基于静息态 fMRI 的多水平独立成分分析的基底节和丘脑的功能连接的细分。
Functional connectivity-based identification of subdivisions of the basal ganglia and thalamus using multilevel independent component analysis of resting state fMRI.
机构信息
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
出版信息
Hum Brain Mapp. 2013 Jun;34(6):1371-85. doi: 10.1002/hbm.21517. Epub 2012 Feb 14.
This study aimed to identify subunits of the basal ganglia and thalamus and to investigate the functional connectivity among these anatomically segregated subdivisions and the cerebral cortex in healthy subjects. For this purpose, we introduced multilevel independent component analysis (ICA) of the resting-state functional magnetic resonance imaging (fMRI). After applying ICA to the whole brain gray matter, we applied second-level ICA restrictively to the basal ganglia and the thalamus area to identify discrete functional subunits of those regions. As a result, the basal ganglia and the thalamus were parcelled into 31 functional subdivisions according to their temporal activity patterns. The extracted parcels showed functional network connectivity between hemispheres, between subdivisions of the basal ganglia and thalamus, and between the extracted subdivisions and cerebral functional components. Grossly, these findings correspond to cortico-striato-thalamo-cortical circuits in the brain. This study also showed the utility of multilevel ICA of resting state fMRI in brain network research.
本研究旨在鉴定基底神经节和丘脑的亚基,并探讨这些解剖分离的细分与大脑皮层在健康个体中的功能连接。为此,我们引入了静息态功能磁共振成像(fMRI)的多层次独立成分分析(ICA)。在对整个大脑灰质进行 ICA 处理后,我们将二级 ICA 有针对性地应用于基底神经节和丘脑区域,以鉴定这些区域的离散功能亚基。结果,基底神经节和丘脑根据其时间活动模式被分割成 31 个功能细分。提取的包裹显示出大脑半球之间、基底神经节和丘脑的细分之间以及提取的细分与大脑功能成分之间的功能网络连接。总的来说,这些发现与大脑中的皮质纹状体丘脑皮质回路相对应。本研究还表明,静息状态 fMRI 的多层次 ICA 在脑网络研究中的实用性。