Review Paper: Reporting Practices for Task fMRI Studies.

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Freya Acar, Camille Maumet, Talia Heuten, Maya Vervoort, Han Bossier, Ruth Seurinck, Beatrijs Moerkerke
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引用次数: 1

Abstract

What are the standards for the reporting methods and results of fMRI studies, and how have they evolved over the years? To answer this question we reviewed 160 papers published between 2004 and 2019. Reporting styles for methods and results of fMRI studies can differ greatly between published studies. However, adequate reporting is essential for the comprehension, replication and reuse of the study (for instance in a meta-analysis). To aid authors in reporting the methods and results of their task-based fMRI study the COBIDAS report was published in 2016, which provides researchers with clear guidelines on how to report the design, acquisition, preprocessing, statistical analysis and results (including data sharing) of fMRI studies (Nichols et al. in Best Practices in Data Analysis and Sharing in Neuroimaging using fMRI, 2016). In the past reviews have been published that evaluate how fMRI methods are reported based on the 2008 guidelines, but they did not focus on how task based fMRI results are reported. This review updates reporting practices of fMRI methods, and adds an extra focus on how fMRI results are reported. We discuss reporting practices about the design stage, specific participant characteristics, scanner characteristics, data processing methods, data analysis methods and reported results.

Abstract Image

综述论文:任务功能磁共振成像研究的报告实践。
功能磁共振成像研究的报告方法和结果的标准是什么,这些年来它们是如何演变的?为了回答这个问题,我们回顾了2004年至2019年间发表的160篇论文。fMRI研究方法和结果的报告风格在已发表的研究之间可能存在很大差异。然而,充分的报告对于研究的理解、复制和重用是必不可少的(例如在荟萃分析中)。为了帮助作者报告基于任务的fMRI研究的方法和结果,COBIDAS报告于2016年发表,该报告为研究人员提供了关于如何报告fMRI研究的设计、获取、预处理、统计分析和结果(包括数据共享)的明确指导方针(Nichols等人在《使用fMRI的神经成像数据分析和共享的最佳实践》,2016)。在过去已经发表的评论中,评估了如何根据2008年指南报告功能磁共振成像方法,但他们没有关注如何报告基于任务的功能磁共振成像结果。这篇综述更新了功能磁共振成像方法的报告实践,并增加了对功能磁共振成像结果如何报告的额外关注。我们讨论了关于设计阶段、具体参与者特征、扫描仪特征、数据处理方法、数据分析方法和报告结果的报告实践。
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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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