果进行有意义的比较。为了满足这一需求,我们开发了一套桌面和web应用程序,用于将串行脑剖面图像注册到三维脑参考地图集(QuickNII, VisuAlign, WebAlign, WebWarp和DeepSlice),并用于在地图集提供的空间环境中执行数据分析(Nutil, QCAlign, SeriesZoom, LocaliZoom和MeshView)。该软件可以在各种组合中使用,创建适合特定研究需求的定制分析管道。web应用程序集成在EBRAINS研究基础设施中,并与EBRAINS数据平台耦合,为在线分析工作台奠定了基础。我们在这里展示了我们的软件生态系统,举例说明了它在研究社区中的应用,并讨论了未来发展的可能方向。
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来源期刊
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics MATHEMATICAL & COMPUTATIONAL BIOLOGY-NEUROSCIENCES
CiteScore
4.80
自引率
5.70%
发文量
132
审稿时长
14 weeks
期刊介绍: Frontiers in Neuroinformatics publishes rigorously peer-reviewed research on the development and implementation of numerical/computational models and analytical tools used to share, integrate and analyze experimental data and advance theories of the nervous system functions. Specialty Chief Editors Jan G. Bjaalie at the University of Oslo and Sean L. Hill at the École Polytechnique Fédérale de Lausanne are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Neuroscience is being propelled into the information age as the volume of information explodes, demanding organization and synthesis. Novel synthesis approaches are opening up a new dimension for the exploration of the components of brain elements and systems and the vast number of variables that underlie their functions. Neural data is highly heterogeneous with complex inter-relations across multiple levels, driving the need for innovative organizing and synthesizing approaches from genes to cognition, and covering a range of species and disease states. Frontiers in Neuroinformatics therefore welcomes submissions on existing neuroscience databases, development of data and knowledge bases for all levels of neuroscience, applications and technologies that can facilitate data sharing (interoperability, formats, terminologies, and ontologies), and novel tools for data acquisition, analyses, visualization, and dissemination of nervous system data. Our journal welcomes submissions on new tools (software and hardware) that support brain modeling, and the merging of neuroscience databases with brain models used for simulation and visualization.
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