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      Verbal Creativity Is Correlated With the Dynamic Reconfiguration of Brain Networks in the Resting State

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          Abstract

          Creativity is the foundation of human culture. All inventions and innovations in history rely upon us to break with the traditional thinking and create something novel. A number of neuroimaging studies have explored the neural mechanism of creativity. However, a majority of researches have focused only on the stationary functional connectivity in resting-state fMRI and task-related fMRI, neglecting the dynamic variation of brain networks. Here, we used dynamic network analysis to investigate the relation between the dynamic reorganization of brain networks and verbal creativity in 370 healthy subjects. We found that the integration of the left lingual gyrus and left middle temporal gyrus (MTG) in default mode network (DMN) and the integration of the DMN and cerebellum, frontoparietal task control network (FPTC) and auditory network (Aud) showed positive correlation with verbal creativity performance. In addition, the recruitment of the bilateral postcentral gyrus from the sensory/somatomotor network (SMN) and the recruitment of the SMN in general displayed a significant correlation with verbal creativity scores. Taken together, these results suggested that the dynamic reorganization among the brain networks involved multiple cognitive processes, such as memory retrieval, imaginative process, cognitive control – these are all important for verbal creativity. These findings provided direct evidence that verbal creativity was related to the dynamic variation of brain mechanism during resting-state, extending past research on the neural mechanism of creativity. Meanwhile, these results bought about new perspectives for verbal creative training and rehabilitation training of depression.

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          Most cited references45

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          Movement-related effects in fMRI time-series.

          This paper concerns the spatial and intensity transformations that are required to adjust for the confounding effects of subject movement during functional MRI (fMRI) activation studies. An approach is presented that models, and removes, movement-related artifacts from fMRI time-series. This approach is predicated on the observation that movement-related effects are extant even after perfect realignment. Movement-related effects can be divided into those that are a function of position of the object in the frame of reference of the scanner and those that are due to movement in previous scans. This second component depends on the history of excitation experienced by spins in a small volume and consequent differences in local saturation. The spin excitation history thus will itself be a function of previous positions, suggesting an autoregression-moving average model for the effects of previous displacements on the current signal. A model is described as well as the adjustments for movement-related components that ensue. The empirical analyses suggest that (in extreme situations) over 90% of fMRI signal can be attributed to movement, and that this artifactual component can be successfully removed.
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            Dynamic reconfiguration of human brain networks during learning.

            Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes--flexibility and selection--must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we investigate the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.
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              Anterior cingulate cortex and conflict detection: an update of theory and data.

              The dorsal anterior cingulate cortex (ACC) and associated regions of the medial frontal wall have often been hypothesized to play an important role in cognitive control. We have proposed that the ACC's specific role in cognitive control is to detect conflict between simultaneously active, competing representations and to engage the dorsolateral prefrontal cortex (DLPFC) to resolve such conflict. Here we review some of the evidence supporting this theory, from event-related potential (ERP) and fMRI studies. We focus on data obtained from interference tasks, such as the Stroop task, and review the evidence that trial-to-trial changes in control engagement can be understood as driven by conflict detection; the data suggest that levels of activation of the ACC and the DLPFC in such tasks do indeed reflect conflict and control, respectively. We also discuss some discrepant results in the literature that highlight the need for future research.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                24 April 2019
                2019
                : 10
                : 894
                Affiliations
                [1] 1Faculty of Psychology, Southwest University , Chongqing, China
                [2] 2Key Laboratory of Cognition and Personality (SWU), Ministry of Education , Chongqing, China
                Author notes

                Edited by: Massimiliano Palmiero, University of L’Aquila, Italy

                Reviewed by: Fabio Sambataro, University of Udine, Italy; Liudmila Al. Dikaya, Southern Federal University, Russia

                *Correspondence: Jiang Qiu, qiuj318@ 123456swu.edu.cn

                These authors have contributed equally to this work

                This article was submitted to Cognition, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2019.00894
                6491857
                31920806
                58bf02b7-a2ef-4b18-88e7-0539d7e47157
                Copyright © 2019 Feng, He, Yang, Zhang, Wu and Qiu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 October 2018
                : 03 April 2019
                Page count
                Figures: 3, Tables: 3, Equations: 0, References: 64, Pages: 9, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Funded by: Natural Science Foundation of Chongqing 10.13039/501100005230
                Funded by: Fok Ying Tung Education Foundation 10.13039/501100010261
                Categories
                Psychology
                Original Research

                Clinical Psychology & Psychiatry
                creativity,resting state,dynamic reorganization,brain networks,neural mechanism

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