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大脑关联能力的体素级定量映射

Voxel-Wise Quantitative Mapping of the Brain Association Ability.

作者信息

Chen Kai, Wang Lijie, Zeng Jianguang, Chen Ai, Gao Zhao, Wang Jiaojian

机构信息

School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.

School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

出版信息

Front Neurosci. 2021 Oct 15;15:746894. doi: 10.3389/fnins.2021.746894. eCollection 2021.

DOI:10.3389/fnins.2021.746894
PMID:34720865
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8555663/
Abstract

The association cortices of the brain are essential for integrating multimodal information that subserves complex and high-order cognitive functions. To delineate the changing pattern of associative cortices can provide critical insight into brain development, aging, plasticity, and disease-triggered functional abnormalities. However, how to quantitatively characterize the association capability of the brain is elusive. Here, we developed a new method of association index (Asso) at the voxel level to quantitatively characterize the brain association ability. Using the Asso method, we found high Asso values in association cortical networks, and low values in visual and limbic networks, suggesting a pattern of significant gradient distribution in neural functions. The spatial distribution patterns of Asso show high similarities across different thresholds suggesting that Asso mapping is a threshold-free method. In addition, compared with functional connectivity strength, i.e., degree centrality method, Asso mapping showed different patterns for association cortices and primary cortices. Finally, the Asso method was applied to investigate aging effects and identified similar findings with previous studies. All these results indicated that Asso can characterize the brain association patterns effectively and open a new avenue to reveal a neural basis for development, aging, and brain disorders.

摘要

大脑的联合皮质对于整合多模态信息至关重要,这些信息支持复杂和高阶认知功能。描绘联合皮质的变化模式可以为大脑发育、衰老、可塑性以及疾病引发的功能异常提供关键见解。然而,如何定量表征大脑的联合能力仍不清楚。在这里,我们开发了一种体素水平的联合指数(Asso)新方法,以定量表征大脑的联合能力。使用Asso方法,我们发现联合皮质网络中的Asso值较高,而视觉和边缘网络中的值较低,这表明神经功能存在显著的梯度分布模式。Asso的空间分布模式在不同阈值下显示出高度相似性,这表明Asso映射是一种无阈值方法。此外,与功能连接强度,即度中心性方法相比,Asso映射在联合皮质和初级皮质中显示出不同的模式。最后,Asso方法被应用于研究衰老效应,并得到了与先前研究相似的结果。所有这些结果表明,Asso可以有效地表征大脑联合模式,并为揭示发育、衰老和脑部疾病的神经基础开辟了一条新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/7e9f4783c6e9/fnins-15-746894-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/4d9da5616ab3/fnins-15-746894-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/04b6fd3878fb/fnins-15-746894-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/16b11e42a814/fnins-15-746894-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/95c7a73ff251/fnins-15-746894-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/7e9f4783c6e9/fnins-15-746894-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/4d9da5616ab3/fnins-15-746894-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/04b6fd3878fb/fnins-15-746894-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/16b11e42a814/fnins-15-746894-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/95c7a73ff251/fnins-15-746894-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8982/8555663/7e9f4783c6e9/fnins-15-746894-g005.jpg

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