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


Journal

Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065

Informations de publication

Date de publication:
09 2020
Historique:
received: 03 06 2019
revised: 06 04 2020
accepted: 26 04 2020
pubmed: 30 5 2020
medline: 15 12 2021
entrez: 30 5 2020
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 32469458
doi: 10.1002/hbm.25035
pmc: PMC7416043
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3620-3636

Subventions

Organisme : China Scholarship Council Fund
ID : 201808340011
Organisme : Fundamental Research Funds for the Central Universities
ID : CDLS-2018-04
Organisme : National Natural Science Foundation of China
ID : 31600862
Organisme : National Natural Science Foundation of China
ID : 31900710
Organisme : National Natural Science Foundation of China
ID : 61773114
Organisme : Scientific Research Innovation Project of Bengbu Medical College
ID : BYKC201905
Organisme : Support Program of Excellent Young Talents in Universities of Anhui Province
ID : gxyqZD2017064

Informations de copyright

© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

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Auteurs

Li Zhang (L)

School of Medical Imaging, Bengbu Medical College, Bengbu, Anhui, China.

John Q Gan (JQ)

School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.

Yanmei Zhu (Y)

Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.

Jing Wang (J)

School of Computer Science and Information Technology, Xinyang Normal University, Xinyang, Henan, China.

Haixian Wang (H)

Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.

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