Shim Miseon, Hwang Han-Jeong, Kuhl Ulrike, Jeon Hyeon-Ae
Department of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.
Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong 30019, Korea.
Brain Sci. 2021 Mar 28;11(4):430. doi: 10.3390/brainsci11040430.
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.
大脑的功能连接在多大程度上反映了不同水平的专业知识？我们通过对数学家和非数学家进行静息态功能磁共振成像（fMRI）来解决这个问题。为此，我们研究了两组参与者在静息状态下全脑区域自发血氧水平依赖波动的相关性上有何不同。此外，通过使用机器学习中的分类算法，我们研究了根据功能连接特征，数学家和非数学家之间的静息态fMRI网络是否有区别。我们发现，数学家的额-丘脑-颞叶连接以及非数学家的内侧额叶区域到楔前叶和外侧眶回至丘脑的连接存在不同程度的参与。此外，数学知识得分较高的数学家，其左右尾状核之间的连接强度较弱，这表明了与数学专业知识相关的连接特征。利用基于静息态fMRI的独特功能连接特征，两组之间的独立功能网络得到了验证，最大分类准确率为91.19%。我们认为预配置的静息态功能连接具有优势作用，以及神经效率对专家成功表现的作用。
