Neuroline：用于 FAIR 多模态神经生理学数据处理的集成模块化流程
Neuroline: an integrated modular pipeline for FAIR multimodal neurophysiology data processing
在系统神经科学中，采用 FAIR 原则进行代码和数据共享受到数据集规模和多样性、数据格式繁多以及分析工作流复杂性的阻碍。这些挑战促使了各种数据标准以及针对特定模态的处理和分析工具的发展。然而，将源自最先进神经生理学实验的多样化已处理数据流整合为一种通用格式仍然困难，而这对于跨模态分析和开放、FAIR 的数据共享至关重要。为解决这一问题，我们开发了 Neuroline，这是一个用于处理神经生理学数据（电生理学、光学成像和行为）的 Python 包，它在单一流程中结合了多模态整合、模块化和标准化输出。它利用已有的软件包，并将所得的已处理数据整合为标准化的 Neurodata Without Borders（NWB）格式。Neuroline 提供了统一的接口，同时保持了灵活性和可扩展性。在此，我们描述了一个能够整合不同类型神经科学数据和软件包的流程的实现及其挑战。最后，我们讨论了 Neuroline 如何促进神经科学数据和软件的可持续性与可及性。
把电生理、光学成像和行为数据整合进同一条模块化流程并统一输出为 NWB，方便跨模态分析与共享。
The adoption of FAIR principles for code and data sharing in systems neuroscience is hindered by the size and diversity of datasets, the multitude of data formats and the complexity of analysis workflows. These challenges have led to the development of various data standards and modality-specific processing and analysis tools. However, it remains difficult to integrate the diverse processed data streams originating from state-of-the-art neurophysiology experiments into a common format, which is crucial for cross-modal analyses and open, FAIR sharing of data. To address this, we developed Neuroline, a Python package for processing neurophysiology data (electrophysiology, optical imaging, and behaviour) that combines multimodal integration, modularity, and standardised output within a single pipeline. It leverages established packages and consolidates the resulting processed data into the standardised Neurodata Without Borders (NWB) format. Neuroline provides a unified interface while preserving flexibility and extensibility. Here we describe the implementation and challenges of a pipeline capable of integrating different types of neuroscientific data and packages. Finally, we address how Neuroline contributes to the sustainability and accessibility of neuroscience data and software.
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来源：bioRxiv · Neuroscience · biorxiv.org