Functional Brain Network Analysis of Knowledge Transfer While Engineering Problem-Solving - Wang, Fuhua; Jiang, Zuhua; Li, Xinyu; Bu, Lingguo; Ji, Yongjun (Frontiers in Human Neuroscience, 2021)
As a complex cognitive activity, knowledge transfer is usually correlated to cognitive processes such as working memory, behavior control, and decision-making in the human brain while engineering problem-solving. It is crucial to explain how the alteration of the functional brain network occurs and how to express it, which causes the alteration of the cognitive structure of knowledge transfer. However, the neurophysiological mechanism of knowledge transfer was rarely considered in existing studies. This paper proposed functional connectivity (FC) to describe and evaluate the differences in the functional brain network of knowledge transfer. In this study, we adopted the modified Wisconsin Card-Sorting Test (M-WCST) reported in the literature. The neural activation of the prefrontal cortex is continuously recorded for 31 participants by fNIRS. Concretely, we discussed the prior cognitive level, knowledge transfer performance, and the transfer distance impacting the wavelet amplitude and wavelet phase coherence. The paired T-test results showed that the prior cognitive level and the transfer distance significantly impact functional connectivity. The Pearson correlation coefficient showed that both wavelet amplitude and wavelet phase coherence are positively correlated to the cognitive function of the prefrontal cortex. Therefore, brain functional connectivity is an available indicator to evaluate cognitive structure alteration in knowledge transfer. Meanwhile, we also discussed why DLPFC and OFA distinguish themselves from other brain areas in the M-WCST experiment. As an exploratory study in NeuroManagement, these findings may provide neurophysiological evidence about the functional brain network of knowledge transfer while engineering problem-solving.