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WeBrain: A web-based brainformatics platform of computational ecosystem for EEG big data analysis

Authors :
Fali Li
Qiunan Zou
Yufan Zhang
Dezhong Yao
Jinnan Gong
Tiejun Liu
Xin Wen
Alan C. Evans
Dong Li
Lingling Zhao
Jianfu Li
Pedro A. Valdes-Sosa
Source :
NeuroImage, Vol 245, Iss, Pp 118713-(2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

The current evolution of 'cloud neuroscience' leads to more efforts with the large-scale EEG applications, by using EEG pipelines to handle the rapidly accumulating EEG data. However, there are a few specific cloud platforms that seek to address the cloud computational challenges of EEG big data analysis to benefit the EEG community. In response to the challenges, a WeBrain cloud platform (https://webrain.uestc.edu.cn/) is designed as a web-based brainformatics platform and computational ecosystem to enable large-scale EEG data storage, exploration and analysis using cloud high-performance computing (HPC) facilities. WeBrain connects researchers from different fields to EEG and multimodal tools that have become the norm in the field and the cloud processing power required to handle those large EEG datasets. This platform provides an easy-to-use system for novice users (even no computer programming skills) and provides satisfactory maintainability, sustainability and flexibility for IT administrators and tool developers. A range of resources are also available on https://webrain.uestc.edu.cn/, including documents, manuals, example datasets related to WeBrain, and collected links to open EEG datasets and tools. It is not necessary for users or administrators to install any software or system, and all that is needed is a modern web browser, which reduces the technical expertise required to use or manage WeBrain. The WeBrain platform is sponsored and driven by the China-Canada-Cuba international brain cooperation project (CCC-Axis, http://ccc-axis.org/), and we hope that WeBrain will be a promising cloud brainformatics platform for exploring brain information in large-scale EEG applications in the EEG community.

Details

Language :
English
ISSN :
10959572
Volume :
245
Database :
OpenAIRE
Journal :
NeuroImage
Accession number :
edsair.doi.dedup.....5f42ab90edb5356b32feed42f069c89c