DeDe宝 (2023-02-01 00:18):
#paper https://doi.org/10.1016/j.neuroimage.2021.118723. NeuroImage 2018. Structural connectivity-based segmentation of the human entorhinal cortex 在啮齿动物中,将内嗅皮层分割为内侧(MEC)与外侧(LEC)具有明确的定义和特征。然而,在人类中,MEC和LEC的对应确切位置却仍然不确定。之前功能性磁共振成像 (fMRI) 研究已将人类内嗅皮层细分为后内侧 (pmEC) 和前外侧 (alEC)部分,但是成像方式和种子区域(seed)对划分结果的影响仍不明确。本研究使用扩散张量成像(DTI) 和概率纤维束成像,根据与已知选择性投射到的其他大脑区域的差异连接来分割人类内嗅皮层的MEC和LEC。我们将 MEC定义为与前下托和压后皮层(RSC) 的联系更紧密的内嗅皮层,LEC定义为与远端 CA1、近端dCA1pSub)以及外侧眶额叶皮层(OFC) 的联系更紧密的内嗅皮层。尽管我们的DTI分割比之前的 fMRI 研究具有更大的内侧-外侧成分,但我们的结果表明人类 MEC 和 LEC 同系物具有朝向后-前和内侧-外侧轴的边界,支持 pmEC 后内侧 (pmEC) 和前外侧 (alEC)的划分方式。
IF:4.700Q1 NeuroImage, 2021-12-15. DOI: 10.1016/j.neuroimage.2021.118723 PMID: 34780919
Structural connectivity-based segmentation of the human entorhinal cortex
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Abstract:
The medial (MEC) and lateral entorhinal cortex (LEC), widely studied in rodents, are well defined and characterized. In humans, however, the exact locations of their homologues remain uncertain. Previous functional magnetic resonance imaging (fMRI) studies have subdivided the human EC into posteromedial (pmEC) and anterolateral (alEC) parts, but uncertainty remains about the choice of imaging modality and seed regions, in particular in light of a substantial revision of the classical model of EC connectivity based on novel insights from rodent anatomy. Here, we used structural, not functional imaging, namely diffusion tensor imaging (DTI) and probabilistic tractography to segment the human EC based on differential connectivity to other brain regions known to project selectively to MEC or LEC. We defined MEC as more strongly connected with presubiculum and retrosplenial cortex (RSC), and LEC as more strongly connected with distal CA1 and proximal subiculum (dCA1pSub) and lateral orbitofrontal cortex (OFC). Although our DTI segmentation had a larger medial-lateral component than in the previous fMRI studies, our results show that the human MEC and LEC homologues have a border oriented both towards the posterior-anterior and medial-lateral axes, supporting the differentiation between pmEC and alEC.
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