Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy

Previous studies have shown that creative thinking is associated with metacontrol, but its neural basis is unknown. The present study explored the neural basis of both by assessing EEG complexity through multiscale entropy. Subjects were engaged in a metacontrol task and an Alternative Uses Task, gr...

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Main Authors: Hang Qi, Chunlei Liu
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Brain Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3425/14/11/1094
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author Hang Qi
Chunlei Liu
author_facet Hang Qi
Chunlei Liu
author_sort Hang Qi
collection DOAJ
description Previous studies have shown that creative thinking is associated with metacontrol, but its neural basis is unknown. The present study explored the neural basis of both by assessing EEG complexity through multiscale entropy. Subjects were engaged in a metacontrol task and an Alternative Uses Task, grouped according to task performance, and the EEG was analysed by multiscale entropy. The results showed that EEG complexity was significantly higher in the high-metacontrol and high-creativity groups than in the low-metacontrol and low-creativity groups, respectively, at high time scales. The metacontrol adaptability score and multipurpose task score were significantly and positively correlated with the EEG complexity at multiple electrode sites. It suggests that metacontrol and creativity are dependent on the activation of long-duration neural networks.
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spelling doaj-art-8bc7899ea329466881cc9e3b3dcc3ff32025-08-20T02:28:08ZengMDPI AGBrain Sciences2076-34252024-10-011411109410.3390/brainsci14111094Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale EntropyHang Qi0Chunlei Liu1School of Psychology, Qufu Normal University, Qufu 273165, ChinaSchool of Psychology, Qufu Normal University, Qufu 273165, ChinaPrevious studies have shown that creative thinking is associated with metacontrol, but its neural basis is unknown. The present study explored the neural basis of both by assessing EEG complexity through multiscale entropy. Subjects were engaged in a metacontrol task and an Alternative Uses Task, grouped according to task performance, and the EEG was analysed by multiscale entropy. The results showed that EEG complexity was significantly higher in the high-metacontrol and high-creativity groups than in the low-metacontrol and low-creativity groups, respectively, at high time scales. The metacontrol adaptability score and multipurpose task score were significantly and positively correlated with the EEG complexity at multiple electrode sites. It suggests that metacontrol and creativity are dependent on the activation of long-duration neural networks.https://www.mdpi.com/2076-3425/14/11/1094metacontrolcreativityelectroencephalographymultiscale entropyneural networks
spellingShingle Hang Qi
Chunlei Liu
Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy
Brain Sciences
metacontrol
creativity
electroencephalography
multiscale entropy
neural networks
title Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy
title_full Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy
title_fullStr Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy
title_full_unstemmed Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy
title_short Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy
title_sort metacontrol regulates creative thinking an eeg complexity analysis based on multiscale entropy
topic metacontrol
creativity
electroencephalography
multiscale entropy
neural networks
url https://www.mdpi.com/2076-3425/14/11/1094
work_keys_str_mv AT hangqi metacontrolregulatescreativethinkinganeegcomplexityanalysisbasedonmultiscaleentropy
AT chunleiliu metacontrolregulatescreativethinkinganeegcomplexityanalysisbasedonmultiscaleentropy