Eeg-FCV
An EEG-Based Functional Connectivity Visualization Framework for Cognitive State Evaluation
Bibliographic Data
| ID | 15522709 |
|---|---|
| Authors | Hong Zeng (0000-0002-3301-2417, Hangzhou Dianzi University), Yanping Jin (0000-0002-0314-0274, Hangzhou Dianzi University), Qi Wu (0000-0001-5487-3278, Hangzhou Dianzi University), Deng Pan (0000-0002-9007-0744, Hangzhou Dianzi University), Feifan Xu (0009-0006-6424-6482, Hangzhou Dianzi University), Yue Zhao (0000-0003-0636-7092, Hangzhou Dianzi University), Hua Hu (0000-0002-4957-879X, Hangzhou Normal University), Wanzeng Kong (0000-0002-0113-6968, Hangzhou Dianzi University, corresponding author) |
| Year | 2022 |
| Volume | 13 |
| Pages | 928781-928781 |
| Publication date | 2022-07-11 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2022.928781 |
| PMID | 35898631 |
| OpenAlex | W4285010105 |
| Language | EN |
| References cited | 46 |
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
Brain activity and meditation · Brain function · Clutter · Cognition · EEG-fMRI · Electroencephalography · Pattern recognition (psychology · Visualization · Computer Science · EEG and Brain-Computer Interfaces · Functional Brain Connectivity Studies · Neural dynamics and brain function · Neuroscience · Psychology · Artificial Intelligence
| Highly cited | No |
|---|