AUTHOR=Zeng Hong , Jin Yanping , Wu Qi , Pan Deng , Xu Feifan , Zhao Yue , Hu Hua , Kong Wanzeng TITLE=EEG-FCV: An EEG-Based Functional Connectivity Visualization Framework for Cognitive State Evaluation JOURNAL=Frontiers in Psychiatry VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2022.928781 DOI=10.3389/fpsyt.2022.928781 ISSN=1664-0640 ABSTRACT=

Electroencephalogram (EEG)-based tools for brain functional connectivity (FC) analysis and visualization play an important role in evaluating brain cognitive function. However, existing similar FC analysis tools are not only visualized in 2 dimensions (2D) but also are highly prone to cause visual clutter and unable to dynamically reflect brain connectivity changes over time. Therefore, we design and implement an EEG-based FC visualization framework in this study, named EEG-FCV, for brain cognitive state evaluation. EEG-FCV is composed of three parts: the Data Processing module, Connectivity Analysis module, and Visualization module. Specially, FC is visualized in 3 dimensions (3D) by introducing three existing metrics: Pearson Correlation Coefficient (PCC), Coherence, and PLV. Furthermore, a novel metric named Comprehensive is proposed to solve the problem of visual clutter. EEG-FCV can also visualize dynamically brain FC changes over time. Experimental results on two available datasets show that EEG-FCV has not only results consistent with existing related studies on brain FC but also can reflect dynamically brain FC changes over time. We believe EEG-FCV could prompt further progress in brain cognitive function evaluation.