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The resting-state cerebro-cerebellar function connectivity and associations with verbal working memory performance
Behavioural Brain Research ( IF 2.7 ) Pub Date : 2021-09-15 , DOI: 10.1016/j.bbr.2021.113586
Yanyan Li 1 , Lihao Yang 1 , Lihua Li 1 , Yuanjun Xie 2 , Peng Fang 3
Affiliation  

The cerebellum plays an important role in cognitive functions through connecting with the cerebral cortical areas. However, the relationship between the resting-state functional connectivity (FC) pattern of human cerebro-cerebellar circuits and cognition is not fully understood. The present study investigated the FC patterns of human cerebro-cerebellar circuits and their associations with verbal working memory performance (an n-back task with three subtasks: 0-back, 1-back, and 2-back) through resting-state functional magnetic resonance imaging (fMRI) data from 34 healthy subjects. The whole-brain connectivity analysis was used to identify the cortical hubs as regions of interest (ROI). Then ROI-based FC analysis was performed to investigate the connectivity characteristics within the key cortical hubs and their associations with n-back task performance. The results showed that the bilateral cerebellum lobule VI as central hubs had increased FC with the default mode network (DMN) node (e.g., right posterior cingulate cortex) and salient network (SN) node (e.g., right anterior cingulate cortex), while decreased FC with the executive control network (ECN) node (e.g., the bilateral superior frontal gyrus). Furthermore, FC values of the cerebellum lobule VI with DMN and ECN nodes correlated with verbal working memory performance (response time of 2-back task). The results suggest that the cerebro-cerebellar circuits involve the underlying neural basis of verbal working memory processing during the resting state.



中文翻译:

静息状态脑-小脑功能连接性和与言语工作记忆表现的关联

小脑通过与大脑皮层区域的连接,在认知功能中起重要作用。然而,人类脑小脑回路的静息状态功能连接(FC)模式与认知之间的关系尚不完全清楚。本研究通过静息状态功能磁研究了人类脑-小脑回路的 FC 模式及其与言语工作记忆表现(具有三个子任务的 n-back 任务:0-back、1-back 和 2-back)的关联。来自 34 名健康受试者的共振成像 (fMRI) 数据。全脑连接分析用于将皮质中枢识别为感兴趣区域 (ROI)。然后进行基于 ROI 的 FC 分析,以研究关键皮层中枢内的连接特征及其与 n-back 任务性能的关联。结果表明,作为中心枢纽的双侧小脑小叶VI与默认模式网络(DMN)节点(例如,右后扣带回皮层)和显着网络(SN)节点(例如,右前扣带回皮层)的FC增加,而减少FC 与执行控制网络 (ECN) 节点(例如,双侧额上回)。此外,带有 DMN 和 ECN 节点的小脑小叶 VI 的 FC 值与言语工作记忆表现(2-back 任务的响应时间)相关。结果表明,脑-小脑回路涉及静息状态下语言工作记忆处理的潜在神经基础。右后扣带皮层)和显着网络(SN)节点(例如,右前扣带皮层),而执行控制网络(ECN)节点(例如,双侧额上回)的FC减少。此外,带有 DMN 和 ECN 节点的小脑小叶 VI 的 FC 值与言语工作记忆表现(2-back 任务的响应时间)相关。结果表明,脑-小脑回路涉及静息状态下语言工作记忆处理的潜在神经基础。右后扣带皮层)和显着网络(SN)节点(例如,右前扣带皮层),而执行控制网络(ECN)节点(例如,双侧额上回)的FC减少。此外,带有 DMN 和 ECN 节点的小脑小叶 VI 的 FC 值与言语工作记忆表现(2-back 任务的响应时间)相关。结果表明,脑-小脑回路涉及静息状态下语言工作记忆处理的潜在神经基础。

更新日期:2021-09-22
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