Brain networks of mathematically gifted adolescents based on directed transfer function and partial directed coherence

Yakun Zhu; Haixian Wang

doi:10.1117/12.2687736

28 August 2023 Brain networks of mathematically gifted adolescents based on directed transfer function and partial directed coherence

Yakun Zhu, Haixian Wang

Author Affiliations +

Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 127241V (2023) https://doi.org/10.1117/12.2687736
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China

Abstract

The study on the structural connectivity and functional connectivity of the brain networks of mathematically gifted adolescents found that mathematically gifted brains exhibited cognitive neural features that are different from average adolescents and beneficial for task processing in the aspects of activation in task-related brain areas, information interaction between hemispheres, and network connection reorganization. In this paper, we adopted directed transfer function (DTF) and partial directed coherence (PDC) to analyze the effective connectivity of mathematically gifted adolescents from electroencephalography (EEG) data. The information flow patterns of the brain networks during the deductive reasoning task were analyzed and the group differences in the information flow of the fronto-parietal network were compared at the θ-band and γ-band. The empirical results demonstrated that the mathematically gifted brain exhibited more information transfer between distant nodes and more information flow from the prefrontal lobe to other brain regions in both DTF and PDC directed networks, ensuring the excellent task performance of mathematically gifted adolescents.

Citation Download Citation

Yakun Zhu and Haixian Wang "Brain networks of mathematically gifted adolescents based on directed transfer function and partial directed coherence", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 127241V (28 August 2023); https://doi.org/10.1117/12.2687736

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Brain

Electroencephalography

Matrices

Covariance matrices

Autoregressive models

Information fusion

Electrodes

Show All Keywords

Keywords/Phrases

Search In:

Publication Years