Department of Electronic, Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea.
Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea.
Hum Brain Mapp. 2018 Mar;39(3):1380-1390. doi: 10.1002/hbm.23926. Epub 2017 Dec 17.
Human brain can be divided into multiple brain regions based on anatomical and functional properties. Recent studies showed that resting-state connectivity can be utilized for parcellating brain regions and identifying their distinctive roles. In this study, we aimed to parcellate the primary and secondary visual cortices (V1 and V2) into several subregions based on functional connectivity and to examine the functional characteristics of each subregion. We used resting-state data from a research database and also acquired resting-state data with retinotopy results from a local site. The long-range connectivity profile and three different algorithms (i.e., K-means, Gaussian mixture model distribution, and Ward's clustering algorithms) were adopted for the parcellation. We compared the parcellation results within V1 and V2 with the eccentric map in retinotopy. We found that the boundaries between subregions within V1 and V2 were located in the parafovea, indicating that the anterior and posterior subregions within V1 and V2 corresponded to peripheral and central visual field representations, respectively. Next, we computed correlations between each subregion within V1 and V2 and intermediate and high-order regions in ventral and dorsal visual pathways. We found that the anterior subregions of V1 and V2 were strongly associated with regions in the dorsal stream (V3A and inferior parietal gyrus), whereas the posterior subregions of V1 and V2 were highly related to regions in the ventral stream (V4v and inferior temporal gyrus). Our findings suggest that the anterior and posterior subregions of V1 and V2, parcellated based on functional connectivity, may have distinct functional properties.
人脑可以根据解剖和功能特性分为多个脑区。最近的研究表明,静息态连接可用于分割脑区并识别其独特的作用。在这项研究中,我们旨在根据功能连接将初级和次级视觉皮层(V1 和 V2)划分为几个子区域,并研究每个子区域的功能特征。我们使用来自研究数据库的静息态数据,并从本地站点获取具有视网膜定位结果的静息态数据。采用长程连接谱和三种不同算法(即 K-均值、高斯混合模型分布和 Ward 聚类算法)进行分割。我们将 V1 和 V2 内的分割结果与视网膜定位中的偏心图进行了比较。我们发现 V1 和 V2 内子区域之间的边界位于周边视野,表明 V1 和 V2 内的前、后子区域分别对应于外周和中央视野的代表。接下来,我们计算了 V1 和 V2 内每个子区域与腹侧和背侧视觉通路中中级和高级区域之间的相关性。我们发现 V1 和 V2 的前子区域与背侧流中的区域(V3A 和下顶叶回)强烈相关,而 V1 和 V2 的后子区域与腹侧流中的区域(V4v 和下颞叶回)高度相关。我们的发现表明,基于功能连接划分的 V1 和 V2 的前、后子区域可能具有不同的功能特性。