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Resting-State Functional Connectivity in Mathematical Expertise

Title
Resting-State Functional Connectivity in Mathematical Expertise
Authors
Shim, MiseonHwang, Han-JeongKuhl, UlrikeJeon, Hyeon-Ae
DGIST Authors
Shim, Miseon; Hwang, Han-Jeong; Kuhl, Ulrike; Jeon, Hyeon-Ae
Issue Date
2021-04
Citation
Brain Sciences, 11(4), 430
Type
Article
Article Type
Article
Author Keywords
resting-state functional connectivitymathematiciansexpertiseneural efficiencymachine learningsupport vector machine
ISSN
2076-3425
Abstract
To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians and non-mathematicians were distinguished depending on features of functional connectivity. We showed diverging involvement of the frontal–thalamic–temporal connections for mathematicians and the medial–frontal areas to precuneus and the lateral orbital gyrus to thalamus connections for non-mathematicians. Moreover, mathematicians who had higher scores in mathematical knowledge showed a weaker connection strength between the left and right caudate nucleus, demonstrating the connections’ characteristics related to mathematical expertise. Separate functional networks between the two groups were validated with a maximum classification accuracy of 91.19% using the distinct resting-state fMRI-based functional connectivity features. We suggest the advantageous role of preconfigured resting-state functional connectivity, as well as the neural efficiency for experts’ successful performance. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
URI
http://hdl.handle.net/20.500.11750/13012
DOI
10.3390/brainsci11040430
Publisher
MDPI AG
Related Researcher
  • Author Jeon, Hyeon-Ae Laboratory of Cognitive Neuroscience
  • Research Interests fMRI, high-level cognition, brain imaging
Files:
Collection:
Department of Brain SciencesLaboratory of Cognitive Neuroscience1. Journal Articles


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