IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v100y2023ics0160289623000661.html
   My bibliography  Save this article

The moderating effect of the DMN connectivity on the correlation between online creativity performances in single- and paired-player modes

Author

Listed:
  • Wu, Ching-Lin

Abstract

This study examined how brain structure influences creative performance during cooperation with others. This study employed graph theory to analyze the moderating effect of connectivity efficiency of a default mode network (DMN) on individuals' creative performance in interactive situations. The results showed that the global efficiencies of the DMN moderated the relationship between individuals' divergent thinking performance in the single- and paired-player modes. When the global efficiency in the DMN is high, an individual's originality performance in the single-player mode has high predictive power for performance in the paired-player mode. In addition, the global efficiency of the DMN can moderate the relationship between the flexibility scores in the single- and paired-player modes. In the case of high global efficiency, the flexibility performance in single-player mode has a higher predictive power in interactive situations. Furthermore, the nodal efficiency of the parahippocampal cortex can moderate the correlation between fluency (an index of divergent thinking) scores in the single- and paired-player modes, whereas the nodal efficiency of the anterior medial prefrontal cortex can moderate the relationship between the Chinese Radical Remote Associates Test performance in the single- and paired-player modes.

Suggested Citation

  • Wu, Ching-Lin, 2023. "The moderating effect of the DMN connectivity on the correlation between online creativity performances in single- and paired-player modes," Intelligence, Elsevier, vol. 100(C).
  • Handle: RePEc:eee:intell:v:100:y:2023:i:c:s0160289623000661
    DOI: 10.1016/j.intell.2023.101785
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289623000661
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.intell.2023.101785?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intell:v:100:y:2023:i:c:s0160289623000661. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.