Data-driven analysis of analogous brain networks in monkeys and humans during natural vision.
Data-driven analysis of analogous brain networks in monkeys and humans during natural vision.
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DOI：
10.1016/j.neuroimage.2012.08.042
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发表时间：
2012-11-15
期刊：
影响因子：
5.7
通讯作者：
Vanduffel, Wim
中科院分区：
文献类型：
--
作者：
Mantini, Dante;Corbetta, Maurizio;Romani, Gian Luca;Orban, Guy A.;Vanduffel, Wim
关键词：
关于人类和非人类灵长类动物功能网络之间的功能对应关系的推断很大程度上依赖于邻近性和解剖扩展模型。然而，已经证明两个物种的拓扑对应区域可以具有不同的功能特性，这表明基于解剖学的方法应该辅以替代方法来进行功能比较。我们最近表明，基于感觉驱动的功能磁共振成像反应的时间相关性的比较分析可以揭示猴子和人类的功能对应区域，而无需依赖空间假设。物种间活动相关性 (ISAC) 分析需要定义一个物种的种子区域，以揭示同一物种和其他物种皮层的功能对应关系。在这里，我们提出了 ISAC 方法的扩展，该方法不依赖于任何种子定义，因此该方法没有任何空间假设。具体来说，我们分别对猴子和人类数据应用独立成分分析（ICA），以定义具有连贯刺激相关活动的物种特定区域网络。然后，我们使用层次聚类分析来识别具有相似时间进程的猴子和人类网络的基于 ICA 的 ISAC 聚类。我们对猴子和人类在看电影期间收集的功能磁共振成像数据实施了这种方法，这种情况会在大部分皮层中引起广泛的感觉驱动活动。使用基于 ICA 的 ISAC，我们检测到了七个猴-人集群。几个簇的时间进程显示出与电影中的运动能量或眼睛运动参数的显着对应关系。其中五个簇跨越了主要或纹状体视觉区域中假定的同源功能网络，而两个簇包括位于皮质表面扩展模型无法预测的拓扑位置的更高级别的视觉区域。总体而言，我们基于 ICA 的 ISAC 分析补充了我们之前基于种子的研究结果，并表明功能过程可以由不同物种的大脑网络执行，这些网络在功能上但不一定在解剖学上对应。总的来说，我们的方法提供了一种新颖的方法来揭示灵长类动物大脑中进化驱动的功能变化，而无需空间假设。
Inferences about functional correspondences between functional networks of human and non-human primates largely rely on proximity and anatomical expansion models. However, it has been demonstrated that topologically correspondent areas in two species can have different functional properties, suggesting that anatomy-based approaches should be complemented with alternative methods to perform functional comparisons. We have recently shown that comparative analyses based on temporal correlations of sensory-driven fMRI responses can reveal functional correspondent areas in monkeys and humans without relying on spatial assumptions. Inter-species activity correlation (ISAC) analyses require the definition of seed areas in one species to reveal functional correspondences across the cortex of the same and other species. Here we propose an extension of the ISAC method that does not rely on any seed definition, hence a method void of any spatial assumption. Specifically, we apply independent component analysis (ICA) separately to monkey and human data to define species-specific networks of areas with coherent stimulus-related activity. Then, we use a hierarchical cluster analysis to identify ICA-based ISAC clusters of monkey and human networks with similar timecourses. We implemented this approach on fMRI data collected in monkeys and humans during movie watching, a condition that evokes widespread sensory-driven activity throughout large portions of the cortex. Using ICA-based ISAC, we detected seven monkey-human clusters. The timecourses of several clusters showed significant correspondences with either the motion energy in the movie or with eye-movement parameters. Five of the clusters spanned putative homologous functional networks in either primary or extrastriate visual regions, whereas two clusters included higher-level visual areas at topological locations that are not predicted by cortical surface expansion models. Overall, our ICA-based ISAC analysis complemented the findings of our previous seed-based investigations, and suggested that functional processes can be executed by brain networks in different species that are functionally but not necessarily anatomically correspondent. Overall, our method provides a novel approach to reveal evolution-driven functional changes in the primate brain with no spatial assumptions.
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DOI：
10.1098/rstb.2005.1627
发表时间：
2005-04-29
影响因子：
6.3
作者：
Bartels, A;Zeki, S
通讯作者：
Zeki, S
影响因子：
5.3
作者：
Moeller, Sebastian;Nallasamy, Nambi;Freiwald, Winrich A.
通讯作者：
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影响因子：
3.7
作者：
Joly, Olivier;Ramus, Franck;Orban, Guy A.
通讯作者：
Orban, Guy A.
影响因子：
56.9
作者：
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通讯作者：
Malach, R
影响因子：
5.3
作者：
Denys, K;Vanduffel, W;Orban, GA
通讯作者：
Orban, GA