Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Zhang L

PROVIDER: S-EPMC7416043 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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

Zhang Li L Gan John Q JQ Zhu Yanmei Y Wang Jing J Wang Haixian H

Human brain mapping 20200529 13

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 sev ...[more]

PMID: 32469458

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Dataset Information

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

Publications

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

Similar Datasets

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