Suppr超能文献

动态网络组织状态下范畴性与坐标性空间关系的分离

Dissociation of categorical and coordinate spatial relations on dynamic network organization states.

作者信息

Hao Xin, Chen Zhencai, Huang Taicheng, Song Yiying, Kong Xiangzhen, Liu Jia

机构信息

Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China.

School of Psychology, Central China Normal University, Wuhan, China.

出版信息

Front Hum Neurosci. 2022 Nov 17;16:972375. doi: 10.3389/fnhum.2022.972375. eCollection 2022.

Abstract

Humans can flexibly represent both categorical and coordinate spatial relations. Previous research has mainly focused on hemisphere lateralization in representing these two types of spatial relations, but little is known about how distinct network organization states support representations of the two. Here we used dynamic resting-state functional connectivity (FC) to explore this question. To do this, we separated a meta-identified navigation network into a ventral and two other subnetworks. We revealed a Weak State and a Strong State within the ventral subnetwork and a Negative State and a Positive State between the ventral and other subnetworks. Further, we found the Weak State (i.e., weak but positive FC) within the ventral subnetwork was related to the ability of categorical relation recognition, suggesting that the representation of categorical spatial relations was related to weak integration among focal regions in the navigation network. In contrast, the Negative State (i.e., negative FC) between the ventral and other subnetworks was associated with the ability of coordinate relation processing, suggesting that the representation of coordinate spatial relations may require competitive interactions among widely distributed regions. In sum, our study provides the first empirical evidence revealing different focal and distributed organizations of the navigation network in representing different types of spatial information.

摘要

人类能够灵活地呈现分类和坐标空间关系。以往的研究主要集中在半球在呈现这两种空间关系时的侧化,但对于不同的网络组织状态如何支持这两种关系的呈现却知之甚少。在这里,我们使用动态静息态功能连接(FC)来探讨这个问题。为此,我们将一个经元分析确定的导航网络分为一个腹侧子网和另外两个子网。我们在腹侧子网内揭示了一种弱状态和一种强状态,在腹侧子网与其他子网之间揭示了一种负状态和一种正状态。此外,我们发现腹侧子网内的弱状态(即弱但为正的FC)与分类关系识别能力有关,这表明分类空间关系的呈现与导航网络中焦点区域之间的弱整合有关。相反,腹侧子网与其他子网之间的负状态(即负FC)与坐标关系处理能力相关,这表明坐标空间关系的呈现可能需要广泛分布区域之间的竞争性相互作用。总之,我们的研究提供了首个实证证据,揭示了导航网络在呈现不同类型空间信息时不同的焦点式和分布式组织。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ea3/9713938/25b849386204/fnhum-16-972375-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验