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评估面部处理系统中网络拓扑结构的组织方式和特异性。

Evaluating the organizational structure and specificity of network topology within the face processing system.

机构信息

Department of Psychology, The Pennsylvania State University, University Park, Pennsylvania.

Department of Health & Human Development, The Pennsylvania State University, University Park, Pennsylvania.

出版信息

Hum Brain Mapp. 2019 Jun 15;40(9):2581-2595. doi: 10.1002/hbm.24546. Epub 2019 Feb 18.

Abstract

There is increasing appreciation that network-level interactions among regions produce components of face processing previously ascribed to individual regions. Our goals were to use an exhaustive data-driven approach to derive and quantify the topology of directed functional connections within a priori defined nodes of the face processing network and evaluate whether the topology is category-specific. Young adults were scanned with fMRI as they viewed movies of faces, objects, and scenes. We employed GIMME to model effective connectivity among core and extended face processing regions, which allowed us to evaluate all possible directional connections, under each viewing condition (face, object, place). During face processing, we observed directional connections from the right posterior superior temporal sulcus to both the right occipital face area and right fusiform face area (FFA), which does not reflect the topology reported in prior studies. We observed connectivity between core and extended regions during face processing, but this limited to a feed-forward connection from the FFA to the amygdala. Finally, the topology of connections was unique to face processing. These findings suggest that the pattern of directed functional connections within the face processing network, particularly in the right core regions, may not be as hierarchical and feed-forward as described previously. Our findings support the notion that topologies of network connections are specialized, emergent, and dynamically responsive to task demands.

摘要

人们越来越认识到,区域之间的网络级相互作用产生了先前归因于单个区域的面部处理成分。我们的目标是使用详尽的、数据驱动的方法来推导和量化预先定义的面部处理网络节点内的有向功能连接的拓扑结构,并评估拓扑结构是否具有类别特异性。年轻成年人在观看人脸、物体和场景的电影时接受 fMRI 扫描。我们采用 GIMME 来模拟核心和扩展面部处理区域之间的有效连接,这使我们能够在每种观察条件(人脸、物体、场所)下评估所有可能的定向连接。在处理面部时,我们观察到从右侧后颞上回到右侧枕部面部区域和右侧梭状回面部区域(FFA)的有向连接,这与先前研究报告的拓扑结构不同。我们在处理面部时观察到核心和扩展区域之间的连接,但仅限于从 FFA 到杏仁核的前馈连接。最后,连接的拓扑结构是专门针对面部处理的。这些发现表明,面部处理网络内的有向功能连接模式,特别是在右侧核心区域,可能不像以前描述的那样具有层次结构和前馈性。我们的发现支持这样一种观点,即网络连接的拓扑结构是专门化的、涌现的,并对任务需求具有动态响应能力。

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