Multimodal evaluation of the amygdala's functional connectivity.
Multimodal evaluation of the amygdala's functional connectivity.
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DOI：
10.1016/j.neuroimage.2016.12.023
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发表时间：
2017-03-01
期刊：
影响因子：
5.7
通讯作者：
Eickhoff SB
中科院分区：
文献类型：
--
作者：
Kerestes R;Chase HW;Phillips ML;Ladouceur CD;Eickhoff SB
杏仁核是研究最广泛的人类大脑区域之一，毫无疑问在许多精神疾病中发挥着核心作用。然而，一个悬而未决的问题是杏仁核亚区域的连接性，特别是中央内侧核（CM）、外侧基底核（LB）和浅层核（SF），是否受到大脑状态（即任务与休息）的调节。在这里，使用多模态方法，我们直接将荟萃分析连接模型（MACM）和特定共激活可能性估计（SCALE）衍生的基于CM、LB和SF任务的共激活的估计与通过静息状态fmri（rs-fmri）评估的这些细胞核的功能连接进行比较。最后，使用预先存在的静息态功能连接衍生的皮质分区，我们检查了 MACM 和 rs-fmri 杏仁核子区域与 17 个大型网络的连接性，以明确解决杏仁核如何与其他大型神经网络相互作用。分析揭示了 CM、LB 和 SF 连接模式与其他大脑区域的显着差异，无论是在任务依赖型还是任务无关型环境中。然而，所有三个区域都显示出与右腹外侧前额叶皮层（VLPFC）的聚合连接，该连接不是由高基础激活率水平驱动的。每个子区域观察到跨 rs-fmri 和 MACM 的相似连接模式，表明每个子区域的任务和静息状态下杏仁核与大脑其他部分的连接具有相似的网络架构，可以根据特定任务需求进行修改。这些发现支持动物模型提出了杏仁核功能的平行模型，但重要的是，也修改了这一立场以表明杏仁核中的整合处理。
The amygdala is one of the most extensively studied human brain regions and undisputedly plays a central role in many psychiatric disorders. However, an outstanding question is whether connectivity of amygdala subregions, specifically the centromedial (CM), laterobasal (LB) and superficial (SF) nuclei, are modulated by brain state (i.e., task vs. rest). Here, using a multimodal approach, we directly compared meta-analytic connectivity modeling (MACM) and specific co-activation likelihood estimation (SCALE)-derived estimates of CM, LB and SF task-based co-activation to the functional connectivity of these nuclei as assessed by resting state fmri (rs-fmri). Finally, using a preexisting resting state functional connectivity-derived cortical parcellation, we examined both MACM and rs-fmri amygdala subregion connectivity with 17 large-scale networks, to explicitly address how the amygdala interacts with other large-scale neural networks. Analyses revealed strong differentiation of CM, LB and SF connectivity patterns with other brain regions, both in task-dependent and task-independent contexts. All three regions, however, showed convergent connectivity with the right ventrolateral prefrontal cortex (VLPFC) that was not driven by high base rate levels of activation. Similar patterns of connectivity across rs-fmri and MACM were observed for each subregion, suggesting a similar network architecture of amygdala connectivity with the rest of the brain across tasks and resting state for each subregion, that may be modified in the context of specific task demands. These findings support animal models that posit a parallel model of amygdala functioning, but importantly, also modify this position to suggest integrative processing in the amygdala.