Girn Manesh, Setton Roni, Turner Gary R, Spreng R Nathan
Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
Neuroscape, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
Netw Neurosci. 2024 Oct 1;8(3):860-882. doi: 10.1162/netn_a_00385. eCollection 2024.
Resting-state functional magnetic resonance imaging (fMRI) investigations have provided a view of the default network (DN) as composed of a specific set of frontal, parietal, and temporal cortical regions. This spatial topography is typically defined with reference to an influential network parcellation scheme that designated the DN as one of seven large-scale networks (Yeo et al., 2011). However, the precise functional organization of the DN is still under debate, with studies arguing for varying subnetwork configurations and the inclusion of subcortical regions. In this vein, the so-called limbic network-defined as a distinct large-scale network comprising the bilateral temporal poles, ventral anterior temporal lobes, and orbitofrontal cortex-is of particular interest. A large multi-modal and multi-species literature on the anatomical, functional, and cognitive properties of these regions suggests a close relationship to the DN. Notably, these regions have poor signal quality with conventional fMRI acquisition, likely obscuring their network affiliation in most studies. Here, we leverage a multi-echo fMRI dataset with high temporal signal-to-noise and whole-brain coverage, including orbitofrontal and anterior temporal regions, to examine the large-scale network resting-state functional connectivity of these regions and assess their associations with the DN. Consistent with our hypotheses, our results support the inclusion of the majority of the orbitofrontal and anterior temporal cortex as part of the DN and reveal significant heterogeneity in their functional connectivity. We observed that left-lateralized regions within the temporal poles and ventral anterior temporal lobes, as well as medial orbitofrontal regions, exhibited the greatest resting-state functional connectivity with the DN, with heterogeneity across DN subnetworks. Overall, our findings suggest that, rather than being a functionally distinct network, the orbitofrontal and anterior temporal regions comprise part of a larger, extended default network.
静息态功能磁共振成像（fMRI）研究揭示了默认网络（DN）由一组特定的额叶、顶叶和颞叶皮质区域组成。这种空间拓扑结构通常是参照一种有影响力的网络分割方案来定义的，该方案将DN指定为七个大规模网络之一（Yeo等人，2011年）。然而，DN的确切功能组织仍在争论中，一些研究主张不同的子网配置，并将皮质下区域纳入其中。在这种情况下，所谓的边缘网络——被定义为一个独特的大规模网络，包括双侧颞极、腹侧颞前叶和眶额皮质——特别令人感兴趣。关于这些区域的解剖、功能和认知特性的大量多模态和多物种文献表明它们与DN密切相关。值得注意的是，这些区域在传统fMRI采集中信号质量较差，这可能在大多数研究中掩盖了它们的网络归属关系。在这里，我们利用一个具有高时间信噪比和全脑覆盖的多回波fMRI数据集，包括眶额和颞前区域，来研究这些区域的大规模网络静息态功能连接性，并评估它们与DN的关联。与我们的假设一致，我们的结果支持将大部分眶额和颞前皮质纳入DN，并揭示了它们功能连接性的显著异质性。我们观察到，颞极和腹侧颞前叶内的左侧化区域以及内侧眶额区域与DN表现出最强的静息态功能连接，且在DN子网中存在异质性。总体而言，我们的研究结果表明，眶额和颞前区域并非一个功能上独特的网络，而是构成了一个更大的、扩展的默认网络的一部分。
