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A cross-modal, cross-species comparison of connectivity measures in the primate brain

机译:一种跨模型,跨物种与脑电脑连接措施的比较

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摘要

In systems neuroscience, the term “connectivity” has been defined in numerous ways, according to the particular empirical modality from which it is derived. Due to large differences in the phenomena measured by these modalities, the assumptions necessary to make inferences about axonal connections, and the limitations accompanying each, brain connectivity remains an elusive concept. Despite this, only a handful of studies have directly compared connectivity as inferred from multiple modalities, and there remains much ambiguity over what the term is actually referring to as a biological construct. Here, we perform a direct comparison based on the high-resolution and high-contrast Enhanced Nathan Klein Institute (NKI) Rockland Sample neuroimaging data set, and the CoCoMac database of tract tracing studies. We compare four types of commonly-used primate connectivity analyses: tract tracing experiments, compiled in CoCoMac; group-wise correlation of cortical thickness; tractographic networks computed from diffusion-weighted MRI (DWI); and correlational networks obtained from resting-state BOLD (fMRI). We find generally poor correspondence between all four modalities, in terms of correlated edge weights, binarized comparisons of thresholded networks, and clustering patterns. fMRI and DWI had the best agreement, followed by DWI and CoCoMac, while other comparisons showed striking divergence. Networks had the best correspondence for local ipsilateral and homotopic contralateral connections, and the worst correspondence for long-range and heterotopic contralateral connections. k-Means clustering highlighted the lowest cross-modal and cross-species consensus in lateral and medial temporal lobes, anterior cingulate, and the temporoparietal junction. Comparing the NKI results to those of the lower resolution/contrast International Consortium for Brain Imaging (ICBM) dataset, we find that the relative pattern of intermodal relationships is preserved, but the correspondence between human imaging connectomes is substantially better for NKI. These findings caution against using “connectivity” as an umbrella term for results derived from single empirical modalities, and suggest that any interpretation of these results should account for (and ideally help explain) the lack of multimodal correspondence.
机译:在系统神经科学中,术语“连通性”已经以许多方式定义,根据其衍生的特定经验方式。由于这些模态测量的现象的差异,所需的假设是对轴突连接的推断,以及各自的伴随的限制仍然是难以捉摸的概念。尽管如此,只有少数的研究直接比较了从多种方式推断的连接,并且对该术语实际称为生物学构建的情况仍然存在巨大歧义。在这里,我们基于高分辨率和高对比度增强的Nathan Klein Institute(NKI)Rockland样本神经影像数据集,以及道路追踪研究的CocoMac数据库的直接比较。我们比较四种类型的常用灵长类动物连接分析:在Cocomac编制的道路追踪实验;群体明智的皮质厚度相关;从扩散加权MRI(DWI)计算的左右传递网络;和从休息状态粗体(FMRI)获得的相关网络。在相关的边缘权重方面,我们发现所有四种模式之间的对应相对不良,阈值网络的二值化比较和聚类模式。 FMRI和DWI具有最佳协议,其次是DWI和Cocomac,而其他比较表现出惊人的分歧。网络对局部同侧和同型对侧连接的最佳对应性,以及对长期和异位对侧连接的最差的对应关系。 K-Means集群突出显示横向和内侧颞叶,前筒和颞逐交界处的最低跨越式和跨物种共识。将NKI结果与脑成像(ICBM)数据集的较低分辨率/对比国际联盟的结果进行比较,我们发现保留了多种关系的相对模式,但人体成像Conceptomes之间的对应性对于NKI而言基本更好。这些调查结果谨慎使用“连接”作为从单一经验方式导出的结果的伞术语,并表明对这些结果的任何解释都应占(并且理想地帮助解释)缺乏多模式对应。

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