Laboratory of Neuro- and Psychophysiology, KU Leuven Medical School, Leuven, Belgium.
Neuroimage. 2012 Nov 15;63(3):1107-18. doi: 10.1016/j.neuroimage.2012.08.042. Epub 2012 Aug 21.
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 either with 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.
在人类和非人类灵长类动物的功能网络之间进行功能对应关系的推断，在很大程度上依赖于邻近和解剖扩展模型。然而，已经证明，两种物种中拓扑上对应的区域可能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 fMRI 响应的时间相关性的比较分析，可以揭示猴子和人类中没有依赖于空间假设的功能对应区域。种间活动相关性 (ISAC) 分析需要在一种物种中定义种子区域，以揭示同一物种和其他物种皮层上的功能对应关系。在这里，我们提出了一种 ISAC 方法的扩展，该方法不依赖于任何种子定义，因此是一种没有任何空间假设的方法。具体来说，我们分别对猴子和人类的数据应用独立成分分析 (ICA)，以定义具有相干刺激相关活动的区域的物种特异性网络。然后，我们使用层次聚类分析来识别猴子和人类网络中具有相似时间历程的基于 ICA 的 ISAC 聚类。我们在猴子和人类观看电影时收集的 fMRI 数据上实施了这种方法，这种条件会在大脑皮层的大部分区域引发广泛的感觉驱动活动。使用基于 ICA 的 ISAC，我们检测到七个猴子-人类集群。几个集群的时间历程显示出与电影中的运动能量或眼动参数的显著对应关系。五个集群跨越了初级或外纹状视觉区域中假定的同源功能网络，而两个集群包括拓扑位置上的高级视觉区域，这些区域不是由皮质表面扩展模型预测的。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的发现，并表明功能过程可以由不同物种的大脑网络执行，这些网络在功能上而不是在解剖学上对应。总的来说，我们的方法提供了一种新颖的方法，可以揭示灵长类动物大脑中没有空间假设的进化驱动的功能变化。
