EEG-FCV: An EEG-Based Functional Connectivity Visualization Framework for Cognitive State Evaluation

• Published in: Frontiers in psychiatry Vol. 13; p. 928781
• Main Authors: Zeng, Hong, Jin, Yanping, Wu, Qi, Pan, Deng, Xu, Feifan, Zhao, Yue, Hu, Hua, Kong, Wanzeng
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 11.07.2022
• Subjects: brain cognitive function; Comprehensive; EEG; functional connectivity; Psychiatry; visualization
• ISSN: 1664-0640; 1664-0640
• DOI: 10.3389/fpsyt.2022.928781

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.