Large-Scale High-Resolution Probabilistic Maps of the Human Superior Longitudinal Fasciculus Subdivisions and their Cortical Terminations.

IF 4 2区 医学 Q1 NEUROSCIENCES Journal of Neuroscience Pub Date : 2025-03-24 DOI:10.1523/JNEUROSCI.0821-24.2025
Matthew Amandola, Katherine Farber, Roma Kidambi, Hoi-Chung Leung
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Abstract

The superior longitudinal fasciculus (SLF) is the large white matter association tract connecting the prefrontal and posterior parietal cortices. Past studies in non-human primates have parcellated the SLF into three subdivisions and have outlined the specific cortico-cortical organization and terminations for each subdivision. However, it is difficult to characterize these structural connections in humans to the specificity of tract-tracing studies in animals. This has led to disagreement on how the SLF subdivisions are organized in the human brain, including if the dorsomedial SLF (SLF-I) is part of the cingulum subsystem. Here, we present a novel large-scale, probabilistic map of the SLF subdivisions, using high-resolution diffusion imaging data from the Human Connectome Project (HCP). We used image data from 302 adult males and 405 adult females to model the three SLF subdivisions in each hemisphere, and attempted to characterize the frontal and parietal termination points for each subdivision. SLF subdivisions were successfully modeled in each subject, showing the dorsomedial-to-ventrolateral organization similar to that in nonhuman primate histological studies. We also found minimal differences between SLF-I models with and without the cingulate gyrus excluded, suggesting that the SLF-I may be a separable tract from the cingulum. Lastly, the SLF subdivisions showed differentiable associations with major cognitive domains such as memory and executive functions. While histological confirmation is needed beyond tractography, these probabilistic masks offer a first step in guiding future exploration of frontoparietal organization by providing detailed characterization of the SLF subdivisions and their potential cortical terminations.Significance statement The prefrontal and posterior parietal areas are interconnected via the SLF, which has been characterized in great detail in monkeys. However, it is difficult to map the SLF organization in the human brain, and previous diffusion MRI findings have been inconsistent. Using diffusion MRI data from 707 individuals, our probabilistic tractography revealed dorsomedial-to-ventrolateral organization of the three SLF subdivisions and their cortical terminations. Our tractography also suggests limited shared volume between the SLF-I and the cingulum, a controversy in recent literature. The SLF subdivisions also differ in their cognitive associations. As a result, we created a large-scale, high-resolution probabilistic parcellation of the SLF, representing an advancement toward standardizing the mapping of human frontoparietal structural connections for clinical and scientific research.

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人类上纵束细分支及其皮层末端的大规模高分辨率概率图。
上纵束(SLF)是连接前额叶和顶叶后皮质的大白质联合束。过去对非人类灵长类动物的研究将SLF分为三个细分,并概述了每个细分的特定皮质-皮质组织和终止。然而,很难将人类的这些结构联系描述为动物的通道追踪研究的特异性。这导致了关于SLF在人脑中是如何组织的分歧,包括背内侧SLF (SLF- i)是否是扣带子系统的一部分。在这里,我们使用来自人类连接体计划(HCP)的高分辨率扩散成像数据,提出了一种新的大规模SLF细分概率图。我们使用302名成年男性和405名成年女性的图像数据对每个半球的三个SLF细分进行建模,并试图表征每个细分的额部和顶叶终止点。在每个受试者中成功地建立了SLF细分模型,显示出与非人灵长类动物组织学研究相似的背内侧到腹外侧组织。我们还发现排除和不排除扣带回的SLF-I模型之间的差异很小,这表明SLF-I可能是与扣带回可分离的束。最后,SLF的细分与记忆和执行功能等主要认知领域有不同的关联。虽然除了神经束造影之外还需要组织学证实,但这些概率掩膜提供了SLF细分及其潜在皮层终止的详细特征,为指导未来探索额顶叶组织提供了第一步。前额叶和后顶叶区通过SLF相互连接,这在猴子身上得到了非常详细的表征。然而,很难绘制人类大脑中SLF的组织,并且先前的弥散MRI结果不一致。利用来自707个个体的弥散MRI数据,我们的概率神经束造影显示了三个SLF分支的背内侧到腹外侧组织及其皮层末端。我们的束状带造影也显示在SLF-I和扣带之间共享的容量有限,这在最近的文献中是有争议的。SLF细分在认知关联方面也有所不同。因此,我们创建了一个大规模的,高分辨率的SLF概率分割,代表了临床和科学研究中标准化人类额顶叶结构连接映射的一个进步。
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来源期刊
Journal of Neuroscience
Journal of Neuroscience 医学-神经科学
CiteScore
9.30
自引率
3.80%
发文量
1164
审稿时长
12 months
期刊介绍: JNeurosci (ISSN 0270-6474) is an official journal of the Society for Neuroscience. It is published weekly by the Society, fifty weeks a year, one volume a year. JNeurosci publishes papers on a broad range of topics of general interest to those working on the nervous system. Authors now have an Open Choice option for their published articles
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