Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuchang District, Wuhan, Hubei 430071, China.
Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuchang District, Wuhan, Hubei 430071, China.
Neuroimage. 2021 Nov 15;242:118473. doi: 10.1016/j.neuroimage.2021.118473. Epub 2021 Aug 12.
The age-related changes in the resting-state networks (RSNs) exhibited temporally specific patterns in humans, and humans and rhesus monkeys have similar RSNs. We hypothesized that the RSNs in rhesus monkeys experienced similar developmental patterns as humans.
We acquired resting-state fMRI data from 62 rhesus monkeys, which were divided into childhood, adolescence, and early adulthood groups. Group independent component analysis (ICA) was used to identify monkey RSNs. We detected the between-group differences in the RSNs and static, dynamic, and effective functional network connections (FNCs) using one-way variance analysis (ANOVA) and post-hoc analysis.
Eight rhesus RSNs were identified, including cerebellum (CN), left and right lateral visual (LVN and RVN), posterior default mode (pDMN), visuospatial (VSN), frontal (FN), salience (SN), and sensorimotor networks (SMN). In internal connections, the CN, SN, FN, and SMN mainly matured in early adulthood. The static FNCs associated with FN, SN, pDMN primarily experienced fast descending slow ascending type (U-shaped) developmental patterns for maturation, and the dynamic FNCs related to pDMN (RVN, CN, and SMN) and SMN (CN) were mature in early adulthood. The effective FNC results showed that the pDMN and VSN (stimulated), SN (inhibited), and FN (first inhibited then stimulated) chiefly matured in early adulthood.
We identified eight monkey RSNs, which exhibited similar development patterns as humans. All the RSNs and FNCs in monkeys were not widely changed but fine-tuned. Our study clarified that the progressive synchronization, exploration, and regulation of cognitive RSNs within the pDMN, FN, SN, and VSN denoted potential maturation of the RSNs throughout development. We confirmed the development patterns of RSNs and FNCs would support the use of monkeys as a best animal model for human brain function.
人类静息态网络（RSN）的年龄相关变化呈现出时间特异性模式，人类和恒河猴具有相似的 RSN。我们假设恒河猴的 RSN 经历了与人类相似的发育模式。
我们从 62 只恒河猴中获取了静息态 fMRI 数据，这些猴子分为儿童期、青春期和成年早期三个组。使用组独立成分分析（ICA）来识别猴子的 RSN。我们使用单向方差分析（ANOVA）和事后分析检测 RSN 以及静态、动态和有效功能网络连接（FNC）的组间差异。
鉴定出 8 个恒河猴 RSN，包括小脑（CN）、左右外侧视觉（LVN 和 RVN）、后默认模式（pDMN）、视空间（VSN）、额（FN）、突显（SN）和感觉运动网络（SMN）。在内部连接中，CN、SN、FN 和 SMN 主要在成年早期成熟。与 FN、SN、pDMN 相关的静态 FNC 主要经历快速下降、缓慢上升的 U 型发育模式成熟，与 pDMN（RVN、CN 和 SMN）和 SMN（CN）相关的动态 FNC 在成年早期成熟。有效 FNC 结果表明，pDMN 和 VSN（受刺激）、SN（受抑制）和 FN（先受抑制后受刺激）主要在成年早期成熟。
我们鉴定出 8 个猴子 RSN，它们表现出与人类相似的发育模式。猴子的所有 RSN 和 FNC 并没有广泛变化，而是进行了微调。我们的研究表明，pDMN、FN、SN 和 VSN 内认知 RSN 的逐步同步、探索和调节表示 RSN 在整个发育过程中的潜在成熟。我们证实 RSN 和 FNC 的发育模式将支持使用猴子作为研究人类大脑功能的最佳动物模型。
