Neuroimaging research requires sophisticated tools for analyzing complex data, but efficiently leveraging these tools can be a major challenge, especially on large datasets. CBRAIN is a web-based platform designed to simplify the use and accessibility of neuroimaging research tools for large-scale, collaborative studies. In this paper, we describe how CBRAIN’s unique features and infrastructure were leveraged to integrate TAPAS PhysIO, an open-source MATLAB toolbox for physiological noise modeling in fMRI data. This case study highlights three key elements of CBRAIN’s infrastructure that enable streamlined, multimodal tool integration: a user-friendly GUI, a Brain Imaging Data Structure (BIDS) data-entry schema, and convenient in-browser visualization of results. By incorporating PhysIO into CBRAIN, we achieved significant improvements in the speed, ease of use, and scalability of physiological preprocessing. Researchers now have access to a uniform and intuitive interface for analyzing data, which facilitates remote and collaborative evaluation of results. With these improvements, CBRAIN aims to become an essential open-science tool for integrative neuroimaging research, supporting FAIR principles and enabling efficient workflows for complex analysis pipelines.

中文翻译：

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基于网络的 fMRI 生理噪声处理：在 CBRAIN 中添加 PhysIO 工具箱

神经影像研究需要复杂的工具来分析复杂的数据，但有效利用这些工具可能是一个重大挑战，尤其是在大型数据集上。CBRAIN 是一个基于网络的平台，旨在简化大规模协作研究的神经影像研究工具的使用和可访问性。在本文中，我们描述了如何利用 CBRAIN 的独特功能和基础设施来集成 TAPAS PhysIO，这是一个用于 fMRI 数据中生理噪声建模的开源 MATLAB 工具箱。本案例研究重点介绍了 CBRAIN 基础设施的三个关键要素，这些要素可实现简化的多模式工具集成：用户友好的 GUI、脑成像数据结构 (BIDS) 数据输入模式以及方便的浏览器内结果可视化。通过将 PhysIO 整合到 CBRAIN 中，我们在生理预处理的速度、易用性和可扩展性方面取得了显着改进。研究人员现在可以使用统一且直观的界面来分析数据，这有助于对结果进行远程协作评估。通过这些改进，CBRAIN 旨在成为综​​合神经影像研究的重要开放科学工具，支持 FAIR 原则并为复杂的分析流程提供高效的工作流程。