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通过人类大脑的结构和几何形状对功能连接性进行基准测试。

Benchmarking functional connectivity by the structure and geometry of the human brain.

作者信息

Liu Zhen-Qi, Betzel Richard F, Misic Bratislav

机构信息

McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.

Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.

出版信息

Netw Neurosci. 2022 Oct 1;6(4):937-949. doi: 10.1162/netn_a_00236. eCollection 2022.

Abstract

The brain's structural connectivity supports the propagation of electrical impulses, manifesting as patterns of coactivation, termed functional connectivity. Functional connectivity emerges from the underlying sparse structural connections, particularly through polysynaptic communication. As a result, functional connections between brain regions without direct structural links are numerous, but their organization is not completely understood. Here we investigate the organization of functional connections without direct structural links. We develop a simple, data-driven method to benchmark functional connections with respect to their underlying structural and geometric embedding. We then use this method to reweigh and reexpress functional connectivity. We find evidence of unexpectedly strong functional connectivity among distal brain regions and within the default mode network. We also find unexpectedly strong functional connectivity at the apex of the unimodal-transmodal hierarchy. Our results suggest that both phenomena-functional modules and functional hierarchies-emerge from functional interactions that transcend the underlying structure and geometry. These findings also potentially explain recent reports that structural and functional connectivity gradually diverge in transmodal cortex. Collectively, we show how structural connectivity and geometry can be used as a natural frame of reference with which to study functional connectivity patterns in the brain.

摘要

大脑的结构连通性支持电脉冲的传播,表现为共同激活模式,即功能连通性。功能连通性源自潜在的稀疏结构连接,尤其是通过多突触通信。因此,没有直接结构联系的脑区之间的功能连接很多,但其组织方式尚未完全了解。在这里,我们研究没有直接结构联系的功能连接的组织方式。我们开发了一种简单的数据驱动方法,以根据其潜在的结构和几何嵌入对功能连接进行基准测试。然后,我们使用这种方法重新权衡和重新表达功能连通性。我们发现了远隔脑区之间以及默认模式网络内意外强大的功能连通性的证据。我们还在单峰 - 跨峰层次结构的顶端发现了意外强大的功能连通性。我们的结果表明,功能模块和功能层次结构这两种现象均源自超越潜在结构和几何的功能相互作用。这些发现也可能解释了最近关于跨峰皮质中结构和功能连通性逐渐分离的报道。总体而言,我们展示了如何将结构连通性和几何用作研究大脑功能连通性模式的自然参考框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34b9/9976650/042169d6c298/netn-06-937-g001.jpg

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