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Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents.
Comput Intell Neurosci. 2020; 2020:4209321.CI

Abstract

The neurocognitive characteristics of mathematically gifted adolescents are characterized by highly developed functional interactions between the right hemisphere and excellent cognitive control of the prefrontal cortex, enhanced frontoparietal cortex, and posterior parietal cortex. However, it is still unclear when and how these cortical interactions occur. In this paper, we used directional coherence analysis based on Granger causality to study the interactions between the frontal brain area and the posterior brain area in the mathematical frontoparietal network system during deductive reasoning tasks. Specifically, the scalp electroencephalography (EEG) signal was first converted into a cortical dipole source signal to construct a Granger causality network over the θ-band and γ-band ranges. We constructed the binary Granger causality network at the 40 pairs of cortical nodes in the frontal lobe and parietal lobe across the θ-band and the γ-band, which were selected as regions of interest (ROI). We then used graph theory to analyze the network differences. It was found that, in the process of reasoning tasks, the frontoparietal regions of the mathematically gifted show stronger working memory information processing at the θ-band. Additionally, in the middle and late stages of the conclusion period, the mathematically talented individuals have less information flow in the anterior and posterior parietal regions of the brain than the normal subjects. We draw the conclusion that the mathematically gifted brain frontoparietal network appears to have more "automated" information processing during reasoning tasks.

Authors+Show Affiliations

Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, China.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, China.Qingdao Port International Company, Ltd., Qingdao 266011, Shandong, China.Co-Innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Shandong Technology and Business University, Yantai 264005, Shandong, China.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, China.Department of Rehabilitation, Zhongda Hospital, Southeast University, Nanjing 210009, Jiangsu, China.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32908474

Citation

Wei, Mengting, et al. "Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents." Computational Intelligence and Neuroscience, vol. 2020, 2020, p. 4209321.
Wei M, Wang Q, Jiang X, et al. Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents. Comput Intell Neurosci. 2020;2020:4209321.
Wei, M., Wang, Q., Jiang, X., Guo, Y., Fan, H., Wang, H., & Lu, X. (2020). Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents. Computational Intelligence and Neuroscience, 2020, 4209321. https://doi.org/10.1155/2020/4209321
Wei M, et al. Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents. Comput Intell Neurosci. 2020;2020:4209321. PubMed PMID: 32908474.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents. AU - Wei,Mengting, AU - Wang,Qingyun, AU - Jiang,Xiang, AU - Guo,Yiyun, AU - Fan,Hui, AU - Wang,Haixian, AU - Lu,Xuesong, Y1 - 2020/08/28/ PY - 2019/09/09/received PY - 2020/07/27/revised PY - 2020/08/10/accepted PY - 2020/9/10/entrez PY - 2020/9/11/pubmed PY - 2021/7/29/medline SP - 4209321 EP - 4209321 JF - Computational intelligence and neuroscience JO - Comput Intell Neurosci VL - 2020 N2 - The neurocognitive characteristics of mathematically gifted adolescents are characterized by highly developed functional interactions between the right hemisphere and excellent cognitive control of the prefrontal cortex, enhanced frontoparietal cortex, and posterior parietal cortex. However, it is still unclear when and how these cortical interactions occur. In this paper, we used directional coherence analysis based on Granger causality to study the interactions between the frontal brain area and the posterior brain area in the mathematical frontoparietal network system during deductive reasoning tasks. Specifically, the scalp electroencephalography (EEG) signal was first converted into a cortical dipole source signal to construct a Granger causality network over the θ-band and γ-band ranges. We constructed the binary Granger causality network at the 40 pairs of cortical nodes in the frontal lobe and parietal lobe across the θ-band and the γ-band, which were selected as regions of interest (ROI). We then used graph theory to analyze the network differences. It was found that, in the process of reasoning tasks, the frontoparietal regions of the mathematically gifted show stronger working memory information processing at the θ-band. Additionally, in the middle and late stages of the conclusion period, the mathematically talented individuals have less information flow in the anterior and posterior parietal regions of the brain than the normal subjects. We draw the conclusion that the mathematically gifted brain frontoparietal network appears to have more "automated" information processing during reasoning tasks. SN - 1687-5273 UR - https://www.unboundmedicine.com/medline/citation/32908474/Directed_Connectivity_Analysis_of_the_Brain_Network_in_Mathematically_Gifted_Adolescents_ L2 - https://doi.org/10.1155/2020/4209321 DB - PRIME DP - Unbound Medicine ER -