title: Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks.
abstract: Working memory (WM) refers to the temporary holding and manipulation of information during the performance of a range of cognitive tasks, and WM training is a promising method for improving an individual's cognitive functions. Our previous work demonstrated that WM performance can be improved through self-regulation of dorsal lateral prefrontal cortex (PFC) activation using real-time functional magnetic resonance imaging (rtfMRI), which enables individuals to control local brain activities volitionally according to the neurofeedback. Furthermore, research concerning large-scale brain networks has demonstrated that WM training requires the engagement of several networks, including the central executive network (CEN), the default mode network (DMN) and the salience network (SN), and functional connectivity within the CEN and DMN can be changed by WM training. Although a switching role of the SN between the CEN and DMN has been demonstrated, it remains unclear whether WM training can affect the interactions between the three networks and whether a similar mechanism also exists during the training process. In this study, we investigated the dynamic functional connectivity between the three networks during the rtfMRI feedback training using independent component analysis (ICA) and correlation analysis. The results indicated that functional connectivity within and between the three networks were significantly enhanced by feedback training, and most of the changes were associated with the insula and correlated with behavioral improvements. These findings suggest that the insula plays a critical role in the reorganization of functional connectivity among the three networks induced by rtfMRI training and in WM performance, thus providing new insights into the mechanisms of high-level functions and the clinical treatment of related functional impairments.
authors.affiliation: College of Information Science and Technology, Beijing Normal University Beijing, China.
authors.forename: Qiushi
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: School of Computer Science and Technology, Tianjin University Tianjin, China.
authors.forename: Gaoyan
authors.initials: G
authors.lastname: Zhang
authors.affiliation: College of Information Science and Technology, Beijing Normal University Beijing, China ; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University Beijing, China.
authors.forename: Li
authors.initials: L
authors.lastname: Yao
authors.affiliation: College of Information Science and Technology, Beijing Normal University Beijing, China.
authors.forename: Xiaojie
authors.initials: X
authors.lastname: Zhao
keywords: functional connectivity; insula; large-scale brain network; real-time fMRI; working memory training