基于Behavior partial least squares方法的结构功能默认网络相关性研究

默认网络近年来受到了人们的广泛关注,然而之前的研究主要分别研究结构默认网络和功能默认网络的变化,关于它们之间相关性的研究相对来说较少.文章对280个健康被试运用Behavior partial least squares(PLS)的方法研究了两种默认网络相关性随着年龄的变化.研究发现默认网络中前部和后部之间的连接较强,就脑区来说楔前叶,前扣带回和顶下小叶和其它脑区之间的连接较强,并且年龄的变化没有引起相关性的显著差异.我们的研究有助于进一步理解大脑结构和功能之间的相互关系,并且证实Behavior PLS是一种适合进行多模态融合研究的统计方法.

Default mode network(DMN)has attracted consistent attention in recent years.However,previous studies mainly focused on the age-related changes of structural default networkand functional default network,and relatively few studies focus on the relationship between structural and functional DMNs.In this paper,we investigated the relationship between the structural and functional DMNS in 280 healthy subjects using Behavior Partial Least Squares(PLS)across the adult lifespan(16-85 years old).The study found that the connections between the front and back parts of the default network were strong.For the brain reons,the connections between the anterior cuneiform lobe,the anterior cingulate gyrus,the Inferior parietal lobuleand other brain regions were strong.The structure-function relationship did not show significant age-related differences.Our research conributes to further understand the relationship between brain structure and function,and confirms that Behavior PLS is a suitable statistical method for multimodal fusion research.