Suppr超能文献

用电源神经影像学技术在足月婴儿中识别新兴的介观-宏观功能大脑网络动力学。

Identifying Emergent Mesoscopic-Macroscopic Functional Brain Network Dynamics in Infants at Term-Equivalent Age with Electric Source Neuroimaging.

机构信息

University of Queensland Centre for Clinical Research, The University of Queensland, Herston, Brisbane, Queensland, Australia.

Royal Brisbane and Women's Hospital, Metro North Hospital and Health Service, Herston, Queensland, Australia.

出版信息

Brain Connect. 2021 Oct;11(8):663-677. doi: 10.1089/brain.2020.0965. Epub 2021 Apr 26.

Abstract

To identify and characterize the functional brain networks at the time when the brain is yet to develop higher order functions in term-born and preterm infants at term-equivalent age. Although functional magnetic resonance imaging (fMRI) data have revealed the existence of spatially structured resting-state brain activity in infants, the temporal information of fMRI data limits the characterization of fast timescale brain oscillations. In this study, we use infants' high-density electroencephalography (EEG) to characterize spatiotemporal and spectral functional organizations of brain network dynamics. We used source-reconstructed EEG and graph theoretical analyses in 100 infants (84 preterm, 16 term born) to identify the rich-club topological organization, temporal dynamics, and spectral fingerprints of dynamic functional brain networks. Five dynamic functional brain networks are identified, which have rich-club topological organizations, distinctive spectral fingerprints (in the delta and low-alpha frequency), and scale-invariant temporal dynamics (<0.1 Hz): The default mode, primary sensory-limbic system, thalamo-frontal, thalamo-sensorimotor, and visual-limbic system. The temporal dynamics of these networks are correlated in a hierarchically leading-following organization, showing that infant brain networks arise from long-range synchronization of band-limited cortical oscillation based on interacting fast- and slow-coherent cortical oscillations. Dynamic functional brain networks do not solely depend on the maturation of cognitive networks; instead, the brain network dynamics exist in infants at term age well before the childhood and adulthood, and hence, it offers a quantitative measurement of neurotypical development in infants. Clinical Trial Registration Number: ACTRN12615000591550. Impact statement Our work offers novel functional insights into the brain network characterization in infants, providing a new functional basis for future deployable prognostication approaches.

摘要

在足月和早产儿达到足月年龄时,识别和描述尚未发展出高级功能的大脑的功能网络。尽管功能磁共振成像(fMRI)数据已经揭示了在婴儿中存在具有空间结构的静息状态大脑活动,但 fMRI 数据的时间信息限制了对快速时间尺度大脑振荡的特征描述。在这项研究中,我们使用婴儿的高密度脑电图(EEG)来描述大脑网络动力学的时空和频谱功能组织。我们使用源重建 EEG 和图论分析在 100 名婴儿(84 名早产儿,16 名足月产儿)中识别丰富俱乐部拓扑组织、时间动态和动态功能大脑网络的频谱特征。确定了五个动态功能大脑网络,它们具有丰富俱乐部的拓扑组织、独特的频谱特征(在 delta 和低 alpha 频率)和标度不变的时间动态(<0.1 Hz):默认模式、主要感觉-边缘系统、丘脑-额皮质系统、丘脑感觉运动系统和视觉边缘系统。这些网络的时间动态以层次领先-跟随组织相关,表明婴儿大脑网络源自基于相互作用的快速和慢相干皮质振荡的皮质振荡的长程同步。动态功能大脑网络不仅取决于认知网络的成熟;相反,大脑网络动力学在婴儿达到足月年龄时就已经存在于儿童和成年期之前,因此,它为婴儿的神经典型发育提供了定量测量。临床试验注册号:ACTRN12615000591550。影响说明我们的工作为婴儿大脑网络特征提供了新的功能见解,为未来可部署的预测方法提供了新的功能基础。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验