一个标准化的开放科学框架,用于共享和重新分析连续感官刺激获得的神经数据。

ArXiv Pub Date : 2024-09-16
Giovanni M Di Liberto, Aaron Nidiffer, Michael J Crosse, Nathaniel J Zuk, Stephanie Haro, Giorgia Cantisani, Martin M Winchester, Aoife Igoe, Ross McCrann, Satwik Chandra, Edmund C Lalor, Giacomo Baruzzo
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引用次数: 0

摘要

神经生理学研究表明,在涉及连续感觉流的场景(如语音和音乐聆听)中研究感觉处理是可能的,也是有价值的。在过去10年左右的时间里,用于分析连续感觉流的神经处理的新分析框架,加上对数据共享的日益参与,导致了涉及连续感觉实验的公开可用数据集的激增。然而,这一研究领域的开放科学努力仍然分散,缺乏一套连贯的指导方针。因此,可以获得许多数据格式和分析工具包,研究之间的兼容性有限或没有兼容性。本文提出了一个端到端的开放科学框架,用于存储、分析、共享和重新分析连续感官实验中记录的神经数据。该框架被设计为易于与现有工具箱(例如,EelBrain、NapLib、MNE、mTRF Toolbox)对接。我们通过用户视图(如何加载和快速重新分析现有数据)和实验者视图(如何存储、分析和共享)来提供指导方针。此外,我们还引入了一个基于web的数据浏览器,可以轻松复制已发布的结果和数据重新分析。在这样做的过程中,我们的目标是促进数据共享,促进透明的研究实践,同时让所有用户都能尽可能直接和方便地了解这一过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A standardised open science framework for sharing and re-analysing neural data acquired to continuous stimuli.

A standardised open science framework for sharing and re-analysing neural data acquired to continuous stimuli.

A standardised open science framework for sharing and re-analysing neural data acquired to continuous stimuli.

A standardised open science framework for sharing and re-analysing neural data acquired to continuous stimuli.

Neurophysiology research has demonstrated that it is possible and valuable to investigate sensory processing in scenarios involving continuous sensory streams, such as speech and music. Over the past 10 years or so, novel analytic frameworks combined with the growing participation in data sharing has led to a surge of publicly available datasets involving continuous sensory experiments. However, open science efforts in this domain of research remain scattered, lacking a cohesive set of guidelines. This paper presents an end-to-end open science framework for the storage, analysis, sharing, and re-analysis of neural data recorded during continuous sensory experiments. We propose a data structure that builds on existing custom structures (Continuous-event Neural Data or CND), providing precise naming conventions and data types, as well as a workflow for storing and loading data in the general-purpose BIDS structure. The framework has been designed to interface with existing EEG/MEG analysis toolboxes, such as Eelbrain, NAPLib, MNE, and mTRF-Toolbox. We present guidelines by taking both the user view (rapidly re-analyse existing data) and the experimenter view (store, analyse, and share), making the process straightforward and accessible. Additionally, we introduce a web-based data browser that enables the effortless replication of published results and data re-analysis.

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