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

机译:灵长类动物大脑中连通性度量的跨模式,跨物种比较

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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. (C) 2015 Elsevier Inc. All rights reserved.
机译:在系统神经科学中,术语“连通性”已根据其衍生的特定经验形式以多种方式定义。由于这些方式所测量的现象之间存在很大差异,因此需要做出关于轴突连接的推断所必需的假设,以及伴随每个轴突的局限性,大脑的连接性仍然难以捉摸。尽管如此,只有少数研究直接比较了从多种方式推断出的连通性,并且对于该术语实际上指的是生物构建体仍然存在很多歧义。在这里,我们基于高分辨率和高对比度的增强型内森·克莱因研究所(NKI)的Rockland Sample神经成像数据集,以及道追踪研究的CoCoMac数据库,进行了直接比较。我们比较了四种常用的灵长类动物连通性分析:在CoCoMac中编译的管道追踪实验;皮质厚度的分组相关性;根据扩散加权MRI(DWI)计算出的束状图网络;以及从静止状态BOLD(fMRI)获得的相关网络。我们发现,在相关边缘权重,阈值网络的二值化比较和聚类模式方面,这四个模态之间的对应关系普遍较差。 fMRI和DWI的一致性最佳,其次是DWI和CoCoMac,而其他比较则显示出惊人的分歧。对于局部同侧和同位对侧连接,网络具有最佳对应关系,而对于远程和异位对侧连接,网络具有最差的对应关系。 k-均值聚类突出显示了外侧和内侧颞叶,前扣带回和颞顶交界处的最低跨模态和跨物种共识。将NKI结果与较低分辨率/对比度的国际脑成像协会(ICBM)数据集的结果进行比较,我们发现保留了联运关系的相对模式,但是对于NKI,人类成像连接体之间的对应关系要好得多。这些发现警告不要将“连通性”用作从单一经验模态得出的结果的总称,并建议对这些结果的任何解释都应说明(最好是有助于解释)多模态对应关系的缺乏。 (C)2015 Elsevier Inc.保留所有权利。

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