Cargando…

EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task

To reveal transition dynamics of global neuronal networks of math‐gifted adolescents in handling long‐chain reasoning, this study explores momentary phase‐synchronized patterns, that is, electroencephalogram (EEG) synchrostates, of intracerebral sources sustained in successive 50 ms time windows dur...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Li, Gan, John Q., Zhu, Yanmei, Wang, Jing, Wang, Haixian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416043/
https://www.ncbi.nlm.nih.gov/pubmed/32469458
http://dx.doi.org/10.1002/hbm.25035
_version_ 1783569249248215040
author Zhang, Li
Gan, John Q.
Zhu, Yanmei
Wang, Jing
Wang, Haixian
author_facet Zhang, Li
Gan, John Q.
Zhu, Yanmei
Wang, Jing
Wang, Haixian
author_sort Zhang, Li
collection PubMed
description To reveal transition dynamics of global neuronal networks of math‐gifted adolescents in handling long‐chain reasoning, this study explores momentary phase‐synchronized patterns, that is, electroencephalogram (EEG) synchrostates, of intracerebral sources sustained in successive 50 ms time windows during a reasoning task and non‐task idle process. Through agglomerative hierarchical clustering for functional connectivity graphs and nested iterative cosine similarity tests, this study identifies seven general and one reasoning‐specific prototypical functional connectivity patterns from all synchrostates. Markov modeling is performed for the time‐sequential synchrostates of each trial to characterize the interstate transitions. The analysis reveals that default mode network, central executive network (CEN), dorsal attention network, cingulo‐opercular network, left/right ventral frontoparietal network, and ventral visual network aperiodically recur over non‐task or reasoning process, exhibiting high predictability in interactively reachable transitions. Compared to non‐gifted subjects, math‐gifted adolescents show higher fractional occupancy and mean duration in CEN and reasoning‐triggered transient right frontotemporal network (rFTN) in the time course of the reasoning process. Statistical modeling of Markov chains reveals that there are more self‐loops in CEN and rFTN of the math‐gifted brain, suggesting robust state durability in temporally maintaining the topological structures. Besides, math‐gifted subjects show higher probabilities in switching from the other types of synchrostates to CEN and rFTN, which represents more adaptive reconfiguration of connectivity pattern in the large‐scale cortical network for focused task‐related information processing, which underlies superior executive functions in controlling goal‐directed persistence and high predictability of implementing imagination and creative thinking during long‐chain reasoning.
format Online
Article
Text
id pubmed-7416043
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley & Sons, Inc.
record_format MEDLINE/PubMed
spelling pubmed-74160432020-08-10 EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task Zhang, Li Gan, John Q. Zhu, Yanmei Wang, Jing Wang, Haixian Hum Brain Mapp Research Articles To reveal transition dynamics of global neuronal networks of math‐gifted adolescents in handling long‐chain reasoning, this study explores momentary phase‐synchronized patterns, that is, electroencephalogram (EEG) synchrostates, of intracerebral sources sustained in successive 50 ms time windows during a reasoning task and non‐task idle process. Through agglomerative hierarchical clustering for functional connectivity graphs and nested iterative cosine similarity tests, this study identifies seven general and one reasoning‐specific prototypical functional connectivity patterns from all synchrostates. Markov modeling is performed for the time‐sequential synchrostates of each trial to characterize the interstate transitions. The analysis reveals that default mode network, central executive network (CEN), dorsal attention network, cingulo‐opercular network, left/right ventral frontoparietal network, and ventral visual network aperiodically recur over non‐task or reasoning process, exhibiting high predictability in interactively reachable transitions. Compared to non‐gifted subjects, math‐gifted adolescents show higher fractional occupancy and mean duration in CEN and reasoning‐triggered transient right frontotemporal network (rFTN) in the time course of the reasoning process. Statistical modeling of Markov chains reveals that there are more self‐loops in CEN and rFTN of the math‐gifted brain, suggesting robust state durability in temporally maintaining the topological structures. Besides, math‐gifted subjects show higher probabilities in switching from the other types of synchrostates to CEN and rFTN, which represents more adaptive reconfiguration of connectivity pattern in the large‐scale cortical network for focused task‐related information processing, which underlies superior executive functions in controlling goal‐directed persistence and high predictability of implementing imagination and creative thinking during long‐chain reasoning. John Wiley & Sons, Inc. 2020-05-29 /pmc/articles/PMC7416043/ /pubmed/32469458 http://dx.doi.org/10.1002/hbm.25035 Text en © 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
Zhang, Li
Gan, John Q.
Zhu, Yanmei
Wang, Jing
Wang, Haixian
EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task
title EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task
title_full EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task
title_fullStr EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task
title_full_unstemmed EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task
title_short EEG source‐space synchrostate transitions and Markov modeling in the math‐gifted brain during a long‐chain reasoning task
title_sort eeg source‐space synchrostate transitions and markov modeling in the math‐gifted brain during a long‐chain reasoning task
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416043/
https://www.ncbi.nlm.nih.gov/pubmed/32469458
http://dx.doi.org/10.1002/hbm.25035
work_keys_str_mv AT zhangli eegsourcespacesynchrostatetransitionsandmarkovmodelinginthemathgiftedbrainduringalongchainreasoningtask
AT ganjohnq eegsourcespacesynchrostatetransitionsandmarkovmodelinginthemathgiftedbrainduringalongchainreasoningtask
AT zhuyanmei eegsourcespacesynchrostatetransitionsandmarkovmodelinginthemathgiftedbrainduringalongchainreasoningtask
AT wangjing eegsourcespacesynchrostatetransitionsandmarkovmodelinginthemathgiftedbrainduringalongchainreasoningtask
AT wanghaixian eegsourcespacesynchrostatetransitionsandmarkovmodelinginthemathgiftedbrainduringalongchainreasoningtask