计算机科学
数据科学
神经影像学
人气
上传
集合(抽象数据类型)
领域(数学)
透视图(图形)
人工智能
万维网
心理学
数学
社会心理学
程序设计语言
精神科
纯数学
作者
Corey L. Horien,Stephanie Noble,Abigail S. Greene,Kangjoo Lee,Daniel S. Barron,Siyuan Gao,David A. O’Connor,Mehraveh Salehi,Javid Dadashkarimi,Xilin Shen,Evelyn M. R. Lake,Robert Todd Constable,Dustin Scheinost
标识
DOI:10.1038/s41562-020-01005-4
摘要
Large datasets that enable researchers to perform investigations with unprecedented rigor are growing increasingly common in neuroimaging. Due to the simultaneous increasing popularity of open science, these state-of-the-art datasets are more accessible than ever to researchers around the world. While analysis of these samples has pushed the field forward, they pose a new set of challenges that might cause difficulties for novice users. Here we offer practical tips for working with large datasets from the end-user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results. This manuscript serves as a practical guide one can use when working with large neuroimaging datasets, thus dissolving barriers to scientific discovery. Horien and colleagues provide a roadmap to working with large, publically available imaging datasets.
科研通智能强力驱动
Strongly Powered by AbleSci AI